A regression analysis was performed, with partial results shown below, along with various plots. In the print-out of results, the square of the correlation coefficient is labeled “Multiple R-squared”. Explain in terms specific to this analysis (i.e., not just general terms) what this R-squared tells us. Response:ln_Income Explanatory: Age Residuals: Min 1Q Median 3Q Max -0.83978. -0.28834 -0.05761 0.25615 1.09741 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 9.680077 0.158362 61.13 < 2e-16 *** samp_reg$Age 0.016778 0.003995 4.20 5.76e-05 *** --- Residual standard error: 0.4012 on 101 degrees of freedom Multiple R-squared: 0.1487, Adjusted R-squared: 0.1403 F-statistic: 17.64 on 1 and 101 DF, p-value: 5.763e-05
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
A
In the print-out of results, the square of the
- Explain in terms specific to this analysis (i.e., not just general terms) what this R-squared tells us.
Response:ln_Income
Explanatory: Age
Residuals:
Min 1Q
-0.83978. -0.28834 -0.05761 0.25615 1.09741
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.680077 0.158362 61.13 < 2e-16 ***
samp_reg$Age 0.016778 0.003995 4.20 5.76e-05 ***
---
Residual standard error: 0.4012 on 101 degrees of freedom
Multiple R-squared: 0.1487, Adjusted R-squared: 0.1403
F-statistic: 17.64 on 1 and 101 DF, p-value: 5.763e-05
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