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The data given below gives annual income (

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Answer #1

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2 4 17.64 11.56 24.01 43.56 34.81 23.04 7.84 26.01 73.96 121 256 196 676 2025 1024 576 324 625 2500 16 14 26 45 32 24 18 25 50 67.2 47.6 127.4 297 188.8 115.2 50.4 127.5 430 3.4 4.9 6.6 5.9 4.8 2.8 5.1 8.6 Σ' 48.3 x4.83 x 261 ry-1473.1 T= 26.1 10x1473.1-261x48.3 10x 8323-2612 2124.7 15109 0.141 -4.83-0.141x 26.1 -1.160 Therefore, the regression equation is: v 1.160+0.141x,

10 9 y=0. 141x + 1.160 30 10 20 40 50 60

The slope of the regression equation (0.141) is interpreted as for 1000 dollars increase in annual family income, the expenditure on entertainment and recreation is expected to increase by 141 dollars.

The intercept of the regression equation (1.160) is interpreted the expected value of the expenditure on entertainment and recreation is 1160 dollars when annual family income is 0.

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Answer 1

Solution:

2 4 17.64 11.56 24.01 43.56 34.81 23.04 7.84 26.01 73.96 121 256 196 676 2025 1024 576 324 625 2500 16 14 26 45 32 24 18 25 50 67.2 47.6 127.4 297 188.8 115.2 50.4 127.5 430 3.4 4.9 6.6 5.9 4.8 2.8 5.1 8.6 Σ' 48.3 x4.83 x 261 ry-1473.1 T= 26.1 10x1473.1-261x48.3 10x 8323-2612 2124.7 15109 0.141 -4.83-0.141x 26.1 -1.160 Therefore, the regression equation is: v 1.160+0.141x,

10 9 y=0. 141x + 1.160 30 10 20 40 50 60

The slope of the regression equation (0.141) is interpreted as for 1000 dollars increase in annual family income, the expenditure on entertainment and recreation is expected to increase by 141 dollars.

The intercept of the regression equation (1.160) is interpreted the expected value of the expenditure on entertainment and recreation is 1160 dollars when annual family income is 0.