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Please show the excel formulas for the below calculations: Question 14 Valley Foothills 109 82 116 161 106 163 157 112 147 222 105 137

Please show the excel formulas for the below calculations:

Question 14

Valley Foothills
109 82
116 161
106 163
157 112
147 222
105 137
173 226
153 200
137 154
110 176

BigDeal Real Estate surveyed prices per square foot in the valley and foothills of Hoke-a-mo, Utah. Based on BD'sDATA,areprices per square foot equal at =0.01?

Question 14 options:

- None of the answers match my calculation.
- The critical value is 2.977 since this is a two-tail scenario. The test statistic is 3.207. Since the test statistic > the critical value, the test statistic does lie in the area of rejection. Reject the null hypothesis. The prices per square foot are not equal at alpha = .01
- The critical value is 2.977 since this is a two-tail scenario. The test statistic is 2.239. Since the test statistic < the critical value, the test statistic does not lie in the area of rejection. Do not reject the null hypothesis. The prices per square foot are equal at alpha = .01
- The critical value is 2.977 since this is a two-tail scenario. The test statistic is 1.936. Since the test statistic < the critical value, the test statistic does not lie in the area of rejection. Do not reject the null hypothesis. The prices per square foot are equal at alpha = .01
- The critical value is 2.977 since this is a two-tail scenario. The test statistic is 1.513. Since the test statistic < the critical value, the test statistic does not lie in the area of rejection. Do not reject the null hypothesis. The prices per square foot are equal at alpha = .01
Hint for Question 14

Test H0: Valley mean = foothill mean.

Is this paired data (2 measurements dependent on the unit of observation), or data from 2 independent populations? When we do not know if the variances are equal, we assume variances are unequal.

Use Data Analysis, t-Test: Two-Sample Assuming Unequal Variances. Take care that the significance level alpha is consistent with the value given in the question and that the Labels check box is only checked if the first row of the Input Range contains variable labels. It is recommended that you include the data labels in the Input Range and check the Labels checkbox.

Excel gives critical values for both one tail P(T<=t) and two tail P(T<=t) two-tail tests. Which critical value applies in this problem?

Question 15- ANOVA-1

Ovservation Portland Houston Jacksonville
1 85 71 59
2 75 75 64
3 82 73 62
4 76 74 69
5 71 69 75
6 85 82 67

National Bearings manufactures bearings at plants located in Portland Oregon, Houston Texas, and Jacksonville Florida. To measure employee knowledge of Total Quality Management (TQM), six employees were randomly selected at each plant and tested. The test scores for these employees are given inDATA. Managers want to know if, on average, knowledge of TQM is equal across the 3 plants. Test equality of mean scores at = 0.05.

Question 15 options:

-The F value of 9 is > the F critical value of 3.682, therefore reject the equality of means. Knowledge of TQM is not equal across the 3 plants.
- The F value of 1.326 is < the F critical value of 3.682, therefore do not reject equality of means. Knowledge of TQM is equal across the 3 plants.
- The F value of 3.419 is < the F critical value of 3.682, therefore do not reject equality of means. Knowledge of TQM is equal across the 3 plants.
- The F value of 6.349 is > the F critical value of 3.682, therefore reject the equality of means. Knowledge of TQM is not equal across the 3 plants.
- None of the answers match my calculation.

Hint for Question 15

Test H0: Portland = Houston = Jacksonville at = 0.05. What Data Analysis procedure is used to test equality of three population means?

Take care to use the Labels checkbox correctly. If the Input Range includes the data labels, check the Labels checkbox. If the Input Range does not include the data labels, do not check the Labels checkbox. It is recommended that you include the data labels in the Input Range and check the Labels checkbox. Verify that the input significance level alpha is correct.

Compare the F and F crit values. What is the rule for rejecting H0: Equal means?

Question 16ANOVA - 2

To test whether the mean time to mix a batch of adhesive is the same for machines produced by four manufacturers, TiteBondMax obtainedDATAon the time (minutes) needed to mix the materials. Test whether the machines have equal mean mixing time at =0.05.

Question 16 options:

- The pvalue 0.0001 is extreme evidence that the machines are not all the same.
- The data provide weak evidence against H0: Equal means at pvalue 0.072. Equality of means remains plausible.
- The data provide insignificant evidence against H0: Equal means at pvalue 0.514. The machine are considered equal.
- The data provide strong evidence against H0: Equal means at pvalue 0.013. The mixing machines are not all equal.
- None of the answers match my calculation.
- The data provide extreme evidence against H0: Equal means at pvalue 0.001. The mixing machines are not all equal.
Hide hint for Question 16

Test H0: Equal mixing times at = 0.05. What Data Analysis procedure is used to test equality of three population means?

Take care to use the Labels checkbox correctly. If the Input Range includes the data labels, check the Labels checkbox. If the Input Range does not include the data labels, do not check the Labels checkbox. It is recommended that you include the data labels in the Input Range and check the Labels checkbox. Verify that the input significance level alpha is correct.

Compare the F and F crit values. What is the rule for rejecting H0: Equal means?

We state that the evidence against H0 is Extreme when p value < 0.001 Overwhelming when 0.001 p value < 0.01 Strong when 0.01 p value < 0.05 Weak when 0.05 p value < 0.10 Insignificant when 0.10 p value

Question 17 Pivot Table

Customer # Eye Condition Gender
1 Farsighted Male
2 Bifocals Male
3 Nearsighted Male
4 Farsighted Male
5 Nearsighted Female
6 Farsighted Male
7 Farsighted Male
8 Nearsighted Female
9 Nearsighted Male
10 Farsighted Male
11 Bifocals Male
12 Farsighted Female
13 Farsighted Male
14 Farsighted Male
15 Farsighted Male
16 Farsighted Male
17 Nearsighted Male
18 Bifocals Female
19 Farsighted Male
20 Farsighted Male
21 Farsighted Male
22 Bifocals Male
23 Farsighted Female
24 Nearsighted Male
25 Nearsighted Female
26 Bifocals Female
27 Nearsighted Female
28 Farsighted Female
29 Bifocals Male
30 Nearsighted Female
31 Farsighted Male
32 Bifocals Female
33 Farsighted Male
34 Bifocals Female
35 Bifocals Female
36 Farsighted Female
37 Bifocals Male
38 Farsighted Male
39 Bifocals Female
40 Bifocals Male
41 Farsighted Male
42 Farsighted Female
43 Bifocals Female
44 Farsighted Female
45 Farsighted Male
46 Farsighted Male
47 Bifocals Female
48 Farsighted Female
49 Farsighted Female
50 Bifocals Male
51 Nearsighted Male
52 Bifocals Female
53 Farsighted Female
54 Farsighted Female
55 Farsighted Male
56 Bifocals Female
57 Farsighted Female
58 Farsighted Male
59 Farsighted Male
60 Nearsighted Male
61 Farsighted Female
62 Nearsighted Male
63 Farsighted Female
64 Farsighted Female
65 Bifocals Female
66 Farsighted Male
67 Bifocals Male
68 Farsighted Female
69 Farsighted Male
70 Farsighted Female
71 Bifocals Female
72 Farsighted Male
73 Bifocals Female
74 Farsighted Female
75 Farsighted Female
76 Farsighted Female
77 Farsighted Female
78 Farsighted Female
79 Farsighted Female
80 Farsighted Female
81 Farsighted Female
82 Farsighted Female
83 Farsighted Female
84 Farsighted Female

To balance inventory at Otto's Optometry, customer Gender and Eye Condition were collected inDATA.Make a 2x2 pivot table withGender in rows and Eye Condition in columns. The pivot table is

Question 17 options:

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