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Page 1: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

STA 2023 EXAM-1

Few Solutions for the

Practice Problems

Mudunuru, Venkateswara Rao

STA 2023

Spring 2016

From Chapters 1, 2, and 3

© Ven M

udun

uru

Page 2: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 1

Practice Problems Sheet

Important vocabulary from Chapter-1 for Exam-1:

1) For the following data given below in A, B, C. Do the following:

a) Find 10%, 15% trimmed mean.

b) Write the five number summary using the entire data. Calculate IQR.

c) Draw a box and whisker plot.

A) 12, 41, 25, 7, 10, 22, 38, 10, 12, 19, 19, 12, 8, 16, 12, 5

B) 19, 11, 7, 24, 13, 15, 10, 3, 10, 20

C) 79, 50, 82, 91, 87, 118, 80, 93

Statistics Survey Bias Stratified

Inferential Parameter Cluster Sampling Error

Systematic Subjects Convenience Blind/Single Blind

Quantitative Census Individuals Systematic

Qualitative Ordinal Simple Random Continuous

Interval Statistic Discrete Descriptive

Ratio Double Blind Nominal Multi-Stage

Sampling

© Ven M

udun

uru

Page 3: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 2

2) For the interval data given in tables D, E, F, G. Calculate the following. Write your values

of (b),(c),(d),(e) in the Table format given below:

Note: Remember that the table with the following column headings with details of first two

columns and the required number of rows based on the problem will be given on the exam.

a) Class width.

b) Cumulative frequency

c) Class midpoint (or class

mark)

d) Draw a frequency histogram

e) Class boundaries

f) Draw a ogive graph

g) Relative frequency

h) Draw a relative frequency

histogram

Interval Frequency Class

Midpoint

Class

Boundaries

Relative

Frequency

Cumulative

Frequency

D)

Weight(lb) Client

frequency

30-49 8

50-69 10

70-89 12

90-109 7

E)

Time in

seconds

Freq

1 to 10 15

11 to 20 20

21 to 30 29

31 to 40 25

41 to 50 22

51 to 60 14

Cost

in $

Sales

frequency

10-26 2

27-43 15

44-60 48

61-77 23

F)

G)

Length in

Meters Frequency

1.1 to 1.5 2

1.6 to 2.0 4

2.1 to 2.5 7

2.6 to 3.0 10

3.1 to 3.5 11

© Ven M

udun

uru

Page 4: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 3

3) Estimate the sample mean, sample standard deviation, Sample variance for the

following interval data in tables D, E, F, and G. Use the Table format given

below.

Note: Remember that the table with the following column headings with details of first

two columns and the required number of rows based on the problem will be given on the

exam.

Interval 𝑭𝒓𝒆𝒒𝒖𝒆𝒏𝒄𝒚, 𝒇 𝑴𝒊𝒅𝒑𝒐𝒊𝒏𝒕, 𝒙 𝒐𝒓 𝒎 𝒙𝒇 𝒙𝟐𝒇

4) Draw Stem and Leaf graph for the following and identify the shape. (Symmetric/Right Skewed/Left Skewed)

a) Student GPAs: 1.8, 2.2, 2.6, 3.4, 3.5, 1.9, 3.2, 3.3, 2.4, 4.0, 3.5, 2.9, 3.6, 3.6, 2.7, 3.5, 4.0,

3.3, 3.0, 2.2, and 1.9.

b) Final scores of students:

70, 48, 100, 65, 69, 73, 30, 93, 76, 82, 100, 89, 72, 74, 95, 91, 86, 75, 55, and 76.

5) Draw the Pie Chart for the following data in tables H, I, J

Note: Remember that the table with the following column headings with details of first

two columns and the required number of rows based on the problem will be given on the

exam

6) Extract the data from the stem and leaf plots given below in K, L:

Category 𝑭𝒓𝒆𝒒𝒖𝒆𝒏𝒄𝒚, 𝒇 𝑷𝒆𝒓𝒆𝒏𝒕𝒂𝒈𝒆 (%) 𝑫𝒆𝒈𝒓𝒆𝒆𝒔

H) I) J)

ICU

Type

Frequency

Medical 12

Surgery 6

Cardiac 5

Other 2

Expenses Cost in $

Housing & Food 130

Savings 25

Miscellaneous 20

Insurance 35

Major Students

Maths 45

Biology 21

Nursing 55

Business 45

Stem Leaf

2 3,4,5,6,8,9

3 5,7

4 1,4,4,6,6,8,9

5 5,8,9

K) Stem Leaf

7 0, 3, 3, 5, 6, 7

8 2, 4, 5, 5, 4

9 0, 0, 5, 3, 7, 1

L)

Key: 2|3 is 0.23

© Ven M

udun

uru

Page 5: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 4

REMEMBER:

Graph Type X-Axis Y-Axis Histogram or

Frequency Histogram

Class

Boundaries/Midpoints Frequency

Relative Frequency

histogram

Class

Boundaries/Midpoints Relative Frequency

Ogive Graph Class Upper

Boundaries Cumulative frequency

𝑪𝒉𝒂𝒑𝒕𝒆𝒓 − 𝟑 𝑸𝒖𝒊𝒄𝒌 𝒇𝒐𝒓𝒎𝒖𝒍𝒂𝒔 𝑳𝒊𝒔𝒕𝒆𝒅 𝑫𝒂𝒕𝒂

𝑺𝒂𝒎𝒑𝒍𝒆 𝑴𝒆𝒂𝒏: �̅� =∑ 𝒙𝒊

𝒏𝒊=𝟏

𝒏

𝑺𝒂𝒎𝒑𝒍𝒆 𝑺𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝑫𝒆𝒗𝒊𝒂𝒕𝒊𝒐𝒏

𝒔 = √∑(𝒙𝒊 − �̅�)𝟐

𝒏 − 𝟏 𝑶𝑹

𝒔 =√∑ 𝒙𝒊

𝟐 −(∑ 𝒙𝒊)𝟐

𝒏𝒏 − 𝟏

𝑺𝒂𝒎𝒑𝒍𝒆 𝑽𝒂𝒓𝒊𝒂𝒏𝒄𝒆, 𝒔𝟐, 𝒊𝒔 𝒐𝒃𝒕𝒂𝒊𝒏𝒆𝒅 𝒃𝒚 𝒔𝒒𝒖𝒂𝒓𝒊𝒏𝒈 𝒕𝒉𝒆

𝒔𝒂𝒎𝒑𝒍𝒆 𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝒅𝒆𝒗𝒊𝒂𝒕𝒊𝒐𝒏, 𝒔

𝑮𝒓𝒐𝒖𝒑𝒆𝒅 𝒐𝒓 𝑰𝒏𝒕𝒆𝒓𝒗𝒂𝒍 𝒅𝒂𝒕𝒂. 𝑵𝒐𝒕𝒆: 𝑰𝒏𝒕𝒆𝒓𝒗𝒂𝒍 𝒅𝒂𝒕𝒂 𝒊𝒔 𝒔𝒂𝒎𝒆 𝒂𝒔 𝒈𝒓𝒐𝒖𝒑𝒆𝒅 𝒅𝒂𝒕𝒂 𝒘𝒊𝒕𝒉 𝒂𝒏 𝒂𝒅𝒅𝒊𝒕𝒊𝒐𝒏𝒂𝒍

𝒔𝒕𝒆𝒑 𝒐𝒇 𝒇𝒊𝒏𝒅𝒊𝒏𝒈 𝒕𝒉𝒆 𝒎𝒊𝒅 𝒑𝒐𝒊𝒏𝒕 𝒐𝒇 𝒕𝒉𝒆 𝒊𝒏𝒕𝒆𝒓𝒗𝒂𝒍 𝒐𝒇 𝒆𝒂𝒄𝒉 𝒄𝒍𝒂𝒔𝒔

𝒂𝒏𝒅 𝒕𝒓𝒆𝒂𝒕𝒊𝒏𝒈 𝒊𝒕 𝒂𝒔 𝒙𝒊 𝒐𝒇 𝒕𝒉𝒆 𝒈𝒓𝒐𝒖𝒑𝒆𝒅 𝒅𝒂𝒕𝒂

𝑺𝒂𝒎𝒑𝒍𝒆 𝑴𝒆𝒂𝒏: �̅� =∑ 𝒙𝒊𝒇𝒊

𝒌𝒊=𝟏

∑ 𝒇𝒊𝒌𝒊=𝟏

=∑ 𝒎𝒊𝒇𝒊

𝒌𝒊=𝟏

∑ 𝒇𝒊𝒌𝒊=𝟏

=∑ 𝒎𝒊𝒇𝒊

𝒌𝒊=𝟏

𝒏

𝑺𝒂𝒎𝒑𝒍𝒆 𝑺𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝑫𝒆𝒗𝒊𝒂𝒕𝒊𝒐𝒏

𝒔 = √∑(𝒙𝒊−�̅�)𝟐𝒇𝒊

𝒏−𝟏 𝑶𝑹 𝒔 = √∑ 𝒙𝒊

𝟐𝒇𝒊−(∑ 𝒙𝒊𝒇𝒊)

𝟐

𝒏

𝒏−𝟏

𝑺𝒂𝒎𝒑𝒍𝒆 𝑽𝒂𝒓𝒊𝒂𝒏𝒄𝒆, 𝒔𝟐, 𝒊𝒔 𝒐𝒃𝒕𝒂𝒊𝒏𝒆𝒅 𝒃𝒚 𝒔𝒒𝒖𝒂𝒓𝒊𝒏𝒈 𝒕𝒉𝒆 𝒔𝒂𝒎𝒑𝒍𝒆 𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝒅𝒆𝒗𝒊𝒂𝒕𝒊𝒐𝒏, 𝒔 © Ven M

udun

uru

Page 6: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 5

FEW SOLUTIONS FOR YOUR HELP. PLEASE NOTE THAT YOU MUST SHOW THE

FORMULAS USED FOR EVERY PROBLEM.

1) [FOR TABLE: A] Ordering the data in ascending form, we get

5 7 8 10 10 12 12 12

12 16 19 19 22 25 38 41

Here we have 16 data values.

a) TRIMMED MEAN

10% Trimmed Mean: We have 10% of 16 = 1.6 ~ 2 { (10

100) × 16 = 1.6 }

Hence Trim 2 data points from both the ends of the ordered data. So we have 12

remaining points.

5, 7, 8, 10, 10, 12, 12, 12, 12, 16, 19, 19, 22, 25, 38, 41

The Mean of 12 points is the 10% Trimmed mean and is obtained by summing

the remaining 12 data points and dividing by 12.

10% Trimmed mean, �̅� =∑ 𝑥𝑖

𝑛=

177

12= 14.75

15% Trimmed Mean: We have 15% of 16 = 2.4 ~ 2 { (15

100) × 16 = 2.4 }

Hence Trim 2 data points from both the ends of the ordered data. So we have 12

remaining points. Which in turn gives us the same trimmed mean as we have for 10%

above.

b) Five Number Summary: 𝑀𝑖𝑛𝑖𝑚𝑢𝑚 = 5;

𝑄1 =10 + 10

2= 10; 𝑄2 =

12 + 12

2= 12; 𝑄3 =

19 + 22

2= 20.5

𝑀𝑎𝑥𝑖𝑚𝑢𝑚 = 41; 𝐼𝑄𝑅 = 𝑄3 – 𝑄1 = 20.5 – 10 = 10.5

c) Box Plot:

5 10 12 20.5 41 © Ven M

udun

uru

Page 7: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 6

Outlier Identification:

Any point which does not fall in the interval (𝑄1 − 1.5 ∗ 𝐼𝑄𝑅, 𝑄3 + 1.5 ∗ 𝐼𝑄𝑅) is considered as

an outlier.

i.e., ( 𝟏𝟎 – (𝟏. 𝟓 ∗ 𝟏𝟎. 𝟓), 𝟐𝟎. 𝟓 + (𝟏. 𝟓 ∗ 𝟏𝟎. 𝟓)) = ( −𝟓. 𝟕𝟓, 𝟑𝟔. 𝟐𝟓 ). Hence the potential outliers in

the data are 38 and 41.

[FOR TABLE: B] Ordering the data in ascending form, we get

3, 7, 10, 10, 11, 13, 15, 19, 20, 24

a) TRIMMED MEAN

10% Trimmed Mean: We have 10% of 10 = 1 { (10

100) × 10 = 1}

Hence Trim 1 data point from both the ends of the ordered data. So we have 8

remaining points.

3, 7, 10, 10, 11, 13, 15, 19, 20, 24

The Mean of 8 points is the 10% Trimmed mean and is obtained by summing the

remaining 8 data points and dividing by 8.

10% Trimmed mean, �̅� =∑ 𝑥𝑖

𝑛=

105

8= 13.125

15% Trimmed Mean: We have 15% of 10 = 1.5 ~ 2 { (15

100) × 10 = 1.5 }

Hence Trim 2 data points from both the ends of the ordered data. So we have 6

remaining points.

3, 7, 10, 10, 11, 13, 15, 19, 20, 24

The Mean of 6 points is the 15% Trimmed mean and is obtained by summing

these remaining 6 data points and dividing by 6.

15% Trimmed mean, �̅� =∑ 𝑥𝑖

𝑛=

78

6= 13

b) Five Number Summary: 𝑀𝑖𝑛𝑖𝑚𝑢𝑚 = 3;

𝑄1 = 10; 𝑄2 =11 + 13

2= 12; 𝑄3 = 19

𝑀𝑎𝑥𝑖𝑚𝑢𝑚 = 24; 𝐼𝑄𝑅 = 𝑄3 – 𝑄1 = 19 – 10 = 9

c) Box Plot:

3 10 12 19 24 © Ve

n Mud

unuru

Page 8: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 7

Fre

qu

ency

Midpoints

Outlier Identification:

Any point which does not fall in the interval (𝑄1 − 1.5 ∗ 𝐼𝑄𝑅, 𝑄3 + 1.5 ∗ 𝐼𝑄𝑅) is

considered as an outlier.

i.e., ( 𝟏𝟎 – (𝟏. 𝟓 ∗ 𝟗), 𝟏𝟗 + (𝟏. 𝟓 ∗ 𝟗)) = ( −𝟑. 𝟓, 𝟑𝟐. 𝟓 )

Hence there are NO potential outliers in the data.

1) [FOR TABLE: D]: 𝐶𝐿𝐴𝑆𝑆 𝑊𝐼𝐷𝑇𝐻: (49 − 30) + 1 = 20

NOTE: Using the data in columns draw the requested graphs. Check slides for more detail.

Frequency Histogram:

Weight(lb) Client

frequency

Class

Mid-Point

Class

Boundaries

Relative

Frequency

(%)

Cumulative

Frequency

30-49 8 39.5 29.5 49.5 21.62 8

50-69 10 59.5 49.5 69.5 27.03 18

70-89 12 79.5 69.5 89.5 32.43 30

90-109 7 99.5 89.5 109.5 18.92 37

37

© Ven M

udun

uru

Page 9: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 8

Rel

ativ

e F

req

uen

cy

Midpoints

Cu

mu

lati

ve

Fre

qu

ency

Class Upper Boundaries

Relative Frequency Histogram

Ogive Graph:

[FOR TABLE: G] CLASS WIDTH: (1.5-1.1) + 0.1 = 0.5

Length in

Meters Frequency

Class

Midpoint

Class

Boundaries

Relative

Frequency

(%)

Cumulative

Frequency

1.1 to 1.5 2 1.3 1.05 1.55 5.88 2

1.6 to 2.0 4 1.8 1.55 2.05 11.76 6

2.1 to 2.5 7 2.3 2.05 2.55 20.59 13

2.6 to 3.0 10 2.8 2.55 3.05 29.41 23

3.1 to 3.5 11 3.3 3.05 3.55 32.35 34

34 © Ven M

udun

uru

Page 10: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 9

Fre

qu

ency

Midpoints Midpoints

Rel

ativ

e F

req

uen

cy

Class Upper Boundaries

Cu

mu

lati

ve

Fre

qu

ency

3) [TABLE: D] For Sample Mean, Sample Standard Deviation and Sample

Variance. Follow these steps:

Weight(lb) Client

frequency Midpoint, m 𝒇. 𝒎 𝒇. 𝒎𝟐

30-49 8 39.5 316 12482

50-69 10 59.5 595 35402.5

70-89 12 79.5 954 75843

90-109 7 99.5 696.5 69301.75

37 2561.5 193029.3

© Ven M

udun

uru

Page 11: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 10

You MUST mention the formulas and steps [given in green color below] in your exam)

Sample mean:

𝑁𝑂𝑇𝐸: �̅� =∑ 𝑓𝑖𝑚𝑖

𝑘𝑖=1

∑ 𝑓𝑖𝑘𝑖=1

=∑ 𝑓𝑖𝑚𝑖

𝑘𝑖=1

𝑛 𝑜𝑟 𝑡ℎ𝑖𝑠 𝑖𝑠 𝑠𝑎𝑚𝑒 𝑎𝑠

∑ 𝑥𝑖𝑓𝑖𝑘𝑖=1

∑ 𝑓𝑖𝑘𝑖=1

�̅� =∑ 𝑓𝑖𝑚𝑖

𝑘𝑖=1

𝑛=

2561.5

37= 69.23

Sample Standard Deviation,

𝑠 =√∑ 𝑥𝑖

2𝑓𝑖 −(∑ 𝑥𝑖𝑓𝑖)2

𝑛𝑛 − 1

=√193029.3 −

(2561.5)2

3737 − 1

= 20.88

Sample Variance: 𝑠2 = (15.531)2 = 436.04

[TABLE: G] For Sample Mean, Sample Standard Deviation and Sample Variance.

Follow these steps:

Length in

Meters Frequency Midpoint,

m 𝒇. 𝒎 𝒇. 𝒎𝟐

1.1 to 1.5 2 1.3 2.6 3.38

1.6 to 2.0 4 1.8 7.2 12.96

2.1 to 2.5 7 2.3 16.1 37.03

2.6 to 3.0 10 2.8 28 78.4

3.1 to 3.5 11 3.3 36.3 119.79

34 90.2 251.56

Sample mean:

𝑁𝑂𝑇𝐸: �̅� =∑ 𝑓𝑖𝑚𝑖

𝑘𝑖=1

∑ 𝑓𝑖𝑘𝑖=1

=∑ 𝑓𝑖𝑚𝑖

𝑘𝑖=1

𝑛 𝑜𝑟 𝑡ℎ𝑖𝑠 𝑖𝑠 𝑠𝑎𝑚𝑒 𝑎𝑠

∑ 𝑥𝑖𝑓𝑖𝑘𝑖=1

∑ 𝑓𝑖𝑘𝑖=1

�̅� =∑ 𝑓𝑖𝑚𝑖

𝑘𝑖=1

𝑛=

90.2

34= 2.65 © Ve

n Mud

unuru

Page 12: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 11

Sample Standard Deviation,

𝑠 =√∑ 𝑥𝑖

2𝑓𝑖 −(∑ 𝑥𝑖𝑓𝑖)2

𝑛𝑛 − 1

=√251.56 −

(90.2)2

3434 − 1

= 0.61

Sample Variance: 𝑠2 = (15.531)2 = 0.372

5) For Table –H: You must compute the Last Two Column values.

NOTE: These steps need not be shown in exam

Percentage for Surgery: 6

25× 100 = 24%

Degrees for Surgery: 24

100× 360 = 86.4

For Table –J:

ICU Type Frequency

Medical 12

Surgery 6

Cardiac 5

Other 2

ICU Type Frequency Percentage Degree

Medical 12 48 172.8

Surgery 6 24 86.4

Cardiac 5 20 72

Other 2 8 28.8

25 100 360

Major Students Percentage Degree

Maths 45 27.11 97.60

Biology 21 12.65 45.54

Nursing 55 33.13 119.27

Business 45 27.11 97.60

166

© Ven M

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Page 13: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 12

4) Draw Stem and Leaf graph for the following and identify the shape.

(Symmetric/Right Skewed/Left Skewed)

a) Student GPAs: 1.8, 2.2, 2.6, 3.4, 3.5, 1.9, 3.2, 3.3, 2.4, 4.0, 3.5, 2.9, 3.6, 3.6, 2.7,

3.5, 4.0, 3.3, 3.0, 2.2, and 1.9

Stem and Leaf Plot:

Clearly, Data is almost symmetrical (or bell shaped)

6) [FOR TABLE-K]:

The data points from the stem-leaf plot are:

0.23, 0.24, 0.25, 0.26, 0.28, 0.29, 0.35, 0.37, 0.41, 0.44, 0.44, 0.46, 0.46, 0.48, 0.49,

0.55, 0.58, 0.59

[FOR TABLE-L]:

The data points from the stem-leaf plot are:

70, 73, 73, 75, 76, 77, 82, 84, 85, 85, 84, 90, 90, 95, 93, 97, 91

Stem Leaf

1 8,9,9

2 2,6,4,9,7,2

3 4,5,2,3,5,6,5,3,0

4 0,0

Key: 1|8 is 1.8

© Ven M

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Page 14: STA 2023 EXAM-1 Few Solutions for the Practice Problemsvmudunur.myweb.usf.edu/SPRING 2016 Exam-1 Review Solutions.pdf · Few Solutions for the Practice Problems Mudunuru, Venkateswara

© Venkateswara Rao Mudunuru Spring 2016 Exam-1 Few Solutions For Practice Sheet 13

Note: Formulas will not be provided nor any cheat sheets are allowed on the exams.

𝑪𝒉𝒂𝒑𝒕𝒆𝒓 − 𝟑 𝑸𝒖𝒊𝒄𝒌 𝒇𝒐𝒓𝒎𝒖𝒍𝒂𝒔 𝑳𝒊𝒔𝒕𝒆𝒅 𝑫𝒂𝒕𝒂

𝑺𝒂𝒎𝒑𝒍𝒆 𝑴𝒆𝒂𝒏: �̅� =∑ 𝒙𝒊

𝒏𝒊=𝟏

𝒏

𝑺𝒂𝒎𝒑𝒍𝒆 𝑺𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝑫𝒆𝒗𝒊𝒂𝒕𝒊𝒐𝒏

𝒔 = √∑(𝒙𝒊 − �̅�)𝟐

𝒏 − 𝟏 𝑶𝑹

𝒔 =√∑ 𝒙𝒊

𝟐 −(∑ 𝒙𝒊)𝟐

𝒏𝒏 − 𝟏

𝑺𝒂𝒎𝒑𝒍𝒆 𝑽𝒂𝒓𝒊𝒂𝒏𝒄𝒆, 𝒔𝟐, 𝒊𝒔 𝒐𝒃𝒕𝒂𝒊𝒏𝒆𝒅 𝒃𝒚 𝒔𝒒𝒖𝒂𝒓𝒊𝒏𝒈 𝒕𝒉𝒆

𝒔𝒂𝒎𝒑𝒍𝒆 𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝒅𝒆𝒗𝒊𝒂𝒕𝒊𝒐𝒏, 𝒔

𝑮𝒓𝒐𝒖𝒑𝒆𝒅 𝒐𝒓 𝑰𝒏𝒕𝒆𝒓𝒗𝒂𝒍 𝒅𝒂𝒕𝒂.

𝑵𝒐𝒕𝒆: 𝑰𝒏𝒕𝒆𝒓𝒗𝒂𝒍 𝒅𝒂𝒕𝒂 𝒊𝒔 𝒔𝒂𝒎𝒆 𝒂𝒔 𝒈𝒓𝒐𝒖𝒑𝒆𝒅 𝒅𝒂𝒕𝒂 𝒘𝒊𝒕𝒉 𝒂𝒏 𝒂𝒅𝒅𝒊𝒕𝒊𝒐𝒏𝒂𝒍 𝒔𝒕𝒆𝒑 𝒐𝒇 𝒇𝒊𝒏𝒅𝒊𝒏𝒈 𝒕𝒉𝒆 𝒎𝒊𝒅 𝒑𝒐𝒊𝒏𝒕 𝒐𝒇 𝒕𝒉𝒆 𝒊𝒏𝒕𝒆𝒓𝒗𝒂𝒍 𝒐𝒇 𝒆𝒂𝒄𝒉 𝒄𝒍𝒂𝒔𝒔

𝒂𝒏𝒅 𝒕𝒓𝒆𝒂𝒕𝒊𝒏𝒈 𝒊𝒕 𝒂𝒔 𝒙𝒊 𝒐𝒇 𝒕𝒉𝒆 𝒈𝒓𝒐𝒖𝒑𝒆𝒅 𝒅𝒂𝒕𝒂

𝑺𝒂𝒎𝒑𝒍𝒆 𝑴𝒆𝒂𝒏: �̅� =∑ 𝒙𝒊𝒇𝒊

𝒌𝒊=𝟏

∑ 𝒇𝒊𝒌𝒊=𝟏

=∑ 𝒎𝒊𝒇𝒊

𝒌𝒊=𝟏

∑ 𝒇𝒊𝒌𝒊=𝟏

=∑ 𝒎𝒊𝒇𝒊

𝒌𝒊=𝟏

𝒏

𝑺𝒂𝒎𝒑𝒍𝒆 𝑺𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝑫𝒆𝒗𝒊𝒂𝒕𝒊𝒐𝒏

𝒔 = √∑(𝒙𝒊 − �̅�)𝟐𝒇𝒊

𝒏 − 𝟏 𝑶𝑹

𝒔 =√∑ 𝒙𝒊

𝟐𝒇𝒊 −(∑ 𝒙𝒊𝒇𝒊)𝟐

𝒏𝒏 − 𝟏

𝑺𝒂𝒎𝒑𝒍𝒆 𝑽𝒂𝒓𝒊𝒂𝒏𝒄𝒆, 𝒔𝟐, 𝒊𝒔 𝒐𝒃𝒕𝒂𝒊𝒏𝒆𝒅 𝒃𝒚 𝒔𝒒𝒖𝒂𝒓𝒊𝒏𝒈 𝒕𝒉𝒆 𝒔𝒂𝒎𝒑𝒍𝒆 𝒔𝒕𝒂𝒏𝒅𝒂𝒓𝒅 𝒅𝒆𝒗𝒊𝒂𝒕𝒊𝒐𝒏, 𝒔 © Ven M

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