# A T Still University Statistics Worksheet

MGMT 650Summer 2022 Week 11 Homework Questions

(Last updated 4/3/2022)

An analyst at a local bank wonders if the age distribution of customers coming for service at his branch

Age

less than 30

30-55

56 or older

Total

In town

25

37

38

100

mall

30

48

22

100

Total

55

85

60

200

1 What is the null hypothesis if you want to check if the age patterns of customers are independent of b

2 What are the expected numbers for each cell in a 3 by 3 table if the null hypothesis is true?

Age

less than 30

30-55

56 or older

Total

In town

0

mall

0

Total

0

0

0

0

3 Use the chi square test to accept or reject the null hypothesis. What is the chi square test statistic?

4 What is the chi square critical value and how many degrees of freedom does it have? Assume alpha is

5 What do you conclude?

ng for service at his branch in town is the same as at a branch located near the mall. He selects 100 transactions at random from each bra

mers are independent of bank location?

othesis is true?

hi square test statistic?

it have? Assume alpha is .05.

sactions at random from each branch and researches the age information for the associated customer. These are the data :

These are the data :

Saeko owns a yarn shop and want to expands her color selection.

Before she expands her colors, she wants to find out if her customers prefer one brand

over another brand. Specifically, she is interested in three different types of bison yarn.

As an experiment, she randomly selected 18 different days and recorded the sales of each brand.

At the .10 significance level, can she conclude that there is a difference in preference between the brands?

Misa’s Bison Yak-et-ty-Yaks

799

Total

6)

Buffalo Yarns

776

784

873

702

795

875

640

822

812

673

893

4,828.00

4,616.00

What is the null hypothesis?

What is the alternative hypothesis?

What is the level of significance?

7)

Use Tools – Data Analysis – ANOVA:Single Factor

to find the F statistic:

8)

From the ANOVA output: What is the F value?

What is the F critical value?

9)

What is your decision?

Explain in statistical terms

799

931

794

920

731

837

5,012.00

Studies have shown that the frequency with which shoppers browse Internet retailers is related to the frequency with

respondents age and answer to the question “How many minutes do you browse online retailers per year?”

Note that this sheet includes questions 10-16

Age (X)

Time (Y)

16

17

19

22

22

22

22

28

28

28

28

30

33

34

35

35

35

36

39

39

40

42

43

44

48

50

50

51

52

54

58

59

60

420

269

315

337

243

459

414

224

381

412

576

333

551

548

626

521

562

699

643

455

666

553

459

525

559

507

612

710

378

566

652

725

695

10)

Use Data > Data Analysis > Correlation to compute the correlation checking the Labels checkbox.

11)

Use the Excel function =CORREL to compute the correlation. If answers for #1 and 2 do not agree, there is an error

12)

13)

The strength of the correlation motivates further examination.

a) Insert Scatter (X, Y) plot linked to the data on this sheet with Age on the horizontal (X) axis.

b) Add to your chart: the chart name, vertical axis label, and horizontal axis label.

c) Complete the chart by adding Trendline and checking boxes

Read directly from the chart:

a) Intercept =

b) Slope =

c) R2 =

Perform Data > Data Analysis > Regression.

14)

Highlight the Y-intercept with yellow. Highlight the X variable in blue. Highlight the R Square in orange

15)

Use Excel to predict the number of minutes spent by a 22-year old shopper. Enter = followed by the regression form

Enter the intercept and slope into the formula by clicking on the cells in the regression output with the results.

16)

Is it appropriate to use this data to predict the amount of time that an 85-year-old will spend browsing online retailers

If yes, what is the amount of time, if no, why?

t retailers is related to the frequency with which they actually purchase products and/or services online. The following data show

owse online retailers per year?”

the Labels checkbox.

#1 and 2 do not agree, there is an error.

lowing data show

17)

On this worksheet, make an XY scatter plot linked to the following data:

X

1.01

1.48

1.8

1.81

1.07

1.53

1.46

1.38

1.77

1.88

1.32

1.75

1.94

1.19

1.31

1.56

1.16

1.22

1.72

1.45

1.43

1.19

2

1.6

1.58

Y

2.8482

4.2772

4.788

5.3757

2.5252

3.0906

4.3362

3.2016

4.3542

4.8692

3.8676

3.9375

5.7424

2.4752

26.2

4.5708

2.842

2.44

5.1256

4.3355

4.2471

3.5343

5.46

3.84

3.8552

18)

Add trendline, regression equation and r squared to the plot.

Add this title. (“Scatterplot of X and Y Data”)

19)

The scatterplot reveals a point outside the point pattern. Copy the data to a new location in the worksheet. You now

Data that are more tha 1.5 IQR below Q1 or more than 1.5 IQR above Q3 are considered outliers and must be inves

It was determined that the outlying point resulted from data entry error. Remove the outlier in the copy of the data.

Make a new scatterplot linked to the cleaned data without the outlier, and add title (“Scatterplot without Outlier,”) tren

X

1.01

1.48

1.8

1.81

1.07

1.53

1.46

1.38

1.77

1.88

1.32

1.75

1.94

Y

2.8482

4.2772

4.788

5.3757

2.5252

3.0906

4.3362

3.2016

4.3542

4.8692

3.8676

3.9375

5.7424

1.19

2.4752

1.56

1.16

1.22

1.72

1.45

1.43

1.19

2

1.6

1.58

4.5708

2.842

2.44

5.1256

4.3355

4.2471

3.5343

5.46

3.84

3.8552

Compare the regression equations of the two plots. How did removal of the outlier affect the slope and R2? Explain w

20)

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