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International Journal of the Sociology of Language, 27, 35-58.

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APPENDICES

APPENDIX A: THE DISCOURSE COMPLETION TEST

Dear student,

Thank you in advance for your participation in this research and for completing this questionnaire. By completing this questionnaire, you agree that I can use your responses for research purposes and possible publications. All your identifying information will be anonymized when the results of this study are presented, written up and/or published. Furthermore, all data I collect for this research will be retained securely.

This questionnaire contains two parts. In part 1, please write down your age and indicate your gender and also write your native language and university major. In part 2 please complete the scenarios.

Part 1

Age: ……….

Gender: ……..

Native Language: .................................

University major? .................................

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Part 2

There are ten situations described below. Please read the description of each situation carefully and write down what you would say in the individual situations.

1. You have borrowed your friend‟s notes and because of the rain yesterday, some of

the notes have been wet and damaged. What would you say when you want to return

the notes?

2. You have promised to deliver a lecture in class but due to a very bad cold, you

have not been able to even attend the class. What would you say to your professor

the next session you attend the class?

3. The university bus is very crowded so you are standing in the bus. The bus driver

suddenly brakes and you lose your control and step on a fellow student‟s foot. What

would you say?

4. You have promised one of the university staff to fill in and return a form two days

ago but you have a two day delay. What would you say when you want to return the

form?

5. You have promised your younger sister/brother to take her/him to the cinema and

you have forgotten to do so. She/he has been waiting for you at home for hours, what

would you say to her/him as you get home?

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6. You have been supposed to meet your close friend at the university library to

exchange some books and you get there an hour later and find your friend still

waiting for you at the library. What would you say to your friend as you see her?

7. As you are talking to one of the university staff, you accidentally spill the cup of

tea on his/her desk. What would you say?

8. You were expected by your supervisor to discuss some of your problems but due

to a heavy traffic, you are 45 minutes late. What would you say to your supervisor as

you see him/her?

9. As you are carrying a chair in the lobby of the university, you hurt a fellow

student‟s hand accidentally. What would you say?

10. You have promised your younger sister/ brother to buy her/him a book from the

bookstore but you have forgotten. What would you say to her/him?

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APPENDIX B: THE QUESTIONNAIRE RESPONSES

Responses to Question Number (1)

1. You have borrowed your friend‟s notes and because of the rain yesterday, some of

the notes have been wet and damaged. What would you say when you want to return

the notes?

Male (1): I‟ve got your notes here but they are not in a good condition. I‟m really

sorry! I can type and then print them out for you if you want.

Male (2): I‟m sorry buddy! Your notes have been damaged because of raining

yesterday. Don‟t worry about it, I would prepare the exact copy of your notes and I‟ll

give you in only one day.

Male (3): Unfortunately on my way back to home it started to rain and I couldn‟t

protect your notes, so some of them are wet or damaged. I am terribly sorry and hope

to make it up to you.

Male (4): It is inconsiderate of me that I could not take care of your notes properly. I

apologize!

Male (5): I feel ashamed. Your notes got wet because of the rain. I„ll make it up to

you by copying them.

Male (6): I apologize! Your notes have been damaged because of the rain, so I have

copied them.

Male (7): I am so sorry about that! Please forgive me! Is there anything I can do

about it? I can rewrite them for you.

Male (8): Your notes got wet because of the rain.

Male (9): Your notes have been wet and damaged because of the rain. I‟ll help u to

retrieve and rewrite them.

Male (10): I am sorry for what happened, although I didn‟t do it on purpose.

Male (11): I`m so sorry, hehe, take it easy.

Male (12): I really apologize! I will solve the problem.

Male (13): It wasn‟t my fault, this bloody rain damaged your notes. I‟ll write them

nicely and give them back to you.

Male (14): Your notes have been damaged because of the rain, but I‟ll do my best to

make it up to you.

Male (15): I‟ve made a fresh copy of your notes.

Male (16): I‟m sorry!

Male (17): I‟m really sorry! The rain has damaged some of your notes. I tried my

best to protect them, but I couldn‟t. Is there anything I could possibly do for you? If

you have the soft copy, I‟ll print out the notes.

Male (18): I‟m so embarrassed. Please accept my apology.

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Male (19): I am terribly sorry! Let me do something to make it up to you.

Male (20): I‟m really so sorry! I didn‟t want to do that, but let me find another notes

for you then. Sorry again dude!

Female (1): I want to tell you something about your notes, unfortunately your notes

got wet in the heavy rain yesterday and it wasn‟t my fault. I am so sorry about that. If

you let me, I will copy them. Sorry again.

Female (2): I am so sorry that I gave you this bad experience. I will never forgive

myself because of my carelessness, please forgive my fault.

Female (3): I‟m so so sorry, I didn‟t take good care of your notes. Some parts have

been damaged because of the rain. I‟ll rewrite them for you if you want. Do you

think you can still use them?

Female (4): I know I‟m guilty and I will try to find notes and write them to you as

soon as possible.

Female (5): I am so sorry some notes became wet. I will try to make it up to you.

Female (6): I am so sorry my dear, but it was out of my control, they got wet

because of the rain. How can I make it up to you?

Female (7): I am terribly sorry for what happened! It was raining cats and dogs. I

am so sorry! If you can wait I will do my best to prepare a new copy of what you

gave me.

Female (8): The notes I borrowed were damaged in the rain. I‟m really sorry about

that! It happened accidentally. I was really worried and didn't know how to return it.

Female (9): I really don‟t know how to apologize!! It happened and was out of my

control. I‟m so sorry!

Female (10): I am really sorry but it was not my mistake and it was out of my

control.

Female (11): I'm so ashamed to say that some of the notes have been damaged. It

was rainy. I should have taken an umbrella. I tried to write it again but it didn't

work. Is there anybody else who has these notes? Sorry again!

Female (12): I copy them or write them again.

Female (13): I would like to appreciate you for what you have done for me. Thanks

a lot.

Female (14): I‟m ashamed.

Female (15): Dear friend, I‟m so so so sorry! The rain damaged your notes

yesterday and it was not really my fault. I feel awful .Let me rewrite or copy them

for you.

Female (16): I‟m very very sorry that your notes got wet but God knows it wasn‟t

my fault because the rain ruined them. I hope it doesn‟t upset you as I have copied

all of them.

Female (17): I‟m ashamed to say it, but the pamphlets you gave me got wet

yesterday, sorry… Should I write the notes again for you in a clean paper?

Female (18): I‟m so sorry! I do apologize for ruining your notes.

Female (19): I don‟t know what to say but I‟m really sorry! If you want I can fix it.

Female (20): Let me tell you what happened. I‟ll make it up to you.

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Responses to Question Number (2)

2. You have promised to deliver a lecture in class but due to a very bad cold, you

have not been able to even attend the class. What would you say to your professor

the next session you attend the class?

Male (1): I‟m really sorry that I couldn‟t attend the class last week. I came down

with a bad cold. I have the MC here. I‟ll surly deliver it next session.

Male (2): I‟m terribly sorry professor! I‟ve got a bad cold and I couldn‟t do

anything. I would do that in the next session if you don‟t mind.

Male (3): I know I was supposed to bring a lecture for the last session, but I was

hardly sick and couldn‟t attend the class. I hope you believe and forgive me. Please

give me another chance to bring the lecture for the class in the coming sessions.

Male (4): Unfortunately I caught a bad cold and that is why I could not attend the

class. I am so sorry that I was not able to deliver the lecture due to my illness. Please

give me one more chance to deliver the lecture.

Male (5): I had a terrible cold.

Male (6): I‟m really sorry! I was terribly sick. I‟m ready to deliver it now.

Male (7): I feel really sorry for not managing to attend the class! Actually, I did

what I could do to attend the class, However it sounded as though everything was

against me: I could not start my car because the engine was frozen. The public

transportation in our neighborhood was not in service. The phone cabs were not

working and I couldn‟t come on foot as my place is so far away from here.

Male (8): It happened because of family wedding party. I had too much works to do.

Male (9): I apologize, may I present it next time?

Male (10): I apologize! I missed the last session due to a terrible cold. Is there any

chance to present it next session?

Male (11): Please accept my apology.

Male (12): I apologize! Would you please determine next session for my lecture.

Male (13): Sir/madam: this is my MC regarding last session I‟m too sorry but due to

my physical and mental situation had to do my medication.

Male (14): I was terribly sick. Here is my MC as a proof.

Male (15): I‟m extremely sorry about what happened last week. I had a very bad

cold.

Male (16): I had a terrible cold last week. I would be grateful if you would kindly

let me deliver it next session.

Male (17): I‟m terribly sorry Prof for not showing up yesterday. I wasn‟t feeling

well and had to stay in bed all day long. I tried to contact you but I couldn‟t find

your telephone number. Please accept my apologies.

Male (18): So sorry Prof! Due to some unpredictable events I couldn‟t attend the

class. I was horribly sick and I will bring the physician‟s confirmation note.

Male (19): Sorry Prof! I could not make it due to bad cold. I hope you don‟t mind.

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Male (20): Sir, I had a very bad cold last week. That does why I couldn‟t attend the

class. I was wondering if you could give me another chance to deliver my lecture

next week. Please accept my excuse.

Female (1): I don‟t know how to say, I really was in trouble because of the bad cold

and it is very kind of you to let me present next session.

Female (2): I‟m so sorry! I feel awful about it.

Female (3): I‟m really sorry! I was terribly sick and I couldn‟t even leave the room

for 2 days. I‟ve seen a doctor and I have the doctor‟s letter. I‟d really appreciate it if

you would give me another chance to deliver it next time. I have all the presentation

ready.

Female (4): It was not in my hand and I couldn‟t do anything.

Female (5): I am sorry! I had a very bad cold. I will present two topics instead of

one next session.

Female (6): Please accept my apologies. I do my best and promise to deliver a

lecture during this semester.

Female (7): I am really sorry for any inconveniences that I caused for the class

schedule. I had a very bad cold and I could not attend the class. I am sorry again and

I am ready to do deliver it next session if it‟s possible.

Female (8): Oh Prof. I am really sorry to say that I was sick all of the week. Would

you please give me a chance to deliver it next time?

Female (9): Prof., please accept my apology. I had a severe cold and I was not able

to go out of the bed. I promise to make it up.

Female (10): I apologize! Due to some health problems I could not prepare my

lecture and attend the class. I expect you to accept my excuse.

Female (11): I was ready to do my best but I had a very bad cold. May you give me

another opportunity to deliver it next week?

Female (12): Really sorry!

Female (13): I apologize for what happened. It made me embarrassed.

Female (14): I apologize! May I deliver it next time? I can‟t talk because of the bad

cold.

Female (15): I‟m so so sorry! I had a very bad cold .I‟d like to deliver it next time if

you accept.

Female (16): Sorry Prof. /Dr. …… I had a terrible cold and headache. I am ready

to deliver my lecture next week if you want me to do.

Female (17): Sorry to be unorganized but I got a bad cold and couldn‟t really make

it. Is it possible for you to give me a second chance? I‟ll deliver it next week.

Female (18): Excuse me! I had a bad cold and I wasn‟t able to go out. May I ask you

to postpone the date of my lecture? I‟m really sorry! I promise to deliver it next

week.

Female (19): I‟m really sorry that I missed it, but you know I was very sick and I

couldn‟t make it.

Female (20): I‟m sorry that I couldn‟t make it.

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Responses to Question Number (3)

3. The university bus is very crowded so you are standing in the bus. The bus driver

suddenly brakes and you lose your control and step on a fellow student‟s foot. What

would you say?

Male (1): I‟m really sorry!

Male (2): I‟m so sorry! Are you OK?

Male (3): Sorry, it wasn‟t my mistake and I didn‟t do it on purpose.

Male (4): I am sorry! It was my fault but I did not do that on purpose.

Male (5): I would say I am terribly sorry to trample your leg.

Male (6): Oh, excuse me! I really apologize. Is it painful?

Male (7): Oh, excuse me, I didn‟t mean to step on your foot. I really feel awful….

Male (8): sorry!!!

Male (9): I apologize!

Male (10): I am so sorry that I stepped on your foot.

Male (11): Heeeeey driver, take care, are you blind? Sorry!

Male (12): Oh I am sorry!

Male (13): Cheee stupid driver! Sorry!

Male (14): Pardon me!

Male (15): Foolish driver! I‟m sorry!

Male (16): I‟m sorry!

Male (17): Sorry man! Eh? Are you OK?

Male (18: Oops! I‟m so sorry!

Male (19: Damn it! Sorry buddy! Crazy driver…

Male (20): Sorry! Sorry! Are you ok?

Female (1): Excuse me! That was not my fault.

Female (2): It‟s not my fault but forgive me.

Female (3): Oh, I‟m so sorry! Did I hurt you?

Female (4): Sorry!!

Female (5): Sorry. It wasn‟t my fault.

Female (6): Oh, I am so sorry! Did I hurt you? Are you OK?

Female (7): I am really sorry!

Female (8): Oh, sorry!

Female (9): Prof., please accept my apology. I had a severe cold and I was not able

to go out of the bed. I promise to make it up.

Female (10): So sorry dear!

Female (11): OOPS sorry! Hurt you? Sorry again.

Female (12): Oh, I‟m sorry!

Female (13): It was driver‟s fault.

Female (14): Excuse me!

Female (15: Oh sorry! It was n‟t my fault. I hope I did n‟t hurt you.

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Female (16): I‟m really sorry! I lost my control and it was not intentionally, Are you

Ok? Really sorry, it wasn‟t my fault indeed but sorry again.

Female (17): Sorry!

Female (18): Sorry! Excuse me!

Female (19): Sorry! Did it hurt?

Female (2o): I apologize!

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Responses to Question Number (4)

4. You have promised one of the university staff to fill in and return a form two days

ago but you have a two day delay. What would you say when you want to return the

form?

Male (1): I‟m sorry it took that long. Do you still accept it?

Male (2): I was very busy during last week, so I‟m sorry, I do apologize.

Male (3): Sorry, I know I had to bring it back 2 days ago. As I was too busy I

completely forgot about it.

Male (4): I apologize for not being able to submit the form on time.

Male (5): I am profusely sorry, I had a hectic week and I could n‟t tackle.

Male (6): Excuse me; something happened to me that I could not return this form on

time.

Male (7): I Apologize! Due to an emergency I had to be away from university for a

couple of days. That‟s why I failed to return the forms by Tuesday.

Male (8): It caused by too much works then I have forgotten to fill that up. I‟m sorry

and I do apologize.

Male (9): I‟m sorry! Let me tell you the truth.

Male (10): It is embarrassing that I could not be able to hand in the form on time

and I want you to accept my apology.

Male (11): Sorry that I delayed for returning it. I was really busy with my

assignments.

Male (12): I apologize! I was really busy.

Male (13): Sorry! I come from Johor Baru then I was delayed.

Male (14): I apologize! I went on vacation for few days.

Male (15): I‟m late as I was so busy.

Male (16): I put off filling the form and that‟s why it‟s late.

Male (17): I do apologize for the delay. The last two days were quite hectic as I was

preparing for a test.

Male (18): I‟m ashamed for such a long delay Sir.

Male (19): I was very busy…. Sorry for that…..Hope I‟m not too late!

Male (20): Sorry! I couldn‟t make it to bring the form two days ago since I had a

terrible accident.

Female (1): I am sorry for my delay. You know, these days I am so busy with my

exams.

Female (2): I am so sorry, I had a personal problem. I will make it up tomorrow

Insha‟Allah.

Female (3): I‟m sorry for the delay. I couldn‟t make it any sooner because of a

problem. I hope I haven‟t made any inconvenience.

Female (4): I‟m busy these days too much. I really forgot to complete it. It will not

happen again. I‟m really sorry.

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Female (5): I am so sorry I had some problems which made me return this form late.

Female (6): I am a very busy person. I hope you accept my apologies.

Female (7): I am really sorry that I could not make it on time.

Female (8): I know it has two days delay and it‟s my fault. May I submit it now?

Female (9): Sorry for my delay!

Female (10): I am really sorry that I was not able to bring it sooner because of my

health problem.

Female (11): I beg your pardon for being late. I had to go outside.

Female (12): I‟m sorry but I had some personal problems.

Female (13): I am so sorry for being late!

Female (14): Excuse me, I should have filled it up two days ago, but I forgot.

Female (15): I „m so so sorry! As I had a cold, it was really impossible to bring it

two days ago.

Female (16): Hi Mr. /Miss …. I‟m really sorry! I forgot totally the exact date of

submitting the forms. Is it ok to give it to you now?

Female (17): Sorry, I was busy and forgot to give it back on time.

Female (18): Sorry for delay, I was in trouble. Hope you accept my excuse.

Female (19): You are right to be mad at me, I‟m sorry for delay! I had a personal

problem.

Female (20): there was a reason for the delay.

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Responses to Question Number (5)

5. You have promised your younger sister/brother to take her/him to the cinema and

you have forgotten to do so. She/he has been waiting for you at home for hours, what

would you say to her/him as you get home?

Male (1): I‟m so sorry! I got stuck in traffic. I‟ll take u to the movies at the end of

this week, I promise.

Male (2): Oh I forgot. Sorry for being late! We can watch another film at home

tonight and we‟ll go during next week.

Male (3): I am truly sorry! I was stuck in the jam for hours, so I couldn‟t get here

any sooner.

Male (4): Please forgive me for forgetting to take you to the cinema. I would

promise to make it up to you next week.

Male (5): I totally forgot the case. Tomorrow I will take you to another

entertainment center

Male (6): I apologize dear! I got in trouble today. Let‟s go somewhere else that you

like more now.

Male (7): So sorry my dear! I was stuck in traffic jam. How would you like me to

make up?

Male (8): I usually forget many stuffs .I promise to take you to the cinema in near

future. Here is an ice cream for you and Let me kiss and hug you honey.

Male (9): I‟m sorry. Let‟s go to the cinema another day.

Male (10): I‟ sorry! We will go to the cinema tomorrow.

Male (11): I`m really sorry honey! I tried a lot to come back home on time, but I

couldn`t. I`ll take you tomorrow, believe me please.

Male (12): I apologize! I will take you somewhere else. It will not happen again.

Male (13): Sorry (kiss), we will go tomorrow, promise promise promise.

Male (14): I am sorry! Let me tell the truth. Promise to take you to the cinema next

time.

Male (15): I apologize! I‟ll make it up as soon as possible.

Male (16): I take you to the cinema even though it‟s late.

Male (17): I‟m so sorry! I really forgot. It was very inconsiderate of me. Shall we go

now or some other time?

Male (18): Sorry babe! I am an idiot and absent-minded.

Male (19): Shit! I totally forgot. Do you accept my apologies? What if I get you a

damn nice gift?

Male (20): Oh darling, I forgot to come. Let‟s go to cinema now. I want to treat you

a nice dinner.

Female (1): I am so shy for that. I promise not to do it again. Instead, I will take you

a better place.

Female (2): I am so sorry!

118

Female (3): I totally forgot about today! I‟m really, really sorry! Why didn‟t you call

me to remind me? You know how forgetful I am! What can I do to make it up to

you? Let‟s see if we can catch the last session!

Female (4): I was busy too much. You should have reminded me. I will postpone

my other plans and take you to the cinema.

Female (5): I am so sorry sweetheart! I was so busy that I even forgot about that.

Promise I‟ll take you out next weakened Insha‟Allah.

Female (6): I am so sorry! I know you are right to be angry and disappointed. How

can I make it up to you?

Female (7): I am sorry honey! I am so busy these days that I forgot my promises.

Now if you have forgiven me let‟s go out and have fun!

Female (8): Oh dear, I was too busy today. We can make it for another time.

Female (9): I‟m so sorry sweet heart! I totally forgot. Never happens again.

Female (10): I love u babe! Maybe we can have another program on weekend and

spend the whole day together.

Female (11): I'm so sorry sweety. I was so busy and forgot. Tomorrow ok?

Female (12): So sorry! Now we can go to the cinema as well as dinner.

Female (13): I am so sorry! Let‟s go next time.

Female (14): I‟ll take you there tomorrow dear.

Female (15): Excuse me dear! I had a lot of work and I forgot it. Why you didn‟t

remind me? We will go there tomorrow Insha‟Allah.

Female (16): Hi darling (hug & kiss him/her), I am so sorry! I was really busy and

forgot we were supposed to go to the movies. Tomorrow I can take you to the park

instead …what‟s your idea?

Female (17): I‟m so so sorry honey! I totally forgot about it. What about tomorrow?

What should I do to compensate my mistake?

Female (18): I‟m really sorry my sweetheart! How can I compensate it?

Female (19): I completely forgot. Sorry honey! I promise that we will go by next

week. I will buy everything for you as a penalty.

Female (20): I‟m really ashamed. Please forgive me! I promise to compensate it to

you.

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Responses to Question Number (6)

6. You have been supposed to meet your close friend at the university library to

exchange some books and you get there an hour later and find your friend still

waiting for you at the library. What would you say to your friend as you see her?

Male (1): I‟m terribly sorry! I mustn‟t have forgotten about it. It was very stupid of

me, and I‟m very sorry again.

Male (2): Excuse me buddy, I‟m late. I overslept. Thanks for waiting.

Male (3): I am really sorry! I know I am late and I hope you accept my apology.

Male (4): I am so sorry that I could not come on time and please accept my

apologies.

Male (5): I really appreciate you as a person that I can always count on. It means a

lot to me.

Male (6): I apologize, there was a heavy traffic.

Male (7): I am so sorry and annoyed my darling for keeping you waiting here! I

should have been here much earlier. I have been through a hectic schedule today.

Let‟s kiss and I promise it won‟t happen again.

Male (8): I smile.

Male (9): I am sorry!

Male (10): It is really sweet of you waiting for me and I want to make it up by

buying something for you.

Male (11): Sorry for my delay, I was in the traffic.

Male (12): I apologize, there was a heavy traffic.

Male (13): I love you… so sorry!

Male (14): I apologize! Let me tell you why I‟m late.

Male (15): I was stuck in traffic jam.

Male (16): I‟m sorry for being late!

Male (17): Sorry for keeping you wait!

Male (18): I‟m down in the mouth buddy!

Male (19): I know how upset you are but I hope you excuse me.

Male (20): I‟m sorry! I got stuck in traffic.

Female (1): I am sorry friend! It wasn‟t my fault, sometimes everything is organized

to make you late.

Female (2): I am so sorry! God knows this wasn‟t my fault.

Female (3): I‟m really sorry honey! I got stuck in traffic. I tried to call you but I

couldn‟t reach you. Are you bored? Let‟s go have a drink! My treat!

Female (4): I‟m so sorry! I really forgot our appointment.

Female (5): Sorry for being late! It will never happen again.

Female (6): Let‟s go and have a drink first to make it up to you. Hope you forgive

me as it wasn‟t my fault. So sorry!

Female (7): I am terribly sorry! What about a cup of coffee in the lib Buffett?

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Female (8): I am really sorry! There was a very heavy traffic.

Female (9): I‟m sorry for my delay! You are right to be angry.

Female (10): I am really embarrassed to make you wait for me for a long time.

Female (11): There was a heavy traffic and I couldn't call you.

Female (12): Something happened and I got here late.

Female (13): I‟m so sorry buddy!

Female (14): I don‟t deserve such a nice friend like you.

Female (15): Pardon me dear! I was stuck in traffic. Let‟s drink something on me.

Female (16): Sorry for my delay! It was my fault. Hope you are not sad ..love you

Female (17): I‟m so sorry to keep you wait dear.

Female (18): Oh dear so sorry! I can‟t stop feeling sorry.

Female (19): Are you angry? Sorry but I had a kind of problem and you know I‟m

always on time, sorry again.

Female (20): So sorry!

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Responses to Question Number (7)

7. As you are talking to one of the university staff, you accidentally spill the cup of

tea on his/her desk. What would you say?

Male (1): Oh, I‟m so sorry! Let me help you. Have u got a piece of tissue?

Male (2): I‟ll clean the desk for you.

Male (3): I am extremely sorry, let me clean your desk and all the mess I made.

Male (4): I apologize for spilling the tea on your desk. Please forgive me.

Male (5): Let me clean it.

Male (6): I apologize! I clean it right now for you.

Male (7): I‟m really sorry! I really didn‟t see the cup on your desk.

Male (8): So sorry!!!!!! I didn‟t mean it. Please let me help you to clean it up, sorry

sorry sorry!

Male (9): I‟m so sorry! Let me clean it.

Male (10): I should have been more careful. I clean up the mess. I beg your pardon.

Male (11): Ooooooh, sorry, sorry, sorry, let me clean it. Excuse me! I didn`t see it.

Male (12): I am really sorry! I clean it now.

Male (13): Sorry! Sorry!

Male (14): I am so sorry! I do apologize.

Male (15): Oh! I clean it now.

Male (16): I‟m so sorry for that!

Male (17): I‟m terribly sorry! I‟ll get something to dry it off.

Male (18): So sorry Sir! I ruined your shirt.

Male (19): I‟m damn sorry! I‟m terribly sorry for that man!

Male (20): I‟m so sorry Sir! Let me make it clean.

Female (1): Oh no! What happened? I am so sorry! I didn‟t mean that. Sorry!

Female (2): I am so sorry! I didn‟t want to do it, let me clean it.

Female (3): I‟m so sorry! Let me clean the desk! I‟m really sorry! Your book had

blocked the cup! I couldn‟t see it was there!

Female (4): I‟m sorry!

Female (5): I am so sorry! I didn‟t mean that. Let me help you cleaning this mess.

Female (6): Oh, I am terribly sorry! It‟s really embarrassing.

Female (7): Oh I‟m sorry! I am really sorry! Is everything ok? Did I damage your

papers? I do apologize.

Female (8): Oh I‟m really sorry! Let me help you to clean it up.

Female (9): I‟m so sorry! Let me help you to clean it here.

Female (10): I am really sorry! Really sorry sir/ madam!

Female (11): I'm so sorry! I will clean it now.

Female (12): I‟m sorry! I‟m so sorry! Let me clean it myself.

Female (13): I do apologize!

Female (14): Excuse me! Let me clean it.

122

Female (15): I‟m terribly sorry! It was my fault. I hope I didn‟t hurt you seriously.

Female (16): I am really really sorry! please let me help you clean the desk/table….

So sorry again! Please accept my apology. I didn‟t notice the cup was there at

all…Sorry

Female (17): Oh sorry!

Female (18): I‟m really sorry! Excuse me!

Female (19): Sorry! Sorry! I beg your pardon. I will fix it. Let me clean your desk.

I‟m sorry!

Female (20): I apologize!

123

Responses to Question Number (8)

8. You were expected by your supervisor to discuss some of your problems but due

to a heavy traffic, you are 45 minutes late. What would you say to your supervisor as

you see him/her?

Male (1): I‟m really sorry! There was a heavy traffic jam and although I left home

on time I ended up late.

Male (2): I‟m really sorry professor! I was stuck in heavy traffic for more than one

hour. It won‟t happen again.

Male (3): Sorry professor! I didn‟t assume there would be a heavy traffic today,

that‟s why I‟m late. I promise to be on time after this.

Male (4): I am sorry that I could not come on time due to the traffic jam. I promise it

will not happen again.

Male (5): I would try not to enter the class and skip it.

Male (6): Really sorry Prof!

Male (7): I am truly sorry for being late! I should have at least notified you of it.

You know, my cell phone was out of credit.

Male (8): I‟m really sorry about it! It was my fault.

Male (9): I am so sorry! I was stuck in a traffic jam.

Male (10): I wish I could come on time but due to the traffic jam I could not, so

please accept my apology sir.

Male (11): Please accept my apology for not being a good and on time student. I was

in traffic.

Male (12): I apologize! It will not happen again.

Male (13): Here is KL; you are the victim of being late when it rains. Sorry sir!

Male (14): I am sorry for being late! I was stuck in the heavy traffic jam.

Male (15): I apologize! I promise not to let it happen again.

Male (16): I got stuck in the traffic.

Male (17): Sorry for being late! I got stuck in traffic jam.

Male (18): I‟m totally shameful. I just got stuck in traffic.

Male (19): I‟m so sorry! I really was stuck in a bad situation.

Male (20): Dear supervisor, I‟m really sorry for the delay! I was stuck in a heavy

traffic.

Female (1): I am so sorry! I was stuck in a very heavy traffic.

Female (2): I blame myself, please forgive me.

Female (3): I‟m really sorry Prof/Dr. It was jammed everywhere. I was even stuck

in the jam on campus for 20 minutes! I hope you haven‟t missed any of your plans

because of this.

Female (4): Sorry Dr.! I tried to come sooner but traffic was really heavy and I

couldn‟t do anything.

124

Female (5): I am so sorry sir! The traffic was so heavy. It‟s my fault; I was supposed

to leave earlier.

Female (6): I am terribly sorry! I was stuck in traffic and there was no way I could

get out of it and arrive earlier. Please forgive me!

Female (7): I am really sorry! I tried to contact you but I couldn‟t. I m really sorry!

It will not happen again.

Female (8): Oh, Prof. I know I am late, but there was a heavy traffic.

Female (9): I‟m sorry Prof. for my delay! It was a terrible jam. Sorry to make you

waiting.

Female (10): Please pardon me. It was completely out of my control you know the

rush hours.

Female (11): I really apologize for being late. There was a heavy traffic.

Female (12): I‟m sorry but it is the fault of the traffic. Sorry!

Female (13): I‟m terribly sorry!

Female (14): Excuse me! It‟s my fault. It will not happen again.

Female (15): I‟m really sorry! There was a heavy traffic. It will not happen in future.

Female (16): Hello Prof./Dr….., I‟m sorry for being late! I always try to be on time

but today I was stock in a very heavy jam …I‟m sorry again!

Female (17): I‟m really sorry! There was a heavy traffic. I was stuck there.

Female (18): Sorry! I was stuck in traffic. I hope I didn‟t waste your time. I promise

this is the last time.

Female (19): Excuse me! I was stuck in heavy traffic jam.

Female (20): I will tell the truth of traffic and try to impress her by my extra work.

125

Responses to Question Number (9)

9. As you are carrying a chair in the lobby of the university, you hurt a fellow

student‟s hand accidentally. What would you say?

Male (1): I‟m so sorry! Are you ok? Do you want me to take you to the doctor?

Male (2): I apologize! Is your hand ok now?

Male (3): I am deeply sorry! I wasn‟t careful while moving the chair. I didn‟t notice

the chair would hit you.

Male (4): I am sorry! It was thoughtless of me to carry the chair in the lobby and I

should not have done that.

Male (5): I am profusely sorry! What can I do for you to relieve your pain?

Male (6): Excuse me! I did not see you, Are you ok?

Male (7): Please forgive me! I am sorry! I did not see you. It badly hurts, doesn‟t it?

Male (8): OPSSSS…so sorry buddy! Can I do something for you?!!!

Male (9): Please forgive me! I did not see you. I‟m so sorry.

Male (10): I did not see you. I am so sorry!

Male (11): Sorry! Let me see what happen to your hand, let me see.

Male (12): I apologize! Do you feel ache?

Male (13): Watch out!

Male (14): I do apologize!

Male (15): Let me rub your hand to relieve pain.

Male (16): how can I help if you‟re hurt?

Male (17): I‟m so sorry! Are you alright? Do you need anything? Shall I take you to

hospital?

Male (18): I am sorry!

Male (19): Sorry man! I hope it didn‟t hurt much.

Male (20): Oh sorry!

Female (1): Excuse me! Are you okay? I should be more careful. I am sorry again!

If you feel pain, I can take you to the hospital.

Female (2): I am sorry! Do you need any help?

Female (3): Oops! I‟m so sorry! Are you hurt? I‟m really sorry!

Female (4): Oops, sorry! Sorry!

Female (5): I am so sorry! I didn‟t mean that. Are you ok?

Female (6): I am terribly sorry! Did I hurt you badly? Let me see if it is ok.

Female (7): I do apologies! Sorry! Sorry! Sorry!

Female (8): Oh sorry! I‟m really sorry!

Female (9): Oh I‟m sorry! Are you ok?

Female (10): I‟m sorry! I did n‟t do it intentionally.

Female (11): Oh, really sorry! Did I hurt you?

Female (12): Excuse me!

Female (13): Sorry!

126

Female (14): I apologize! I‟m really ashamed. Are you ok?

Female (15): I‟m terribly sorry! It was my fault. I hope I did n‟t hurt you seriously.

Female (16): I am so so sorry! It was my fault and I had to be more cautious. Hope

you haven‟t hurt badly, any help? Are you ok? Please forgive me dear, do you want

me to do anything for you?

Female (17): Oh, sorry!

Female (18): Excuse me! Sorry!

Female (19): Oh sorry! Did it hurt? Let me see. Sorry again!

Female (20): Sorry! Sorry! Let me help you relieve the pain.

127

Responses to Question Number (10)

10. You have promised your younger sister/ brother to buy her/him a book

from the bookstore but you have forgotten. What would you say to her/him?

Male (1): I‟m sorry! I couldn‟t get the book today but I will get it tomorrow, ok?

Male (2): I really forgot that. I promise I will buy you tomorrow.

Male (3): Sorry! I didn‟t have time today to buy the book I promised you before, but

I will buy it for you as soon as possible.

Male (4): I apologize for forgetting to buy the book. I promise I will buy an extra

book for you tomorrow.

Male (5): I feel embarrassed.

Male (6): Excuse me! I totally forgot. I go and buy it now.

Male (7): Excuse me, honey!!! I hope I did not upset you…I have become so

forgetful lately. Can I buy it tomorrow on my way back home?

Male (8): I‟m so sorry, I just forgot to buy that for you darling, shall we go out and

buy it together now darling?

Male (9): Today I have forgotten but take it easy, tomorrow I will certainly buy it

for you.

Male (10): I am so sorry that I forgot to buy a book for you. I promise I will buy it

for you tomorrow.

Male (11): I`m really sorry man, I forgot it. I`ll bring it for you tomorrow. Please

remind me tomorrow, I‟m busy nowadays.

Male (12): I apologize! I promise to buy it tomorrow.

Male (13): The book shop didn‟t have the book. Tomorrow I will try another shop.

Male (14): Darling, I am sorry! I forgot to buy the book for you.

Male (15): I could n‟t find it.

Male (16): I go back to the bookstore to get it my dear!

Male (17): Sorry! I was very busy today and forgot to buy the book. I‟ll certainly

buy it tomorrow, I promise.

Male (18): Sorry babe! I‟m such an idiot and absent minded.

Male (19): Oh damn it! I am so sorry! What can I do to make you happy?

Male (20): Sorry! I promise to buy a very nice one for you tomorrow.

Female (1): Sorry, I am so forgetful these days. If it is not late still let‟s go now.

Female (2): I am sorry! I was so busy but I will compensate it to you.

Female (3): Oops! I forgot to get you the book! I‟m sorry, I‟ll get it tomorrow. Can

you send me a massage and remind me while I‟m out? But if you need it today, we

can go out now and get it for you. We‟ll have a snack on the way back!

Female (4): Sorry I forgot, I will go and buy it for you right now.

Female (5): I am sorry darling! I totally forgot. Let me buy you two books instead.

Female (6): I am so sorry my dear! I was really occupied and I forgot about the

book, let‟s go and buy one now, how is that?

128

Female (7): Oh I am really sorry! I totally forgot to buy the book, but if you want it

now we can go together and buy it.

Female (8): Oh dear we can go to the bookstore the other day and you can buy

whatever you need.

Female (9): Sorry dear I forgot to get it. I‟ll buy it tomorrow. Ok?

Female (10): don‟t worry darling I promise to buy it for you tomorrow morning.

Female (11): Sorry honey, I forgot. I was so busy. Tomorrow I will buy.

Female (12): Sorry! I buy it tomorrow, one day makes no difference.

Female (13): I‟m so sorry dear!

Female (14): Excuse me, I forgot to but it. If you need it, I go and buy it now.

Female (15): It was not my fault honey, the book store was closed. I‟ll buy it

tomorrow ok?

Female (16): Hi lovely … I forgot to buy the book, but now we can go together and

buy the book you want. Sorry my dear!

Female (17): Sorry dear! I will go now and buy it for you dear.

Female (18): Oh sorry my dear! I will buy it as soon as possible.

Female (19): Sorry honey! I have forgotten to buy you the book. I will buy it

tomorrow.

Female (20): I will go back and buy it.

129

APPENDIX C: STATISTICAL ANALYSES AND SIGNIFICANT VALUES

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Gender * IFDI1 400 100.0% 0 .0% 400 100.0%

Gender * IFDI2 400 100.0% 0 .0% 400 100.0%

Gender * IFDI3 400 100.0% 0 .0% 400 100.0%

Gender * IFDI4 400 100.0% 0 .0% 400 100.0%

Gender * IFDI5 400 100.0% 0 .0% 400 100.0%

Gender * IFDI6 400 100.0% 0 .0% 400 100.0%

Gender * AP1 400 100.0% 0 .0% 400 100.0%

Gender * AP2 400 100.0% 0 .0% 400 100.0%

Gender * AP3 400 100.0% 0 .0% 400 100.0%

Gender * AP4 400 100.0% 0 .0% 400 100.0%

Gender * AP5 400 100.0% 0 .0% 400 100.0%

Gender * AP6 400 100.0% 0 .0% 400 100.0%

Gender * AP7 400 100.0% 0 .0% 400 100.0%

Gender * AP8 400 100.0% 0 .0% 400 100.0%

Gender * AP9 400 100.0% 0 .0% 400 100.0%

Gender * AP10 400 100.0% 0 .0% 400 100.0%

Gender * AP11 400 100.0% 0 .0% 400 100.0%

Gender * AP12 400 100.0% 0 .0% 400 100.0%

Gender * AP13 400 100.0% 0 .0% 400 100.0%

Gender * AP14 400 100.0% 0 .0% 400 100.0%

Gender * AP15 400 100.0% 0 .0% 400 100.0%

Gender * AP16 400 100.0% 0 .0% 400 100.0%

Gender * AP17 400 100.0% 0 .0% 400 100.0%

Gender * AP18 400 100.0% 0 .0% 400 100.0%

Gender * AP19 400 100.0% 0 .0% 400 100.0%

Gender * NAP1 400 100.0% 0 .0% 400 100.0%

Gender * NAP2 400 100.0% 0 .0% 400 100.0%

Gender * NAP3 400 100.0% 0 .0% 400 100.0%

Gender * NAP4 400 100.0% 0 .0% 400 100.0%

Gender * NAP5 400 100.0% 0 .0% 400 100.0%

130

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Gender * IFDI1 400 100.0% 0 .0% 400 100.0%

Gender * IFDI2 400 100.0% 0 .0% 400 100.0%

Gender * IFDI3 400 100.0% 0 .0% 400 100.0%

Gender * IFDI4 400 100.0% 0 .0% 400 100.0%

Gender * IFDI5 400 100.0% 0 .0% 400 100.0%

Gender * IFDI6 400 100.0% 0 .0% 400 100.0%

Gender * AP1 400 100.0% 0 .0% 400 100.0%

Gender * AP2 400 100.0% 0 .0% 400 100.0%

Gender * AP3 400 100.0% 0 .0% 400 100.0%

Gender * AP4 400 100.0% 0 .0% 400 100.0%

Gender * AP5 400 100.0% 0 .0% 400 100.0%

Gender * AP6 400 100.0% 0 .0% 400 100.0%

Gender * AP7 400 100.0% 0 .0% 400 100.0%

Gender * AP8 400 100.0% 0 .0% 400 100.0%

Gender * AP9 400 100.0% 0 .0% 400 100.0%

Gender * AP10 400 100.0% 0 .0% 400 100.0%

Gender * AP11 400 100.0% 0 .0% 400 100.0%

Gender * AP12 400 100.0% 0 .0% 400 100.0%

Gender * AP13 400 100.0% 0 .0% 400 100.0%

Gender * AP14 400 100.0% 0 .0% 400 100.0%

Gender * AP15 400 100.0% 0 .0% 400 100.0%

Gender * AP16 400 100.0% 0 .0% 400 100.0%

Gender * AP17 400 100.0% 0 .0% 400 100.0%

Gender * AP18 400 100.0% 0 .0% 400 100.0%

Gender * AP19 400 100.0% 0 .0% 400 100.0%

Gender * NAP1 400 100.0% 0 .0% 400 100.0%

Gender * NAP2 400 100.0% 0 .0% 400 100.0%

Gender * NAP3 400 100.0% 0 .0% 400 100.0%

Gender * NAP4 400 100.0% 0 .0% 400 100.0%

Gender * NAP5 400 100.0% 0 .0% 400 100.0%

Gender * NAP6 400 100.0% 0 .0% 400 100.0%

131

Gender * IFDI1

Crosstab

IFDI1

Not Used Used Total

Gender Male Count 144 56 200

% within Gender 72.0% 28.0% 100.0%

% within IFDI1 54.3% 41.5% 50.0%

% of Total 36.0% 14.0% 50.0%

Female Count 121 79 200

% within Gender 60.5% 39.5% 100.0%

% within IFDI1 45.7% 58.5% 50.0%

% of Total 30.3% 19.8% 50.0%

Total Count 265 135 400

% within Gender 66.3% 33.8% 100.0%

% within IFDI1 100.0% 100.0% 100.0%

% of Total 66.3% 33.8% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 5.915a 1 .015

Continuity Correctionb 5.412 1 .020

Likelihood Ratio 5.936 1 .015

Fisher's Exact Test .020 .010

Linear-by-Linear

Association

5.900 1 .015

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 67.50.

b. Computed only for a 2x2 table

132

Gender * IFDI2

Crosstab

IFDI2

Not Used Used Total

Gender Male Count 142 58 200

% within Gender 71.0% 29.0% 100.0%

% within IFDI2 55.3% 40.6% 50.0%

% of Total 35.5% 14.5% 50.0%

Female Count 115 85 200

% within Gender 57.5% 42.5% 100.0%

% within IFDI2 44.7% 59.4% 50.0%

% of Total 28.7% 21.3% 50.0%

Total Count 257 143 400

% within Gender 64.3% 35.8% 100.0%

% within IFDI2 100.0% 100.0% 100.0%

% of Total 64.3% 35.8% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 7.934a 1 .005

Continuity Correctionb 7.358 1 .007

Likelihood Ratio 7.970 1 .005

Fisher's Exact Test .007 .003

Linear-by-Linear

Association

7.915 1 .005

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 71.50.

b. Computed only for a 2x2 table

133

Gender * IFDI3

Crosstab

IFDI3

Not Used Used Total

Gender Male Count 199 1 200

% within Gender 99.5% .5% 100.0%

% within IFDI3 50.8% 12.5% 50.0%

% of Total 49.8% .3% 50.0%

Female Count 193 7 200

% within Gender 96.5% 3.5% 100.0%

% within IFDI3 49.2% 87.5% 50.0%

% of Total 48.3% 1.8% 50.0%

Total Count 392 8 400

% within Gender 98.0% 2.0% 100.0%

% within IFDI3 100.0% 100.0% 100.0%

% of Total 98.0% 2.0% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 4.592a 1 .032

Continuity Correctionb 3.189 1 .074

Likelihood Ratio 5.154 1 .023

Fisher's Exact Test .068 .034

Linear-by-Linear

Association

4.580 1 .032

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 4.00.

b. Computed only for a 2x2 table

134

Gender * IFDI4

Crosstab

IFDI4

Not Used Used Total

Gender Male Count 200 0 200

% within Gender 100.0% .0% 100.0%

% within IFDI4 50.1% .0% 50.0%

% of Total 50.0% .0% 50.0%

Female Count 199 1 200

% within Gender 99.5% .5% 100.0%

% within IFDI4 49.9% 100.0% 50.0%

% of Total 49.8% .3% 50.0%

Total Count 399 1 400

% within Gender 99.8% .3% 100.0%

% within IFDI4 100.0% 100.0% 100.0%

% of Total 99.8% .3% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.003a 1 .317

Continuity Correctionb .000 1 1.000

Likelihood Ratio 1.389 1 .239

Fisher's Exact Test 1.000 .500

Linear-by-Linear

Association

1.000 1 .317

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is .50.

b. Computed only for a 2x2 table

135

Gender * IFDI5

Crosstab

IFDI5

Not Used Used Total

Gender Male Count 162 38 200

% within Gender 81.0% 19.0% 100.0%

% within IFDI5 46.7% 71.7% 50.0%

% of Total 40.5% 9.5% 50.0%

Female Count 185 15 200

% within Gender 92.5% 7.5% 100.0%

% within IFDI5 53.3% 28.3% 50.0%

% of Total 46.3% 3.8% 50.0%

Total Count 347 53 400

% within Gender 86.8% 13.3% 100.0%

% within IFDI5 100.0% 100.0% 100.0%

% of Total 86.8% 13.3% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 11.506a 1 .001

Continuity Correctionb 10.527 1 .001

Likelihood Ratio 11.846 1 .001

Fisher's Exact Test .001 .001

Linear-by-Linear

Association

11.477 1 .001

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 26.50.

b. Computed only for a 2x2 table

136

Gender * IFDI6

Crosstab

IFDI6

Not Used Used Total

Gender Male Count 184 16 200

% within Gender 92.0% 8.0% 100.0%

% within IFDI6 51.3% 39.0% 50.0%

% of Total 46.0% 4.0% 50.0%

Female Count 175 25 200

% within Gender 87.5% 12.5% 100.0%

% within IFDI6 48.7% 61.0% 50.0%

% of Total 43.8% 6.3% 50.0%

Total Count 359 41 400

% within Gender 89.8% 10.3% 100.0%

% within IFDI6 100.0% 100.0% 100.0%

% of Total 89.8% 10.3% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 2.201a 1 .138

Continuity Correctionb 1.739 1 .187

Likelihood Ratio 2.217 1 .136

Fisher's Exact Test .187 .093

Linear-by-Linear

Association

2.196 1 .138

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 20.50.

b. Computed only for a 2x2 table

137

Gender * AP1

Crosstab

AP1

Not Used Used Total

Gender Male Count 122 78 200

% within Gender 61.0% 39.0% 100.0%

% within AP1 48.4% 52.7% 50.0%

% of Total 30.5% 19.5% 50.0%

Female Count 130 70 200

% within Gender 65.0% 35.0% 100.0%

% within AP1 51.6% 47.3% 50.0%

% of Total 32.5% 17.5% 50.0%

Total Count 252 148 400

% within Gender 63.0% 37.0% 100.0%

% within AP1 100.0% 100.0% 100.0%

% of Total 63.0% 37.0% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square .686a 1 .407

Continuity Correctionb .526 1 .468

Likelihood Ratio .687 1 .407

Fisher's Exact Test .469 .234

Linear-by-Linear

Association

.685 1 .408

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 74.00.

b. Computed only for a 2x2 table

138

Gender * AP2

Crosstab

AP2

Not Used Used Total

Gender Male Count 174 26 200

% within Gender 87.0% 13.0% 100.0%

% within AP2 49.0% 57.8% 50.0%

% of Total 43.5% 6.5% 50.0%

Female Count 181 19 200

% within Gender 90.5% 9.5% 100.0%

% within AP2 51.0% 42.2% 50.0%

% of Total 45.3% 4.8% 50.0%

Total Count 355 45 400

% within Gender 88.8% 11.3% 100.0%

% within AP2 100.0% 100.0% 100.0%

% of Total 88.8% 11.3% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.227a 1 .268

Continuity Correctionb .901 1 .342

Likelihood Ratio 1.231 1 .267

Fisher's Exact Test .342 .171

Linear-by-Linear

Association

1.224 1 .269

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 22.50.

b. Computed only for a 2x2 table

139

Gender * AP3

Crosstab

AP3

Not Used Used Total

Gender Male Count 176 24 200

% within Gender 88.0% 12.0% 100.0%

% within AP3 51.0% 43.6% 50.0%

% of Total 44.0% 6.0% 50.0%

Female Count 169 31 200

% within Gender 84.5% 15.5% 100.0%

% within AP3 49.0% 56.4% 50.0%

% of Total 42.3% 7.8% 50.0%

Total Count 345 55 400

% within Gender 86.3% 13.8% 100.0%

% within AP3 100.0% 100.0% 100.0%

% of Total 86.3% 13.8% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.033a 1 .309

Continuity Correctionb .759 1 .384

Likelihood Ratio 1.035 1 .309

Fisher's Exact Test .384 .192

Linear-by-Linear

Association

1.030 1 .310

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 27.50.

b. Computed only for a 2x2 table

140

Gender * AP4

Crosstab

AP4

Not Used Used Total

Gender Male Count 179 21 200

% within Gender 89.5% 10.5% 100.0%

% within AP4 51.0% 42.9% 50.0%

% of Total 44.8% 5.3% 50.0%

Female Count 172 28 200

% within Gender 86.0% 14.0% 100.0%

% within AP4 49.0% 57.1% 50.0%

% of Total 43.0% 7.0% 50.0%

Total Count 351 49 400

% within Gender 87.8% 12.3% 100.0%

% within AP4 100.0% 100.0% 100.0%

% of Total 87.8% 12.3% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.140a 1 .286

Continuity Correctionb .837 1 .360

Likelihood Ratio 1.143 1 .285

Fisher's Exact Test .360 .180

Linear-by-Linear

Association

1.137 1 .286

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 24.50.

b. Computed only for a 2x2 table

141

Gender * AP5

Crosstab

AP5

Not Used Used Total

Gender Male Count 180 20 200

% within Gender 90.0% 10.0% 100.0%

% within AP5 49.7% 52.6% 50.0%

% of Total 45.0% 5.0% 50.0%

Female Count 182 18 200

% within Gender 91.0% 9.0% 100.0%

% within AP5 50.3% 47.4% 50.0%

% of Total 45.5% 4.5% 50.0%

Total Count 362 38 400

% within Gender 90.5% 9.5% 100.0%

% within AP5 100.0% 100.0% 100.0%

% of Total 90.5% 9.5% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square .116a 1 .733

Continuity Correctionb .029 1 .865

Likelihood Ratio .116 1 .733

Fisher's Exact Test .737 .432

Linear-by-Linear

Association

.116 1 .733

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 19.00.

b. Computed only for a 2x2 table

142

Gender * AP6

Crosstab

AP6

Not Used Used Total

Gender Male Count 183 17 200

% within Gender 91.5% 8.5% 100.0%

% within AP6 50.8% 42.5% 50.0%

% of Total 45.8% 4.3% 50.0%

Female Count 177 23 200

% within Gender 88.5% 11.5% 100.0%

% within AP6 49.2% 57.5% 50.0%

% of Total 44.3% 5.8% 50.0%

Total Count 360 40 400

% within Gender 90.0% 10.0% 100.0%

% within AP6 100.0% 100.0% 100.0%

% of Total 90.0% 10.0% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.000a 1 .317

Continuity Correctionb .694 1 .405

Likelihood Ratio 1.003 1 .316

Fisher's Exact Test .405 .202

Linear-by-Linear

Association

.997 1 .318

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 20.00.

b. Computed only for a 2x2 table

143

Gender * AP7

Crosstab

AP7

Not Used Used Total

Gender Male Count 184 16 200

% within Gender 92.0% 8.0% 100.0%

% within AP7 48.8% 69.6% 50.0%

% of Total 46.0% 4.0% 50.0%

Female Count 193 7 200

% within Gender 96.5% 3.5% 100.0%

% within AP7 51.2% 30.4% 50.0%

% of Total 48.3% 1.8% 50.0%

Total Count 377 23 400

% within Gender 94.3% 5.8% 100.0%

% within AP7 100.0% 100.0% 100.0%

% of Total 94.3% 5.8% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 3.737a 1 .053

Continuity Correctionb 2.952 1 .086

Likelihood Ratio 3.832 1 .050

Fisher's Exact Test .084 .042

Linear-by-Linear

Association

3.727 1 .054

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 11.50.

b. Computed only for a 2x2 table

144

Gender * AP8

Crosstab

AP8

Not Used Used Total

Gender Male Count 187 13 200

% within Gender 93.5% 6.5% 100.0%

% within AP8 51.7% 34.2% 50.0%

% of Total 46.8% 3.3% 50.0%

Female Count 175 25 200

% within Gender 87.5% 12.5% 100.0%

% within AP8 48.3% 65.8% 50.0%

% of Total 43.8% 6.3% 50.0%

Total Count 362 38 400

% within Gender 90.5% 9.5% 100.0%

% within AP8 100.0% 100.0% 100.0%

% of Total 90.5% 9.5% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 4.187a 1 .041

Continuity Correctionb 3.518 1 .061

Likelihood Ratio 4.253 1 .039

Fisher's Exact Test .060 .030

Linear-by-Linear

Association

4.177 1 .041

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 19.00.

b. Computed only for a 2x2 table

145

Gender * AP9

Crosstab

AP9

Not Used Used Total

Gender Male Count 193 7 200

% within Gender 96.5% 3.5% 100.0%

% within AP9 50.8% 35.0% 50.0%

% of Total 48.3% 1.8% 50.0%

Female Count 187 13 200

% within Gender 93.5% 6.5% 100.0%

% within AP9 49.2% 65.0% 50.0%

% of Total 46.8% 3.3% 50.0%

Total Count 380 20 400

% within Gender 95.0% 5.0% 100.0%

% within AP9 100.0% 100.0% 100.0%

% of Total 95.0% 5.0% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.895a 1 .169

Continuity Correctionb 1.316 1 .251

Likelihood Ratio 1.923 1 .166

Fisher's Exact Test .251 .125

Linear-by-Linear

Association

1.890 1 .169

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 10.00.

b. Computed only for a 2x2 table

146

Gender * AP10

Crosstab

AP10

Not Used Used Total

Gender Male Count 194 6 200

% within Gender 97.0% 3.0% 100.0%

% within AP10 50.3% 42.9% 50.0%

% of Total 48.5% 1.5% 50.0%

Female Count 192 8 200

% within Gender 96.0% 4.0% 100.0%

% within AP10 49.7% 57.1% 50.0%

% of Total 48.0% 2.0% 50.0%

Total Count 386 14 400

% within Gender 96.5% 3.5% 100.0%

% within AP10 100.0% 100.0% 100.0%

% of Total 96.5% 3.5% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square .296a 1 .586

Continuity Correctionb .074 1 .786

Likelihood Ratio .297 1 .586

Fisher's Exact Test .601 .393

Linear-by-Linear

Association

.295 1 .587

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 7.00.

b. Computed only for a 2x2 table

147

Gender * AP11

Crosstab

AP11

Not Used Used Total

Gender Male Count 194 6 200

% within Gender 97.0% 3.0% 100.0%

% within AP11 50.3% 42.9% 50.0%

% of Total 48.5% 1.5% 50.0%

Female Count 192 8 200

% within Gender 96.0% 4.0% 100.0%

% within AP11 49.7% 57.1% 50.0%

% of Total 48.0% 2.0% 50.0%

Total Count 386 14 400

% within Gender 96.5% 3.5% 100.0%

% within AP11 100.0% 100.0% 100.0%

% of Total 96.5% 3.5% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square .296a 1 .586

Continuity Correctionb .074 1 .786

Likelihood Ratio .297 1 .586

Fisher's Exact Test .601 .393

Linear-by-Linear

Association

.295 1 .587

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 7.00.

b. Computed only for a 2x2 table

148

Gender * AP12

Crosstab

AP12

Not Used Used Total

Gender Male Count 194 6 200

% within Gender 97.0% 3.0% 100.0%

% within AP12 49.2% 100.0% 50.0%

% of Total 48.5% 1.5% 50.0%

Female Count 200 0 200

% within Gender 100.0% .0% 100.0%

% within AP12 50.8% .0% 50.0%

% of Total 50.0% .0% 50.0%

Total Count 394 6 400

% within Gender 98.5% 1.5% 100.0%

% within AP12 100.0% 100.0% 100.0%

% of Total 98.5% 1.5% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 6.091a 1 .014

Continuity Correctionb 4.230 1 .040

Likelihood Ratio 8.409 1 .004

Fisher's Exact Test .030 .015

Linear-by-Linear

Association

6.076 1 .014

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 3.00.

b. Computed only for a 2x2 table

149

Gender * AP13

Crosstab

AP13

Not Used Used Total

Gender Male Count 196 4 200

% within Gender 98.0% 2.0% 100.0%

% within AP13 49.7% 66.7% 50.0%

% of Total 49.0% 1.0% 50.0%

Female Count 198 2 200

% within Gender 99.0% 1.0% 100.0%

% within AP13 50.3% 33.3% 50.0%

% of Total 49.5% .5% 50.0%

Total Count 394 6 400

% within Gender 98.5% 1.5% 100.0%

% within AP13 100.0% 100.0% 100.0%

% of Total 98.5% 1.5% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square .677a 1 .411

Continuity Correctionb .169 1 .681

Likelihood Ratio .690 1 .406

Fisher's Exact Test .450 .343

Linear-by-Linear

Association

.675 1 .411

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 3.00.

b. Computed only for a 2x2 table

150

Gender * AP14

Crosstab

AP14

Not Used Used Total

Gender Male Count 197 3 200

% within Gender 98.5% 1.5% 100.0%

% within AP14 50.9% 23.1% 50.0%

% of Total 49.3% .8% 50.0%

Female Count 190 10 200

% within Gender 95.0% 5.0% 100.0%

% within AP14 49.1% 76.9% 50.0%

% of Total 47.5% 2.5% 50.0%

Total Count 387 13 400

% within Gender 96.8% 3.3% 100.0%

% within AP14 100.0% 100.0% 100.0%

% of Total 96.8% 3.3% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 3.896a 1 .048

Continuity Correctionb 2.862 1 .091

Likelihood Ratio 4.103 1 .043

Fisher's Exact Test .087 .044

Linear-by-Linear

Association

3.886 1 .049

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 6.50.

b. Computed only for a 2x2 table

151

Gender * AP15

Crosstab

AP15

Not Used Used Total

Gender Male Count 197 3 200

% within Gender 98.5% 1.5% 100.0%

% within AP15 49.7% 75.0% 50.0%

% of Total 49.3% .8% 50.0%

Female Count 199 1 200

% within Gender 99.5% .5% 100.0%

% within AP15 50.3% 25.0% 50.0%

% of Total 49.8% .3% 50.0%

Total Count 396 4 400

% within Gender 99.0% 1.0% 100.0%

% within AP15 100.0% 100.0% 100.0%

% of Total 99.0% 1.0% 100.0%

Chi-Square Tests

Value Df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.010a 1 .315

Continuity Correctionb .253 1 .615

Likelihood Ratio 1.057 1 .304

Fisher's Exact Test .623 .312

Linear-by-Linear

Association

1.008 1 .315

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 2.00.

b. Computed only for a 2x2 table

152

Gender * AP16

Crosstab

AP16

Not Used Used Total

Gender Male Count 198 2 200

% within Gender 99.0% 1.0% 100.0%

% within AP16 49.7% 100.0% 50.0%

% of Total 49.5% .5% 50.0%

Female Count 200 0 200

% within Gender 100.0% .0% 100.0%

% within AP16 50.3% .0% 50.0%

% of Total 50.0% .0% 50.0%

Total Count 398 2 400

% within Gender 99.5% .5% 100.0%

% within AP16 100.0% 100.0% 100.0%

% of Total 99.5% .5% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 2.010a 1 .156

Continuity Correctionb .503 1 .478

Likelihood Ratio 2.783 1 .095

Fisher's Exact Test .249 .249

Linear-by-Linear

Association

2.005 1 .157

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 1.00.

b. Computed only for a 2x2 table

153

Gender * AP17

Crosstab

AP17

Not Used Used Total

Gender Male Count 199 1 200

% within Gender 99.5% .5% 100.0%

% within AP17 50.3% 25.0% 50.0%

% of Total 49.8% .3% 50.0%

Female Count 197 3 200

% within Gender 98.5% 1.5% 100.0%

% within AP17 49.7% 75.0% 50.0%

% of Total 49.3% .8% 50.0%

Total Count 396 4 400

% within Gender 99.0% 1.0% 100.0%

% within AP17 100.0% 100.0% 100.0%

% of Total 99.0% 1.0% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.010a 1 .315

Continuity Correctionb .253 1 .615

Likelihood Ratio 1.057 1 .304

Fisher's Exact Test .623 .312

Linear-by-Linear

Association

1.008 1 .315

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 2.00.

b. Computed only for a 2x2 table

154

Gender * AP18

Crosstab

AP18

Not Used Used Total

Gender Male Count 199 1 200

% within Gender 99.5% .5% 100.0%

% within AP18 49.9% 100.0% 50.0%

% of Total 49.8% .3% 50.0%

Female Count 200 0 200

% within Gender 100.0% .0% 100.0%

% within AP18 50.1% .0% 50.0%

% of Total 50.0% .0% 50.0%

Total Count 399 1 400

% within Gender 99.8% .3% 100.0%

% within AP18 100.0% 100.0% 100.0%

% of Total 99.8% .3% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.003a 1 .317

Continuity Correctionb .000 1 1.000

Likelihood Ratio 1.389 1 .239

Fisher's Exact Test 1.000 .500

Linear-by-Linear

Association

1.000 1 .317

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is .50.

b. Computed only for a 2x2 table

155

Gender * AP19

Crosstab

AP19

Not

Used

Used Total

Gend

er

Male Count 200 0 200

% within

Gender

100.0

%

.0% 100.0

%

% within

AP19

50.6% .0% 50.0%

% of Total 50.0% .0% 50.0%

Fema

le

Count 195 5 200

% within

Gender

97.5% 2.5% 100.0

%

% within

AP19

49.4% 100.0

%

50.0%

% of Total 48.8% 1.3% 50.0%

Total Count 395 5 400

% within

Gender

98.8% 1.3% 100.0

%

% within

AP19

100.0

%

100.0

%

100.0

%

% of Total 98.8% 1.3% 100.0

%

Chi-Square Tests

Value df Asymp.

Sig. (2-

sided)

Exact Sig.

(2-sided)

Exact Sig.

(1-sided)

Pearson Chi-

Square

5.063a 1 .024

Continuity

Correctionb

3.241 1 .072

Likelihood Ratio 6.995 1 .008

Fisher's Exact Test .061 .030

Linear-by-Linear

Association

5.051 1 .025

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected

count is 2.50.

b. Computed only for a 2x2 table

156

Gender * NAP1

Crosstab

NAP1

Not Used Used Total

Gender Male Count 197 3 200

% within Gender 98.5% 1.5% 100.0%

% within NAP1 52.1% 13.6% 50.0%

% of Total 49.3% .8% 50.0%

Female Count 181 19 200

% within Gender 90.5% 9.5% 100.0%

% within NAP1 47.9% 86.4% 50.0%

% of Total 45.3% 4.8% 50.0%

Total Count 378 22 400

% within Gender 94.5% 5.5% 100.0%

% within NAP1 100.0% 100.0% 100.0%

% of Total 94.5% 5.5% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 12.314a 1 .000

Continuity Correctionb 10.823 1 .001

Likelihood Ratio 13.650 1 .000

Fisher's Exact Test .001 .000

Linear-by-Linear

Association

12.283 1 .000

N of Valid Cases 400

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 11.00.

b. Computed only for a 2x2 table

157

Gender * NAP2

Crosstab

NAP2

Not Used Used Total

Gender Male Count 198 2 200

% within Gender 99.0% 1.0% 100.0%

% within NAP2 49.7% 100.0% 50.0%

% of Total 49.5% .5% 50.0%

Female Count 200 0 200

% within Gender 100.0% .0% 100.0%

% within NAP2 50.3% .0% 50.0%

% of Total 50.0% .0% 50.0%

Total Count 398 2 400

% within Gender 99.5% .5% 100.0%

% within NAP2 100.0% 100.0% 100.0%

% of Total 99.5% .5% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 2.010a 1 .156

Continuity Correctionb .503 1 .478

Likelihood Ratio 2.783 1 .095

Fisher's Exact Test .249 .249

Linear-by-Linear

Association

2.005 1 .157

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 1.00.

b. Computed only for a 2x2 table

158

Gender * NAP3

Crosstab

NAP3

Not Used Used Total

Gender Male Count 199 1 200

% within Gender 99.5% .5% 100.0%

% within NAP3 50.3% 25.0% 50.0%

% of Total 49.8% .3% 50.0%

Female Count 197 3 200

% within Gender 98.5% 1.5% 100.0%

% within NAP3 49.7% 75.0% 50.0%

% of Total 49.3% .8% 50.0%

Total Count 396 4 400

% within Gender 99.0% 1.0% 100.0%

% within NAP3 100.0% 100.0% 100.0%

% of Total 99.0% 1.0% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.010a 1 .315

Continuity Correctionb .253 1 .615

Likelihood Ratio 1.057 1 .304

Fisher's Exact Test .623 .312

Linear-by-Linear

Association

1.008 1 .315

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 2.00.

b. Computed only for a 2x2 table

159

Gender * NAP4

Crosstab

NAP4

Not Used Used Total

Gender Male Count 199 1 200

% within Gender 99.5% .5% 100.0%

% within NAP4 49.9% 100.0% 50.0%

% of Total 49.8% .3% 50.0%

Female Count 200 0 200

% within Gender 100.0% .0% 100.0%

% within NAP4 50.1% .0% 50.0%

% of Total 50.0% .0% 50.0%

Total Count 399 1 400

% within Gender 99.8% .3% 100.0%

% within NAP4 100.0% 100.0% 100.0%

% of Total 99.8% .3% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square 1.003a 1 .317

Continuity Correctionb .000 1 1.000

Likelihood Ratio 1.389 1 .239

Fisher's Exact Test 1.000 .500

Linear-by-Linear

Association

1.000 1 .317

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is .50.

b. Computed only for a 2x2 table

160

Gender * NAP5

Crosstab

NAP5

Not Used Used Total

Gender Male Count 199 1 200

% within Gender 99.5% .5% 100.0%

% within NAP5 50.0% 50.0% 50.0%

% of Total 49.8% .3% 50.0%

Female Count 199 1 200

% within Gender 99.5% .5% 100.0%

% within NAP5 50.0% 50.0% 50.0%

% of Total 49.8% .3% 50.0%

Total Count 398 2 400

% within Gender 99.5% .5% 100.0%

% within NAP5 100.0% 100.0% 100.0%

% of Total 99.5% .5% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-

sided)

Exact Sig. (2-

sided)

Exact Sig. (1-

sided)

Pearson Chi-Square .000a 1 1.000

Continuity Correctionb .000 1 1.000

Likelihood Ratio .000 1 1.000

Fisher's Exact Test 1.000 .751

Linear-by-Linear

Association

.000 1 1.000

N of Valid Cases 400

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 1.00.

b. Computed only for a 2x2 table

161

Gender * NAP6

Crosstab

NAP6

Not Used Total

Gender Male Count 200 200

% within Gender 100.0% 100.0%

% within NAP6 50.0% 50.0%

% of Total 50.0% 50.0%

Female Count 200 200

% within Gender 100.0% 100.0%

% within NAP6 50.0% 50.0%

% of Total 50.0% 50.0%

Total Count 400 400

% within Gender 100.0% 100.0%

% within NAP6 100.0% 100.0%

% of Total 100.0% 100.0%

Chi-Square Tests

Value

Pearson Chi-Square .a

N of Valid Cases 400

a. No statistics are computed

because NAP6 is a constant.