10. Is there a significant difference in e-mail hours per week among the same 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? 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 COLLECE 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 76 10.42 9.840 1.129 8.17 12.67 40 CRADUATE 10.957 425 5.63 7.30 100 Total 664 6.46 ANOVA Email hours per week Sum of Squares df Mean Square Sig. Between Croups 4. 911.922 7.912 .000 3647.686 Within Groups 75953.372 659 115.255 Total 79601.059 663 7000ooo
10. Is there a significant difference in e-mail hours per week among the same 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? 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 COLLECE 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 76 10.42 9.840 1.129 8.17 12.67 40 CRADUATE 10.957 425 5.63 7.30 100 Total 664 6.46 ANOVA Email hours per week Sum of Squares df Mean Square Sig. Between Croups 4. 911.922 7.912 .000 3647.686 Within Groups 75953.372 659 115.255 Total 79601.059 663 7000ooo
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Problem 1P
Related questions
Question
![CO Is there a significant difference in e-mail hours per week among the same
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?
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 COLLECE
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
CRADUATE
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.
Between Croups
911.922
7.912
.000
3647.686
4.
Within Groups
75953.372
659
115.255
Total
79601.059
663
(DEGREE) and](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc62044ee-09c3-4aa6-a714-1b979d5b8de8%2F9dedb777-4277-476d-9e61-074b26768483%2Fgdfp3lr_processed.jpeg&w=3840&q=75)
Transcribed Image Text:CO Is there a significant difference in e-mail hours per week among the same
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?
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 COLLECE
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
CRADUATE
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.
Between Croups
911.922
7.912
.000
3647.686
4.
Within Groups
75953.372
659
115.255
Total
79601.059
663
(DEGREE) and
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