Marketer Hours of Training Sales Revenue 1 3 147643 2 6 120253 3 4 88777 4 3 157183 5 8 166802 6 2 127011 7 2 140582 8 10 104909 9 5 109778 10 5 110944 11 8 117820 12 3 136171 13 9 132366 14 5 64333...




























































































































































































































MarketerHours of TrainingSales Revenue
13147643
26120253
3488777
43157183
58166802
62127011
72140582
810104909
95109778
105110944
118117820
123136171
139132366
14564333
15379541
167179653
1712127204
186114559
194139737
20471936
218143105
226158422
239124784
2410151596
25495001
263103926
2712204264
289213471
29582178
307123313
316116686
323126791
33896543
346136833
357115203
363108528
3711124951
381098837
395100181
405102495
413118540
424134944









































































































































































































SUMMARY OUTPUT
Regression Statistics
Multiple R0.319551492
R Square0.102113156
Adjusted R Square0.079665985
Standard Error30180.01209
Observations42
ANOVA
dfSSMSFSignificance F
Regression141434194594.14E+094.5490430.039125
Residual40364333251859.11E+08
Total4140576744644
CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%
Intercept102590.349311164.943779.1886132.09E-1180025.16125155.580025.16125155.5
X Variable 13592.8827241684.5464872.1328490.039125188.28736997.478188.28736997.478



  • Againwith 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
    great
    e
    r

    than

    z
    e
    ro, 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.




  • Clearlystate 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.



  • Givean interpretation of the realized coefficient of determination value ( r 2 ) given in your summary Excel regression output.

Jun 02, 2022
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