The personnel director for Electronics Associates developed the following estimated regression equation relating an employee's score on a job satisfaction test to length of service and wage rate. ŷ = 14.4 − 8.69x1 + 13.52x2 where x1  =  length of service (years) x2  =  wage rate (dollars) y  =  job satisfaction test score (higher scores indicate greater job satisfaction).     #1) Find the value of the test statistic. (Round your answer to two decimal places.) F = Find the p-value. (Round your answer to three decimal places.) p-value =   #2)Did the estimated regression equation provide a good fit to the data? Explain. (Round your answers to two decimal places.) Since R2 =   Ra2 =    #3) Find the value of the test statistic for ?2. (Round your answer to two decimal places.) Find the p-value. (Round your answer to three decimal places.) p-value =

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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.