Consider the following dataset obtained from a sample. 1 80 3 97 4. 92 4 102 103 8 111 10 119 10 123 11 117 13 136 (a) Compute the estimated linear regression coefficients to predict y using x values. (b) Using the estimated regression line found in the previous part, predict the value of y if x equals to 7. (c) Compute SSE, SST, and SSR. Then, also compute the resulting coefficient of determination and comment on the goodness of fit. (d) Conduct t-test to test the significance of the regression relationship with a = 0.05. (e) Conduct F-test to test the significance of the regression relationship with a = 0.05.
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.
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