1. A researcher has asked you to re-evaluate this data below. Only, this time th
ID: 3363836 • Letter: 1
Question
1. A researcher has asked you to re-evaluate this data below. Only, this time the researcher has asked you to estimate an OLS model regressing the effect of both the effect of teacher experience and time of day on student test scores
Start by writing out, in complete sentences and using the statistical notation, the re- searcher’s hypotheses about the effect of time of day and teacher experience on student test scores.
Next, estimate, a multivariate OLS model that estimates the effect of time of day and teacher experience on student test scores. Report those results in a table that is publication quality.
Case Score Teacher Time
1
98
High Experience
Morning
2
50
High Experience
Morning
3
88
Low Experience
Morning
4
93
Low Experience
Morning
5
75
High Experience
Morning
6
90
Low Experience
Morning
7
93
High Experience
Afternoon
8
100
Low Experience
Afternoon
9
95
High Experience
Afternoon
10
98
High Experience
Afternoon
11
91
Low Experience
Afternoon
12
100
Low Experience
Afternoon
1
98
High Experience
Morning
2
50
High Experience
Morning
3
88
Low Experience
Morning
4
93
Low Experience
Morning
5
75
High Experience
Morning
6
90
Low Experience
Morning
7
93
High Experience
Afternoon
8
100
Low Experience
Afternoon
9
95
High Experience
Afternoon
10
98
High Experience
Afternoon
11
91
Low Experience
Afternoon
12
100
Low Experience
Afternoon
Explanation / Answer
First the data is convert into indicator varibles as
Regression Analysis: Score versus Teacher_High Exp, Time_Afternoon
The regression equation is
Score = 86.8 - 8.83 Teacher_High Experience + 13.8 Time_Afternoon
Predictor Coef SE Coef T P
Constant 86.750 6.205 13.98 0.000
Teacher_High Experience -8.833 7.165 -1.23 0.249
Time_Afternoon 13.833 7.165 1.93 0.086
S = 12.4100 R-Sq = 36.8% R-Sq(adj) = 22.8%
Analysis of Variance
Source DF SS MS F P
Regression 2 808.2 404.1 2.62 0.127
Residual Error 9 1386.1 154.0
Total 11 2194.2
Source DF Seq SS
Teacher_High Experience 1 234.1
Time_Afternoon 1 574.1
Unusual Observations
Teacher_High
Obs Experience Score Fit SE Fit Residual St Resid
2 1.00 50.00 77.92 6.21 -27.92 -2.60R
R denotes an observation with a large standardized residual.
The OLS model of regression equation is
Score = 86.8 - 8.83 Teacher_High Experience + 13.8 Time_Afternoon
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