Question

Average Joe's Gym Income Statement For the Year Ended December 31st 2013 2014 2,975,990 2,575,990 1,368,955 1,184,955 1,607,035 1,391,035 Sales Cast of Sales Gross Profit Expenses 125,490 155,490 Amortization 134,500 102,800 175,680 155,600 General and Administrative Marketing and Sales Interest Expense 96,090 76,820 295,980 255,000 315,000 Office Expense Wages and Benefits, Administration Total Operating Expenses 315,000 1,153470 1,049,980 453,565 341,055 Operating Income Gain (loses) on marketable securities Impairment los on capital assets ncome joss before taxes Provision for (benefit from) income taxes 9,800 25,475 350,855 479,040 98,239 252,616 134,131 344,909 Net Income 573,338 252,615 750,953 Opening Balance-Retained Earnings 344,909 Net Income 75,000 75,000 Dividends 1,020,862 750,953 Claing Balance-Retained Earnings BUSI 1013 Business Statsc Simple Linear Regression Example: Reed Auto Sales Reed Auto periodically has a special week-long sale. As part of the advertising campaign Reed runs one or more television commercials during the weekend preceding the sale. Data from a sample of 5 previous sales are shown: Number of Number of TV Ads (x) 1 Cars Sold (y) 14 24 2 18 1 17 27 Ey 100 y20 Ex 10 2

Answer 1

following simple linear regression model has been developed using ms-excel

y=10+5x

	x	y
	1	14
	3	24
	2	18
	1	17
	3	27
sum	10	100
mean	2	20
n	5	5
variance	0.80	22.80
cov(x,y)=	4
b=cov(x,y)/var(x)=	=4/0.8=5
a=mean(y)-b*mean(x)=	=20-5*2=10

this can be also done using ms-excel data analysis tool kit

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.936586
R Square	0.877193
Adjusted R Square	0.836257
Standard Error	2.160247
Observations	5
ANOVA
	df	SS	MS	F	Significance F
Regression	1	100	100	21.42857	0.018986
Residual	3	14	4.666667
Total	4	114
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	10	2.366432	4.225771	0.024236	2.468958	17.53104	2.468958	17.53104
X	5	1.080123	4.6291	0.018986	1.562565	8.437435	1.562565	8.437435