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The data below are the temperatures on randomly chosen days during the summer and the number of employee absences at a local company on those days.
Temperature: Number of absences
72 3
85 7
91 10
90 10
88 8
98 15
75 4
100 15
80 5
(a) Find the least square regression line. Round slope and y-intercept nearest hundredth.
(b) Predict the number of absences when temperature is 88.
(c) Find the residual when temperature is 98. Analyze the result.
(b) Test the claim, at the α = 0.05 level of significance, that a linear relation exists between the temperature and number of absences. Apply classical approach and p-value approach.
(c) Find 95 % confidence interval about the slope fo the true least-square regression line. Interpret the result.
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