onsider the coefficient estimates of the following market model linear regression of general motors (gm) on the S&P500 market returns coefficient estimate std error tvalue pr(>ItI) intercept 0.005860 0.0003704 1.582 0.12412 sp500 0.0904753 0.266702 3.392 0.00196
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.
consider the coefficient estimates of the following market model linear regression of general motors (gm) on the S&P500 market returns
coefficient
| estimate | std error | tvalue | pr(>ItI) | |
| intercept | 0.005860 | 0.0003704 | 1.582 | 0.12412 |
| sp500 | 0.0904753 | 0.266702 | 3.392 | 0.00196 |
The number of observations is 32.At the 1% significance level, what is the (1)test statistic value,(2) the critical values (3) decision regarding the null hypothesis that the beta coefficient on the market returns is equal to 1.61
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