Question

The American Association of Individual Investors (AAII) On-Line Discount Broker Survey polls members on their experiences with discount brokers. As part of the survey, members were asked to rate the quality of the speed of execution with their broker as well as provide an overall satisfaction rating for electronic trades. Possible responses (scores) were no opinion (), unsatisfied (), somewhat satisfied (), satisfied (), and very satisfied (). For each broker summary scores were computed by calculating a weighted average of the scores provided by each respondent. A portion of the survey results follow (AAII website, February , ).

Brokerage	Speed	Satisfaction
Scottrade, Inc.	3.8	3.9
Charles Schwab	2.8	2.4
Fidelity Brokerage Services	3.3	3.5
TD Ameritrade	2.8	3.2
E*Trade Financial	3.7	3.3
Vanguard Brokerage Services	3.6	3.4
USAA Brokerage Services	3.2	3.5
Thinkorswim	3.7	4.0
Wells Fargo Investments	3.0	2.8
Interactive Brokers	3.1	2.8
Zecco.com	3.7	3.6

C. Develop the least squares estimated regression equation. Enter negative value as negative number. 

Satisfaction=       +           Speed (four decimals)

D. Provide an interpretation for the slope of the estimated regression equation.

The slope of the estimated regression line is approximately                    (to  4 decimals). So, a one unit  - Select your answer -increasedecreaseItem 6 in the speed of execution rating will increase the overall satisfaction rating by approximately          points (1 decimal)

 

E. Suppose TD Ameritrade developed new software to increase their speed of execution rating. If the new software is able to increase their speed of execution rating from the current value of 2.8  to the average speed of execution rating for the other 10 brokerage firms that were surveyed, what value would you predict for the overall satisfaction rating?

 (to 3 decimals)

*Need Urgently Please**

Answer 1

using excel data analysis tool for regression,steps are:

write data>menu>data>data analysis>regression>enter required labels>ok> and following o/p is obtained

Multiple R	0.75144
R Square	0.56466
Adjusted R Square	0.41955
Standard Error	0.28710
Observations	5
ANOVA
	df	SS	MS	F	Significance F
Regression	1	0.32	0.32	3.8912	0.1431
Residual	3	0.25	0.08
Total	4	0.57
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	-2.9727	3.2737	-0.9081	0.4308	-13.391	7.446
X	1.9091	0.9678	1.9726	0.143083161	-1.171	4.989

A)

from above o/p

F-stat = 3.891

B)

at α=0.05,df=1 and 3

F-critical value=10.128 excel function: =F.INV.RT(0.05,1,3) ]

since, F-stat < critical value, Fail to reject Ho