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Regression model for the appraisal value

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Reference no: EM131069199

An investor plans to develop a regression model for the appraisal value (in thousands of dollars) of property in her city (Y) based on 5 numerical variables:

Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + β5X5 + ε

The investor would like to test whether or not the model has any significance. That is, she would like to test the hypotheses:

H0: β1 = β2 = β3 = β4 = β5 = 0

HA: not all βj are zero

A sample of 30 items are drawn and the data is used to create the prediction equation:

y^ = b0 + b1x1 + b2x2 + b3x3 + b4x4 + b5x5

The regression sum of squares (SSR) is calculated to be 384.7 and the error sum of squares (SSE) is calculated to be 549.5. An F test is conducted to test the above hypotheses.

a) Calculate the test statistic (F) for this test. Give your answer to 2 decimal places.

F = 

b) With a 99% level of confidence, the investor cancannot reject the null hypothesis

Reference no: EM131069199

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