Following output for the multiple regression problem shows results as results. SUMMARY OUTPUT Regression Statistics Multiple R 0.70955 R Square 0.503461 Adjusted R Square 0.410359 Standard Error 2.130054 Observations 20 ANOVA df SS MS F Significance F Regression 3 73.60593 24.53531 5.40767 0.0092117 Residual 16 72.59407 4.537129 Total 19 146.2 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 48.63081 6.3247384 7.688984 9.2E-07 35.222968 62.038661 Price of Coke -0.3035 0.1711745 -1.77307 0.09525 -0.6663779 0.0593694 Ad Expenditure 0.342937 0.1655882 2.071021 0.05489 -0.0080947 0.6939678 Pepsi Price 0.23406 0.1393504 1.679653 0.11244 -0.0613493 0.5294699 Find and Interpret Adjusted Coefficient of Determination, Adjusted R2, and the Correlation Coefficient, R. The ANOVA table gives the F statistic for testing the claim that there is no significant relationship between your all of your independent and dependent variables. The sig. value is your p value. Using p-value decide you should Reject or Accept claim. Write the Fitted Regression line from the results? Decide about significance using the p-value. Following output for the multiple regression problem shows results as results. SUMMARY OUTPUT Regression Statistics Multiple R 0.70955 R Square 0.503461 Adjusted R Square 0.410359 Standard Error 2.130054 Observations 20 ANOVA df SS MS F Significance F Regression 3 73.60593 24.53531 5.40767 0.0092117 Residual 16 72.59407 4.537129 Total 19 146.2 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 48.63081 6.3247384 7.688984 9.2E-07 35.222968 62.038661 Price of Coke -0.3035 0.1711745 -1.77307 0.09525 -0.6663779 0.0593694 Ad Expenditure 0.342937 0.1655882 2.071021 0.05489 -0.0080947 0.6939678 Pepsi Price 0.23406 0.1393504 1.679653 0.11244 -0.0613493 0.5294699 Find and Interpret Adjusted Coefficient of Determination, Adjusted R2, and the Correlation Coefficient, R. The ANOVA table gives the F statistic for testing the claim that there is no significant relationship between your all of your independent and dependent variables. The sig. value is your p value. Using p-value decide you should Reject or Accept claim. Write the Fitted Regression line from the results? Decide about significance using the p-value.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Following output for the multiple regression problem shows results as results.
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SUMMARY OUTPUT |
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Regression Statistics |
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Multiple R |
0.70955 |
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R Square |
0.503461 |
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Adjusted R Square |
0.410359 |
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Standard Error |
2.130054 |
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Observations |
20 |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
3 |
73.60593 |
24.53531 |
5.40767 |
0.0092117 |
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Residual |
16 |
72.59407 |
4.537129 |
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Total |
19 |
146.2 |
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Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
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Intercept |
48.63081 |
6.3247384 |
7.688984 |
9.2E-07 |
35.222968 |
62.038661 |
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Price of Coke |
-0.3035 |
0.1711745 |
-1.77307 |
0.09525 |
-0.6663779 |
0.0593694 |
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Ad Expenditure |
0.342937 |
0.1655882 |
2.071021 |
0.05489 |
-0.0080947 |
0.6939678 |
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Pepsi Price |
0.23406 |
0.1393504 |
1.679653 |
0.11244 |
-0.0613493 |
0.5294699 |
- Find and Interpret Adjusted Coefficient of Determination, Adjusted R2, and the
Correlation Coefficient , R. - The ANOVA table gives the F statistic for testing the claim that there is no significant relationship between your all of your independent and dependent variables. The sig. value is your p value. Using p-value decide you should Reject or Accept claim.
- Write the Fitted Regression line from the results?
- Decide about significance using the p-value.
Following output for the multiple regression problem shows results as results.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.70955
R Square
0.503461
Adjusted R Square
0.410359
Standard Error
2.130054
Observations
20
ANOVA
df
SS
MS
F
Significance F
Regression
3
73.60593
24.53531
5.40767
0.0092117
Residual
16
72.59407
4.537129
Total
19
146.2
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
48.63081
6.3247384
7.688984
9.2E-07
35.222968
62.038661
Price of Coke
-0.3035
0.1711745
-1.77307
0.09525
-0.6663779
0.0593694
Ad Expenditure
0.342937
0.1655882
2.071021
0.05489
-0.0080947
0.6939678
Pepsi Price
0.23406
0.1393504
1.679653
0.11244
-0.0613493
0.5294699
- Find and Interpret Adjusted Coefficient of Determination, Adjusted R2, and the Correlation Coefficient, R.
- The ANOVA table gives the F statistic for testing the claim that there is no significant relationship between your all of your independent and dependent variables. The sig. value is your p value. Using p-value decide you should Reject or Accept claim.
- Write the Fitted Regression line from the results?
- Decide about significance using the p-value.
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