Question

Pass attempts data for pass attempts and yards gained are as follows:

Has to be done in excel. If possible could you please explain step by step so I understand it. Thank you.

Attempts x 116,90,82,108,92

Yards y: 1001 823 851, 873 837

find y1 when x=95

1. Construct a scatter plot label all the X's?

2. Does the scatter plot show evidence of a linear? If it does what type and why?

3. Find the value of R?

4. Test the value for R show a full hypothesis test?

5. Intrupt R2 in context?

6. Find the regression?

7. Construct the residual plot and label all accesses?

8. Is the linear model a value one?

Answer 1

Solutin1;in xcel seelect the data

Go to insert>scatter

Then desgin >axis titles>primary horizonal

you will get

scatterplot as

Add chart elements >data labels

2. Does the scatter plot show evidence of a linear? If it does what type and why?

From scatterplot

form:linear

strength:strong

direction:positive

positive linear relationship exists between x and y

3. Find the value of R?

go to data >data analsyis

correaltion

you will get

	X	Y
X	1
Y	0.819001	1

that is correlation coeffcient

R=0.8190

4. Test the value for R show a full hypothesis test?

r=0.8190

n=number of pairs=5

H0:

Ha:

alpha=0.05

t stat

=t=rsqrt(n-2)/sqrt(1-r^2)

=0.8190*sqrt(5-2)/sqrt(1-0.8190^2)

t=2.47223

P value in excel

=T.DIST.2T(2.47223;3)

=0.089886506

P>0.05

Fail to reject H0

Accept H0

No relationship at 5%

but if at 10% relationship exists.

Solution6:

to get the regression eq

go to data>data analysis>regression

you will get

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.819001
R Square	0.670763
Adjusted R Square	0.561017
Standard Error	47.529
Observations	5
ANOVA
	df	SS	MS	F	Significance F
Regression	1	13806.98	13806.98	6.111972	0.089886
Residual	3	6777.018	2259.006
Total	4	20584
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	466.1581	167.5359	2.782438	0.068851	-67.0158	999.332	-67.0158	999.332
X	4.209446	1.702685	2.47224	0.089886	-1.20926	9.628148	-1.20926	9.628148

From output

R sq=0.670763

=0.6707638*100

=67.08%

67.08% variation in y is explained by model.