sample size be 45. This data file contains a measure of school academic performance as well as other attributes of the elementary schools, such as, class size, enrollment, poverty, etc. Let's dive right in and perform a regression analysis using the variables api00, acs_k3, meals and full. Fit the regression model and get the following SAS output. The following are the outputs from SAS. Analysis of Variance

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Using the California Department of Education's API 2000 dataset with
sample size be 45. This data file contains a measure of school academic
performance as well as other attributes of the elementary schools, such
as, class size, enrollment, poverty, etc. Let's dive right in and perform a
regression analysis using the variables api00, acs_k3, meals and full. Fit
the regression model and get the following SAS output.
The following are the outputs from SAS.
Source
Model
Error
Corrected Total
Variable
Intercept
acs_k3
meals
full
Label
DF
3
a
b
Intercept
avg class size k-3
pct free meals.
pct full credential
Sum of
Squares
DF
Analysis of Variance
1
1
1
1
с
1271
e
Mean
Square
875
d
Parameter Estimates
Parameter
Estimate
875.05923
-2.50651
-3.31802
0.12031
Answer the question using the SAS output.
F Value
f
Standard
Error
31.03465
1.59469
0.23408
0.12072
Pr > F
g
t Value
32.08
-1.92
-24.04
1.20
Pr > |t|
<.0001
0.0553
<.0001
0.2321
Transcribed Image Text:Using the California Department of Education's API 2000 dataset with sample size be 45. This data file contains a measure of school academic performance as well as other attributes of the elementary schools, such as, class size, enrollment, poverty, etc. Let's dive right in and perform a regression analysis using the variables api00, acs_k3, meals and full. Fit the regression model and get the following SAS output. The following are the outputs from SAS. Source Model Error Corrected Total Variable Intercept acs_k3 meals full Label DF 3 a b Intercept avg class size k-3 pct free meals. pct full credential Sum of Squares DF Analysis of Variance 1 1 1 1 с 1271 e Mean Square 875 d Parameter Estimates Parameter Estimate 875.05923 -2.50651 -3.31802 0.12031 Answer the question using the SAS output. F Value f Standard Error 31.03465 1.59469 0.23408 0.12072 Pr > F g t Value 32.08 -1.92 -24.04 1.20 Pr > |t| <.0001 0.0553 <.0001 0.2321
(a) Please write down the estimated linear model for this data.
(b) Above is a partial ANOVA Table from fitting this model. Find the missing
values a, b, c, d, e, f and g.
(c) State the null and alternative hypothesis of the overall F test.
(d) Based on the output, please draw conclusion for the above test.
(e) Calculate R^2 based on the ANOVA table.
Transcribed Image Text:(a) Please write down the estimated linear model for this data. (b) Above is a partial ANOVA Table from fitting this model. Find the missing values a, b, c, d, e, f and g. (c) State the null and alternative hypothesis of the overall F test. (d) Based on the output, please draw conclusion for the above test. (e) Calculate R^2 based on the ANOVA table.
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