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If the F test shows an overall significance, the t test is used to determine whether each of the individual independent variables is significant.

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In simple linear regression, the F and t tests provide the same conclusion. Suppose we believe that salary (y) is related to the years of experience (x1) and the score on the programmer aptitude test (x2) by the following regression model:

Of 20 programmers is shown on the next slide. The years of experience, score on the aptitude test,Īnd corresponding annual salary ($1000s) for a sample Was related to the years of experience and the score on Regression analysis could be used to determine if salary

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The error is a normally distributed random variable reflecting the deviation between the y value and the expected value of y given byĪ software firm collected data for a sample of 20Ĭomputer programmers. The variance of, denoted by 2, is the same for all values of the independent variables. The error is a random variable with mean of zero. The estimated multiple regression equation is: , bp that are used as the point estimators of the parameters b0, b1, b2. xp is called the multiple regression equation.Ī simple random sample is used to compute sample statistics b0, b1, b2. The equation that describes how the mean value of y is related to x1, x2. , bp are the parameters.Į is a random variable called the error term. xp and an error term is called the multiple regression model.ī0, b1, b2. The equation that describes how the dependent variable y is related to the independent variables x1, x2. Multiple regressionfor Estimation and Prediction

Exponent powerpoint equation editor