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To test if shift work leads to increase in caloric intake, a dietician had 20 of her clients record the amount of calories they consumed during the day. She believed those who work at night consumed more calories.  The data below are in hundreds of calories.  Is there a significant difference among the caloric inputs?         DAY         NIGHT BOYS: 44           42           45           41           41           41           39           36           40           36   GIRLS: 48          60            49           52            47           52            53            42             52          60   Using α=.05 and the SPSS output below.  What is the critical value of F ? What is the obtained value of the interaction F=? Are any of the main effects significant?  If so, which ones

To test if shift work leads to increase in caloric intake, a dietician had 20 of her clients record the amount of calories they consumed during the day. She believed those who work at night consumed more calories.  The data below are in hundreds of calories.  Is there a significant difference among the caloric inputs?         DAY         NIGHT BOYS: 44           42           45           41           41           41           39           36           40           36   GIRLS: 48          60            49           52            47           52            53            42             52          60   Using α=.05 and the SPSS output below.  What is the critical value of F ? What is the obtained value of the interaction F=? Are any of the main effects significant?  If so, which ones

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.4: Distributions Of Data
Problem 19PFA
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To test if shift work leads to increase in caloric intake, a dietician had 20 of her clients record the amount of calories they consumed during the day. She believed those who work at night consumed more calories.  The data below are in hundreds of calories.  Is there a significant difference among the caloric inputs? 

       DAY         NIGHT

BOYS: 44           42

          45           41

          41           41

          39           36

          40           36

 

GIRLS: 48          60

           49           52

           47           52

           53            42

            52          60

 

Using α=.05 and the SPSS output below. 

What is the critical value of F ?

What is the obtained value of the interaction F=?

Are any of the main effects significant?  If so, which ones 

Gender Descriptive Statistic Dependent Variable: calories Gender day_night| Mean Std. Deviation N 1.00 1.00 2.00 53.2000 7.429670 5 39.2000 2.949580 5 Total 46.2000 9.101890 10 2.588440 1.00 2.00 2.00 49.8000 5 53.2000 7.429670 5 Total 51.5000 5.542760 10 Total 1.00 2.00 51.5000 46.2000 5.542760 10 9.101890 10 Total 48.8500 7.82220 20 Levene's Test of Equality of Error Variances" Levene Statistic df1 df2 Sig calories Based on Mean 1.688 3 16 210 Based on Median 1.155 3 16 .358 Based on Median and 1.155 3 10.966 |.371 with adjusted df Based on trimmed mean 1.80 3 16.188 Tests the null hypothesis that the error variance of the dependent variable is equal across groups, a. Dependent variable: calories b. Design: Intercept + Gender + day_night + Gender * day_night Tests of Between-Subjects Effects Dependent Variable: calories Туре III Sum of Squares 659.350* Partial Eta Source df Mean Square Sig. 6.988 .003 F Squared Corrected Model 219.783 567 47726.450 47726.450 1517.534 .000 Intercept Gender day night Gender * day_night .990 140.450 140.450 4.466.051 .218 140.450 140.450 4.466 .051 218 378.450 378.450 12.033 .003 .429 Error 503.200 16 31.450 Total 48889.000 20 Corrected Total 1162.550 19 Tests of Between-Subjects Effects Dependent Variable: calories Source Noncent. Parameter Observed Power Corrected Model 20.965 .939 1.000 510 Intercept 1517.534 Gender 4.466 Day night Gender day night 4.466 510 12.033 902 Error Total Corrected Total a. R Squared = .567 (Adjusted R Squared = 486) b. Computed using alpha = .05
Transcribed Image Text:Gender Descriptive Statistic Dependent Variable: calories Gender day_night| Mean Std. Deviation N 1.00 1.00 2.00 53.2000 7.429670 5 39.2000 2.949580 5 Total 46.2000 9.101890 10 2.588440 1.00 2.00 2.00 49.8000 5 53.2000 7.429670 5 Total 51.5000 5.542760 10 Total 1.00 2.00 51.5000 46.2000 5.542760 10 9.101890 10 Total 48.8500 7.82220 20 Levene's Test of Equality of Error Variances" Levene Statistic df1 df2 Sig calories Based on Mean 1.688 3 16 210 Based on Median 1.155 3 16 .358 Based on Median and 1.155 3 10.966 |.371 with adjusted df Based on trimmed mean 1.80 3 16.188 Tests the null hypothesis that the error variance of the dependent variable is equal across groups, a. Dependent variable: calories b. Design: Intercept + Gender + day_night + Gender * day_night Tests of Between-Subjects Effects Dependent Variable: calories Туре III Sum of Squares 659.350* Partial Eta Source df Mean Square Sig. 6.988 .003 F Squared Corrected Model 219.783 567 47726.450 47726.450 1517.534 .000 Intercept Gender day night Gender * day_night .990 140.450 140.450 4.466.051 .218 140.450 140.450 4.466 .051 218 378.450 378.450 12.033 .003 .429 Error 503.200 16 31.450 Total 48889.000 20 Corrected Total 1162.550 19 Tests of Between-Subjects Effects Dependent Variable: calories Source Noncent. Parameter Observed Power Corrected Model 20.965 .939 1.000 510 Intercept 1517.534 Gender 4.466 Day night Gender day night 4.466 510 12.033 902 Error Total Corrected Total a. R Squared = .567 (Adjusted R Squared = 486) b. Computed using alpha = .05
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