The following results are from data concerning the amount withdrawn from an ATM machine based on the amount of time spent at the ATM machine (SECONDS) and the gender, FEMALE (dummy variable = 1 for females and = 0 for males) and an interaction term, SECONDS*FEMALE SUMMARY OUTPUT Regression Statistics Multiple R 0.503 R Square Adjusted R Square Standard Error Observations 50 ANOVA df SS MS F Significance F Regression 2728.7 5.19 0.004 Residual 24161.8 525.3 Total 32348 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 130.5 23.51 5.89 0 91.03 185.67 Seconds -1.99 0.676 0.002 -3.401 -0.839 Female -69.3 31.3 -2.26 -137.33 -8.07 Seconds*Female 2 0.89 2.8 0.007 0.67 Based on the regression results, what is the predicted amount withdrawn for a male who spends 29 at the ATM machine? (please express your answer using 1 decimal places)
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.
QUESTION 16 STATS
- The following results are from data concerning the amount withdrawn from an ATM machine based on the amount of time spent at the ATM machine (SECONDS) and the gender, FEMALE (dummy variable = 1 for females and = 0 for males) and an interaction term, SECONDS*FEMALE
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SUMMARY OUTPUT |
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Regression Statistics |
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Multiple R |
0.503 |
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R Square |
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Adjusted R Square |
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Standard Error |
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Observations |
50 |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
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2728.7 |
5.19 |
0.004 |
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Residual |
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24161.8 |
525.3 |
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Total |
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32348 |
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Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
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Intercept |
130.5 |
23.51 |
5.89 |
0 |
91.03 |
185.67 |
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Seconds |
-1.99 |
0.676 |
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0.002 |
-3.401 |
-0.839 |
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Female |
-69.3 |
31.3 |
-2.26 |
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-137.33 |
-8.07 |
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Seconds*Female |
2 |
0.89 |
2.8 |
0.007 |
0.67 |
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Based on the regression results, what is the predicted amount withdrawn for a male who spends 29 at the ATM machine? (please express your answer using 1 decimal places)
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