Knowing the number of hours the student studied for the exam, can you predict their post-test scores?Select the appropriate statistical test, state the null and alternative hypotheses, determine the correct criterion for testing the hypothesis, and obtain the correct statistics. Solved by hand. Regression[DataSet0]Variables Entered/RemovedVariablesVariablesModelEnteredRemovedMethodxbEntera. Dependent Variable: yb. All requested variables entered.Model SummaryAdjusted RSquareStd. Error ofModelRR Squarethe Estimate1.483.233.1851.41875a. Predictors: (Constant), x ANOVASum ofModelSquaresdfMean SquareFSig.1Regression9.79519.7954.866.042bResidual32.205162.013Total42.00017a. Dependent Variable: yb. Predictors: (Constant), xCoefficientsStandardizedUnstandardized CoefficientsCoefficientsModelBStd. ErrorBetatSig.1(Constant)2.2461.4391.561.138.288.131.4832.206.042a. Dependent Variable: y

Name: Knowing the number of hours the student studied for the exam, can you
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Description: Knowing the number of hours the student studied for the exam, can you predict their post-test scores?Select the appropriate statistical test, state the null and alternative hypotheses, determine the correct criterion for testing the hypothesis, and o

For the given Results, we can state hypothesis as, Null hypothesis, Ho: there is no relationship…

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MATLAB: An Introduction with Applications

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Knowing the number of hours the student studied for the exam, can you predict their post-test scores?

Select the appropriate statistical test, state the null and alternative hypotheses, determine the correct criterion for testing the hypothesis, and obtain the correct statistics. Solved by hand.

Regression
[DataSet0]
Variables Entered/Removed
Variables
Variables
Model
Entered
Removed
Method
xb
Enter
a. Dependent Variable: y
b. All requested variables entered.
Model Summary
Adjusted R
Square
Std. Error of
Model
R
R Square
the Estimate
1
.483
.233
.185
1.41875
a. Predictors: (Constant), x

ANOVA
Sum of
Model
Squares
df
Mean Square
F
Sig.
1
Regression
9.795
1
9.795
4.866
.042b
Residual
32.205
16
2.013
Total
42.000
17
a. Dependent Variable: y
b. Predictors: (Constant), x
Coefficients
Standardized
Unstandardized Coefficients
Coefficients
Model
B
Std. Error
Beta
t
Sig.
1
(Constant)
2.246
1.439
1.561
.138
.288
.131
.483
2.206
.042
a. Dependent Variable: y

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