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Correlation and Regression

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1. A computer company wants to study the relationship between the number of microcomputers in use in different areas and the number of software packages the company sells in the areas. A simple linear regression analysis of 21 geographical regions reveals the following: b0=12.43, b1= 1.076, s(b0)=13.65, s(b1)=0.083 , SSE (sum of square error) = 1,076.11, SSX (Sum of square X) = 72.641, xbar= 12,453 computers. Using this information, construct 95% confidence intervals for the regression parameters b0 and b1 .

2. Price and earning data of West Tech is given in the following table. Estimate the regression equation.

Price (Y) 20 23 25 27 23
Earning (X) 0.54 0.56 0.65 0.76 0.5

Estimate the correlation coefficient of Price and Earning using the above data. At .05 level of significance, test the null hypothesis that the population correlation coefficient is 0.

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Constructs 95% confidence intervals for the regression parameters b0 and b1 and tests the null hypothesis that the population correlation coefficient is 0.

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