C10. Is there a significant difference in e-mail hours educational groups? Using data from the GSS 2018. we ran an ANOVA model using DEGREE (educational attainment) as the independent variable and EMAILHR (e-mail hours per week) as the dependent variable. Based on an alpha of .05, what per week among the same do you conclude? Descriptives Email hours per week 95% Confidence Interval for Mean Std. Deviation Mean Std. Error Lower Bound Upper Bound Minimum Maximum LT HIGH SCHOOL 68 3.63 10.117 1.227 1.18 6.08 70 HIGH SCHOOL 328 5.05 10.378 .573 3.92 6.18 100 JUNIOR COLLEGE 68 5.93 10.722 1.300 3.33 8.52 70 BACHELOR 124 9.62 12.399 1.113 7.42 11.82 60 GRADUATE 76 10.42 9.840 1.129 8.17 12.67 40 664 6.46 10.957 .425 5.63 7.30 100 Total ANOVA Email hours per week Sum of Squares df Mean Square Sig. 911.922 7.912 .000 4 Between Groups 3647.686 659 115.255 Within Groups 75953.372 663 Total 79601.059

C10. Is there a significant difference in e-mail hours educational groups? Using data from the GSS 2018. we ran an ANOVA model using DEGREE (educational attainment) as the independent variable and EMAILHR (e-mail hours per week) as the dependent variable. Based on an alpha of .05, what per week among the same do you conclude? Descriptives Email hours per week 95% Confidence Interval for Mean Std. Deviation Mean Std. Error Lower Bound Upper Bound Minimum Maximum LT HIGH SCHOOL 68 3.63 10.117 1.227 1.18 6.08 70 HIGH SCHOOL 328 5.05 10.378 .573 3.92 6.18 100 JUNIOR COLLEGE 68 5.93 10.722 1.300 3.33 8.52 70 BACHELOR 124 9.62 12.399 1.113 7.42 11.82 60 GRADUATE 76 10.42 9.840 1.129 8.17 12.67 40 664 6.46 10.957 .425 5.63 7.30 100 Total ANOVA Email hours per week Sum of Squares df Mean Square Sig. 911.922 7.912 .000 4 Between Groups 3647.686 659 115.255 Within Groups 75953.372 663 Total 79601.059

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Description: C10. Is there a significant difference in e-mail hourseducational groups? Using data from the GSS 2018, we ran an ANOVA model usingDEGREE (educational attainment) as the independent variable and EMAILHR(e-mail hours per week) as the dependent variab

MATLAB: An Introduction with Applications

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Author:Amos Gilat

Publisher:Amos Gilat

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2-Proportion Test

In a 2-proportion test, two separate proportions are measured at the same time, and their similarity is evaluated. It is also known as a 2-proportion z-test, and a comparison of two different proportions is done in this method.

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Question

C10. Is there a significant difference in e-mail hours
educational groups? Using data from the GSS 2018, we ran an ANOVA model using
DEGREE (educational attainment) as the independent variable and EMAILHR
(e-mail hours per week) as the dependent variable. Based on an alpha of .05, what
do you conclude?
per
week
among
the same
Descriptives
Email hours per week
95% Confidence Interval for
Mean
Std.
Deviation
Mean
Std. Error
Lower Bound
Upper Bound
Minimum
Maximum
LT HIGH SCHOOL
68
3.63
10.117
1.227
1.18
6.08
70
HIGH SCHOOL
328
5.05
10.378
.573
3.92
6.18
100
JUNIOR COLLEGE
68
5.93
10.722
1.300
3.33
8.52
70
BACHELOR
124
9.62
12.399
1.113
7.42
11.82
60
GRADUATE
76
10.42
9.840
1.129
8.17
12.67
40
Total
664
6.46
10.957
.425
5.63
7.30
100
ANOVA
Email hours per week
Sum of
Squares
df
Mean Square
F
Sig.
911.922
7.912
.000
4
Between Groups
3647.686
659
115.255
Within Groups
75953.372
663
Total
79601.059

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