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Seminar 3 (2011)

Exploring Assumptions, T-test analysis and writing up your lab

report.

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Plan for todayWhy is .05 so important

Why are Degrees of freedom different on the within and between t-tests

What do we need to do before computing a t-test– Plot the variables using a histogram (visual check for

normality)– Check for skewdness– Check for kurtosis

Running a T-test

Writing up the lab report.

Designing an experiment

Hypothesis– When you are designing an experiment you

have two types of hypothesis Experimental (Exciting) hypothesis

– You predicted what the result will be

Null (Dull) hypothesis – The findings are just down to chance

Variables– The variable you change (Independent)– The result of that change (Dependent)

Shandy Study

My friend claimed that he can tell the difference between 2 pints of Shandy depending on how it was made

– Where the lager went in first

Vs.– Where the lemonade went in first

Shandy Study

Hypothesis– My Friend CAN taste the difference between

pints where lemonade has gone in first compared to where the lager has gone in first.

– The answers are down to chance

Variables– Independent Variable: Which order the 2

ingredients go in.

– Dependent Variable: His answer

Lets do the StudyLets have drinks some with lager first (LF) and some with lemonade in first (LemF).– There will be an equal number of LF and LemF drinks.– But you will not know which order they were in.

If I gave 2 drinks, there are only 2 orders the pints can be placed:

LF LemF or LemF LFWith only 2 possible orders the participant has a 50% chance of getting the right answer.

Which is not very convincing, as I hate Shandy and I would also have a good chance of getting the answer right just by guessing

So lets make things more complicated by having 6 drinks

There are 20 orders in which the pints can be placed.

If your guessing she would have a 1 in 20 chance of getting the correct answer. – 1 ÷ 20=.05 to make that in to a percentage

5% chance of guessing correctly

Lets say the participant did get the answer right six times in a row.

I would be pretty convinced. And so would Fisher

LemF LemF LemF LF LF LF

Who is Fisher?Fisher (1925) suggested that only when we are 95% certain that a result is genuine (not happening by chance) we should accept it as being true.

This is the basic principle of saying that something is statistically significant.

It may not really be true (you may have just guessed) but this is where the agreed line has been drawn.

So Back to the hypotheses

Hypothesis– Experimental (Exciting) hypothesis: You can taste the

difference between pints that have the ingredients going in a different order.

– Null (Dull) hypothesis: She is just guessing, answers are just down to chance.

You have not “proven” either of the hypotheses.

But we can say the Null one is unlikely or reject it ; we are 95% sure it is not true

Can we ever “prove” the experimental hypothesis ?

Well No,

It is like the lottery, the odds of picking the 6 correct numbers is 1 in 13,983,815.

So we can be very sure we will not pick the correct numbers, it is significantly unlikely.

But then again someone does manage to do this nearly every week.

Which is why we can only say the Null hypothesis is statically unlikely to be true.

Degrees of freedom

Paired Samples t-test or Within-subjects -subjects t-test

Our IV: Recall condition – Level 1 : Individual recall – Level 2 : Group recall

Degrees of freedom

Independent Samples t-test or Between-subjects t-test

Our IV: Group size – Level 1 : 2 person group– Level 2 :5 person group

2 person group 5

per

son

group

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Festival HygieneField (2009) looked at the hygiene levels of Download festival attendees across the 3 days.

Today we are going to be looking at the hygiene levels of Sonisphere festival attendees across the 2 day festival.

Festival HygieneField (2009, p.94) reports a scale ranging between:

0 = “You smell like a corpse that’s been left to rot up a skunk’s arse”

4 = “You smell of sweet roses on a fresh spring day”

Our survey of Sonisphere festival used

the same scale

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Open the Data file

The data set we are using is called “Sonisphere Festival”

It is on the U drive U24103

Seminar 3

Use the EXPLORE function to produce skew and kurtosis statistics

Skew should = 0 in perfect normally distributed data.

Skew = 0 (normal)Positive Skew = + Negative Skew

Use the EXPLORE function to produce skew and kurtosis statistics

Kurtosis should = 0 in perfect normally distributed data.

Kurtosis = 0 “mesokurtosis”

+ ve kurtosis

“leptokurtosis”

- ve kurtosis

“platykurtosis”

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What’s an acceptable level of skew and kurtosis for a t-test?

Rules of thumb-

- Skewness ok if less than 0.8

- Kurtosis ok if between -2 & +2

Are our levels of skew and kurtosis acceptable?

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Our sample includes people with both standard and VIP tickets.

Use Select Cases if and exclude all the people with VIP tickets

Now create the Histograms and Descriptives again.

Then Answer Questions 1 to 6.

Take Select Case if Off

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******Take off the filter and Select all cases *****

We want to see if there is a significant difference in hygiene levels of people with Standard and VIP tickets.

What kind of t-test do we need to use for our hypothesis?

– Independent (Between-subjects t-test ) – Paired-samples (Within-subjects t-test

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Recode in to different variableTransform

Recode in to different variable

Move Tick_Type across

Name Two_Tick_Type– Change

Old and New Values– 0->0, 1->1, 2->1, 3->1, 4->1

Continue then OK

How to do an independent-samples t-test using SPSS

An independent-samples t-test involves comparing two different groups on a single dependent variable.

Between-subjects t-test

Dependent variable (DV) goes hereIndependent variable (IV) goes here

For the IV SPSS needs to be told what the label numbers are of the two groups we want to compare

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Means and Std. Deviations of the two groups on the DV

Are two rows for the t-test result. Only one row, defined by the result of the Levene’s test, is looked at

If the significance for Levene's test is:

greater-than (>) .05 use the top row “Equal variables assumed”.

.05 or below (=<), then use the bottom row "Equal Variances not

Assumed" .

If the significance for Levene's test is 0.05 or below, then use the bottom row "Equal Variances not Assumed" test. Otherwise use the top row “Equal variables assumed”.

Levene's test is greater than .05 therefore we need to use the top row.

t=2.49 df=98 p=.015

There was a significant effect of perceived group size, t(98)=2.49 p=.015. Participants recall a grater number of items when they thought they were in a group of two (M=5.66, SD= 1.44) as apposed to a group of 5 people (M=4.92, SD=1.53)

If the significance for Levene's test is 0.05 or below, then use the bottom row "Equal Variances not Assumed" test. Otherwise use the top row “Equal variables assumed”.

Levene's test is less than .05 therefore we need to use the bottom row.

t=2.49 df=97.56 p=.015

There was a significant effect of perceived group size, t(97.56)=2.49 p=.015. Participants recall a grater number of items when they thought they were in a group of two (M=5.66, SD= 1.44) as apposed to a group of 5 people (M=4.92, SD=1.53)

How to do a paired-samples t-test using SPSS

A paired samples t-test would allow us to compare the same participants performance on 2 variables

Within-subjects t-test

Mean for individual scores Mean for group scores

Means (and SDs) for the two variables

Mean difference between the two variables

Standard deviation of the difference between the two variables

t = 19.71Note: we ignore minus signs when reporting t values

df=49 p <.001

p=.0000000000000000000000000000000000004738209580081584

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There was a significant effect of perceived group, t(99)=19.71 p<.001. Participants recall a grater number of items when they thought they were working on there own (M=8.93, SD= 1.18) as apposed to a group (M=5.29, SD=1.53)

t=19.71 df=99 p<.001

Field Easter Egg hunt

The are 9 hidden messages (Easter eggs)

In the Core Text Field (2009). The first person

to show me or john a Easter egg  will receive

a Easter egg*.

*One per person.Field, A. (2009) Discovering Statistics Using SPSS (third edition). Sage publications: London, UK.

We are going to stop for 20 min so you can work through questions 1- 8 on the worksheet and

have a break.**Question 7 is answered using the day one data**