18. In the Low Birthweight data that you used for assignment, there were two variables bwt [child's birthweight in grams] and race_eth [race/ethnicity of mother (1-white; 2-black; 3-other)]. You are conducting an analysis to assess if mean age differs across the three race groups and have the following output. Group A Group B Label Mean Std Dev Samp Size ANOVA Table Group Residual Total Pairwise Comparison Group A B C Bonferroni Correction Number of Groups Number of Tests Type 1 Error Rate p-value Threshold SS Mean 3103.74 1 3103.74 5070607.63 94846445.01 2719.69 727.72 99917052.65 2804.01 96 SEM 186 188 74.27 125.26 88.12 df 2 2 2719.69 638.68 26 MS 2535303.82 509927.12 Group B 0.012 3 3 0.050 0.017 Group C 3 0.010 2804.01 0.584 721.30 Fstat 67 4.97 Group C p-value Mothers from all three categories of race/ethnicity have statistically significant differences in mean birthweight of their children. 0.008 Which one of the following statements is the best conclusion, assuming a Type I error rate of 0.05? The mean birthweight of children born to white mothers is statistically different from children born to non- white mothers. We cannot use the Low Birthweight dataset to examine differences in mean birthweight relative to race and ethnicity because there are not an equal number of mothers in each race/ethnicity group. A linear regression model fit to the data would produce a negative regression coefficient, suggesting there are significant differences in mean birthweight among the three race/ethnicity groups of the mothers.
18. In the Low Birthweight data that you used for assignment, there were two variables bwt [child's birthweight in grams] and race_eth [race/ethnicity of mother (1-white; 2-black; 3-other)]. You are conducting an analysis to assess if mean age differs across the three race groups and have the following output. Group A Group B Label Mean Std Dev Samp Size ANOVA Table Group Residual Total Pairwise Comparison Group A B C Bonferroni Correction Number of Groups Number of Tests Type 1 Error Rate p-value Threshold SS Mean 3103.74 1 3103.74 5070607.63 94846445.01 2719.69 727.72 99917052.65 2804.01 96 SEM 186 188 74.27 125.26 88.12 df 2 2 2719.69 638.68 26 MS 2535303.82 509927.12 Group B 0.012 3 3 0.050 0.017 Group C 3 0.010 2804.01 0.584 721.30 Fstat 67 4.97 Group C p-value Mothers from all three categories of race/ethnicity have statistically significant differences in mean birthweight of their children. 0.008 Which one of the following statements is the best conclusion, assuming a Type I error rate of 0.05? The mean birthweight of children born to white mothers is statistically different from children born to non- white mothers. We cannot use the Low Birthweight dataset to examine differences in mean birthweight relative to race and ethnicity because there are not an equal number of mothers in each race/ethnicity group. A linear regression model fit to the data would produce a negative regression coefficient, suggesting there are significant differences in mean birthweight among the three race/ethnicity groups of the mothers.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![18. In the Low Birthweight data that you used for assignment, there were two variables bwt [child's birthweight in
grams] and race_eth [race/ethnicity of mother (1-white; 2-black; 3-other)]. You are conducting an analysis to
assess if mean age differs across the three race groups and have the following output.
Group A
Group B
Label
Mean
Std Dev
Samp Size
ANOVA Table
Group
Residual
Total
Pairwise Comparison
Group
A
B
C
Number of Groups
Number of Tests
Type I Error Rate
p-value Threshold
Bonferroni Correction
SS
Mean
3103.74
1
2719.69
3103.74
5070607.63
94846445.01
2804.01
727.72
99917052.65
96
186
188
SEM
74.27
125.26
88.12
df
2
2
2719.69
638.68
26
MS
2535303.82
509927.12
Group B
0.012
3
3
0.050
0.017
Group C
3
0.010
2804.01
0.584
721.30
Fstat
67
4.97
Group C
p-value
Mothers from all three categories of race/ethnicity have statistically significant differences in mean
birthweight of their children.
0.008
Which one of the following statements is the best conclusion, assuming a Type I error rate of 0.05?
O The mean birthweight of children born to white mothers is statistically different from children born to non-
white mothers.
We cannot use the Low Birthweight dataset to examine differences in mean birthweight relative to race and
ethnicity because there are not an equal number of mothers in each race/ethnicity group.
A linear regression model fit to the data would produce a negative regression coefficient, suggesting there
are significant differences in mean birthweight among the three race/ethnicity groups of the mothers.
Training](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F55815cee-d512-430a-a622-df495154bead%2F4574372f-c958-483d-8ac4-ccd73be3017e%2Fsnapplb_processed.jpeg&w=3840&q=75)
Transcribed Image Text:18. In the Low Birthweight data that you used for assignment, there were two variables bwt [child's birthweight in
grams] and race_eth [race/ethnicity of mother (1-white; 2-black; 3-other)]. You are conducting an analysis to
assess if mean age differs across the three race groups and have the following output.
Group A
Group B
Label
Mean
Std Dev
Samp Size
ANOVA Table
Group
Residual
Total
Pairwise Comparison
Group
A
B
C
Number of Groups
Number of Tests
Type I Error Rate
p-value Threshold
Bonferroni Correction
SS
Mean
3103.74
1
2719.69
3103.74
5070607.63
94846445.01
2804.01
727.72
99917052.65
96
186
188
SEM
74.27
125.26
88.12
df
2
2
2719.69
638.68
26
MS
2535303.82
509927.12
Group B
0.012
3
3
0.050
0.017
Group C
3
0.010
2804.01
0.584
721.30
Fstat
67
4.97
Group C
p-value
Mothers from all three categories of race/ethnicity have statistically significant differences in mean
birthweight of their children.
0.008
Which one of the following statements is the best conclusion, assuming a Type I error rate of 0.05?
O The mean birthweight of children born to white mothers is statistically different from children born to non-
white mothers.
We cannot use the Low Birthweight dataset to examine differences in mean birthweight relative to race and
ethnicity because there are not an equal number of mothers in each race/ethnicity group.
A linear regression model fit to the data would produce a negative regression coefficient, suggesting there
are significant differences in mean birthweight among the three race/ethnicity groups of the mothers.
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