# 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)
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
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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