Please help to find some data with at least 100 cases that to run a simple regre
ID: 2921587 • Letter: P
Question
Please help to find some data with at least 100 cases that to run a simple regression into the Spss software firstly, and making the SPSS output tables as a screen shot. Then use to answer questions by typed in detailly. Thank you so much!(please to answer all the 4 question by typed in detailly, and show the SPSS output table, please)
Questions:
1. Describe the variables. What are they? How are they coded?(detailly)
2. What is your prediction of the relationship between these variables? What do you expect to see?(detailly)
3. Compute and report the regression equation. What is the equation? Was your prediction supported? How much variance was explained?(detailly)
4. What are the practical implications of this relationship? If you collected additional data, do you think the relationship would replicate? Why or why not?(detailly)
Explanation / Answer
1. Describe the variables. What are they? How are they coded?(detailly)
Answer:
For this study, we choose two correlated variables such as number of study hours during test and test score. As we know that the score of test depends on the study time. Here, we consider the dependent variable or response variable as test score and independent variable or explanatory variable as the number of study hours. For the given two variables we use ratio scale of measurement. Numbers are coded as the nearest integers and no fractional number consider for the given two variables.
2. What is your prediction of the relationship between these variables? What do you expect to see?(detailly)
Answer:
We predict that there would be a strong positive linear relationship or association exists between the two variables number of study hours and test score. We expect to see the strong positive correlation between the dependent variable and independent variable.
3. Compute and report the regression equation. What is the equation? Was your prediction supported? How much variance was explained?(detailly)
Answer:
The required regression equation is given as below:
Test score = -4.961 + 9.986*Number of study hours
Y = -4.961 + 9.986*X
From the given regression output, our prediction is supported. The correlation coefficient between the given two variables is given as 0.993 which indicate a strong positive linear relationship or association exists between the two variables number of study hours and test score. The coefficient of determination or the value of R square is given as 0.986, which means about 98.6% of the variance or variation in the dependent variable test score is explained by the regression or independent variable number of study hours.
Regression
Descriptive Statistics
Mean
Std. Deviation
N
Test score
44.1700
23.02965
100
Number of study hours
4.9200
2.29043
100
Correlations
Test score
Number of study hours
Pearson Correlation
Test score
1.000
.993
Number of study hours
.993
1.000
Sig. (1-tailed)
Test score
.
.000
Number of study hours
.000
.
N
Test score
100
100
Number of study hours
100
100
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.993a
.986
.986
2.70074
a. Predictors: (Constant), Number of study hours
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
51791.301
1
51791.301
7100.564
.000a
Residual
714.809
98
7.294
Total
52506.110
99
a. Predictors: (Constant), Number of study hours
b. Dependent Variable: Test score
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
-4.961
.643
-7.721
.000
Number of study hours
9.986
.119
.993
84.265
.000
a. Dependent Variable: Test score
4. What are the practical implications of this relationship? If you collected additional data, do you think the relationship would replicate? Why or why not?(detailly)
Answer:
Practically, we know that there is a relationship exists between the total time spend for study and test score. There would be some exceptional cases. Practically, this relationship indicates that if we need more test score, then we need to spend more time for study. If we collected additional data or completely new data, the relationship would be replicate and there would be no significant difference between the correlation coefficients; because a sample result always implies the population parameters.
Descriptive Statistics
Mean
Std. Deviation
N
Test score
44.1700
23.02965
100
Number of study hours
4.9200
2.29043
100
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