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 15 3 79541 16 7 179653 17 12 127204 18 6 114559 19 4 139737 20 4 71936 21 8 143105 22 6 158422 23 9 124784 24 10 151596 25 4 95001 26 3 103926 27 12 204264 28 9 213471 29 5 82178 30 7 123313 31 6 116686 32 3 126791 33 8 96543 34 6 136833 35 7 115203 36 3 108528 37 11 124951 38 10 98837 39 5 100181 40 5 102495 41 3 118540 42 4 134944 SUMMARY OUTPUT Regression Statistics Multiple R 0.319551492 R Square 0.102113156 Adjusted R Square 0.079665985 Standard Error 30180.01209 Observations 42 ANOVA df SS MS F Significance F Regression 1 4143419459 4.14E+09 4.549043 0.039125 Residual 40 36433325185 9.11E+08 Total 41 40576744644 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 102590.3493 11164.94377 9.188613 2.09E-11 80025.16 125155.5 80025.16 125155.5 X Variable 1 3592.882724 1684.546487 2.132849 0.039125 188.2873 6997.478 188.2873 6997.478 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 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. 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.

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 15 3 79541 16 7 179653 17 12 127204 18 6 114559 19 4 139737 20 4 71936 21 8 143105 22 6 158422 23 9 124784 24 10 151596 25 4 95001 26 3 103926 27 12 204264 28 9 213471 29 5 82178 30 7 123313 31 6 116686 32 3 126791 33 8 96543 34 6 136833 35 7 115203 36 3 108528 37 11 124951 38 10 98837 39 5 100181 40 5 102495 41 3 118540 42 4 134944 SUMMARY OUTPUT Regression Statistics Multiple R 0.319551492 R Square 0.102113156 Adjusted R Square 0.079665985 Standard Error 30180.01209 Observations 42 ANOVA df SS MS F Significance F Regression 1 4143419459 4.14E+09 4.549043 0.039125 Residual 40 36433325185 9.11E+08 Total 41 40576744644 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 102590.3493 11164.94377 9.188613 2.09E-11 80025.16 125155.5 80025.16 125155.5 X Variable 1 3592.882724 1684.546487 2.132849 0.039125 188.2873 6997.478 188.2873 6997.478 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 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. 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.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Related questions

Question

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
15	3	79541
16	7	179653
17	12	127204
18	6	114559
19	4	139737
20	4	71936
21	8	143105
22	6	158422
23	9	124784
24	10	151596
25	4	95001
26	3	103926
27	12	204264
28	9	213471
29	5	82178
30	7	123313
31	6	116686
32	3	126791
33	8	96543
34	6	136833
35	7	115203
36	3	108528
37	11	124951
38	10	98837
39	5	100181
40	5	102495
41	3	118540
42	4	134944

SUMMARY OUTPUT

Regression Statistics
Multiple R	0.319551492
R Square	0.102113156
Adjusted R Square	0.079665985
Standard Error	30180.01209
Observations	42

ANOVA
	df	SS	MS	F	Significance F
Regression	1	4143419459	4.14E+09	4.549043	0.039125
Residual	40	36433325185	9.11E+08
Total	41	40576744644

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	102590.3493	11164.94377	9.188613	2.09E-11	80025.16	125155.5	80025.16	125155.5
X Variable 1	3592.882724	1684.546487	2.132849	0.039125	188.2873	6997.478	188.2873	6997.478

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 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.

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.

Expert Solution

Trending now

This is a popular solution!

Step by step

Solved in 2 steps

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

$Anova and Design of Experiments$

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.