Question

Using Excel:

Regression Statistics
Multiple R	0.9021
R- Square	0.8138
Adjusted R Square	0.7828
Standard Error	9.4006
ANOVA
	df	SS	MS	F
Regression	1	2317.6	2317.6	26.226
Residual	6	530.23	88.372
Total	7	2847.9
	Coefficients	Standard Error	t Stat	P-value
Intercept	45.897	5.5447	8.2776	0.0002
Number of Surgeries (x)	5.1951	1.0144	5.1211	0.0022

1. r = 0.90 strong positive correlation 2. y = 5.195 x + 45.897 , 3. r² = 0.8138 , and 4. S_e =  9.4006

5. Results of the Pearson correlation indicated that there was a significant positive association between age and number and surgeries with r = 0.90 . The results of the regression indicated the predictor explained 81% of the variance (R² =0.81, F(1,6)= 26.2, p < 0.01).

Exercise 1: Use the sample data below to answer the following question(s). The paired data consist of the cost of regionally advertising (in thousands of dollars) a certain pharmaceutical drug and the number of new prescriptions written (in thousands).

Cost	9	2	3	4	2	5	9	10
Number	85	52	55	68	67	86	83	73

1. Find the value of the linear correlation coefficient r.
2. Find the equation of the regression line, letting Number of Surgeries be the independent (x) variable.
3. Find the coefficient of determination.
4. Find the standard error of estimate s_e.
5. Report the result in APA format

Answer 1

we will solve it by using excel and the steps are

Enter the Data into excel

Click on Data tab

Click on Data Analysis

Select Regression

Select input Y Range as Range of dependent variable.

Select Input X Range as Range of independent variable

click on labels if your selecting data with labels

click on ok.

So this is the output of Regression in Excel.

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.7077
R Square	0.5009
Adjusted R Square	0.4177
Standard Error	2.5473
Observations	8.0000
ANOVA
	df	SS	MS	F	Significance F
Regression	1.0000	39.0678	39.0678	6.0209	0.0495
Residual	6.0000	38.9322	6.4887
Total	7.0000	78.0000
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-7.2756	5.2839	-1.3769	0.2177	-20.2048	5.6536	-20.2048	5.6536
Number	0.1796	0.0732	2.4538	0.0495	0.0005	0.3587	0.0005	0.3587

1)the value of the linear correlation coefficient r = 0.7077

2) the equation of the regression line, letting Number of Surgeries be the independent (x) variable

Cost = -7.2756+0.1796Number of Surgeries

3)t he coefficient of determination.

R-square = 0.5009

4)

the standard error of estimate se = 2.5473