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Use the built regression tool in Excel and your personalized data set (see above) to estimate the simple regression of sales revenue in dollars (

 Use the built regression tool in Excel and your personalized data set (see above) to estimate the simple regression of sales revenue in dollars (Y) generated by a telemarketer in his/her first year of completed service on the number of hours of preliminary training provided to a new telemarketer (X).

When answering the following questions, assume all the assumptions of the neoclassical (stochastic regressor) simple regression (NSR) model with multivariate normally distributed random disturbances are satisfied.

b. Clearly state your estimated conditional expectation function (sample regression line). Note that you do not need to estimate your equation manually, but rather you should simply write down your sample regression line using the estimated intercept and coefficient of X given in your summary regression output from Excel.

c. With reference to your estimated equation, calculate (using a calculator) a 90% confidence interval for the coefficient of X (i.e.β2 ) in the model. In performing this calculation, use the relevant estimated standard error of the estimator of the coefficient of X given in your summary Excel regression output. Give an interpretation of the confidence interval you calculate.

d. Again with reference to your estimated equation, perform a test of the null hypothesis that the coefficient of number of hours of preliminary training provided to a telemarketer ( β2 ) equals zero against the alternative that it is greater than zero, using the α = 0.05 (i.e. 5%) level of significance. In presenting your answer to this question you are required to use the 6-step hypothesis testing procedure given in the unit summary lecture notes. Again in answering this question, you should use the relevant estimated standard error of the estimator of the coefficient of X given in your summary Excel regression output.

e. Give an interpretation of the realized coefficient of determination value ( r 2 ) given in your summary Excel regression output.

MarketerHours of Training (x)Sales Revenue (y)
13139096
26140835
34106518
43145455
58185201
62118674
72127721
810157273
95127185
105127963
118152546
123131447
139168911
14596889
15393694
167187102
1712185469
186137039
194140491
20495291
218169404
226166281
239163856
2410188397
254110667
263109951
2712236842
289222981
295108786
307149542
316138458
323125194
338138362
346151889
357144136
363113019
3711177301
3810153225
395120787
405122330
413119693
424137296

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b The estimated conditional expectation function sample regression line can be written as Y 2500 40X ... blur-text-image

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