Question

85	1,810
90	4,825
79	438
82	775
84	1,213
96	8,692
88	2,356
76	266
93	4,930
97	9,138
89	2,714
83	1,082
85	1,290
90	3,970
82	894
91	2,906
90	4,615
84	1,168
79	462
81	1,018
95	5,950

What is multiple R, R square, & Adjusted R square?

Do regression model results indicate significance, meaning the results can be accepted? Yes or No.

For every 1 increase in Temperature, how much do sales increase?

Answer 1

You didn't mention which column represent temperature and which is sales.

I assume first one is temperature and other one is sale.

I used excel for calculation purpose.

output is as follows:

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.922351
R Square	0.850732
Adjusted R Square	0.842876
Standard Error	1041.057
Observations	21
ANOVA
	df	SS	MS	F	Significance F
Regression	1	1.17E+08	1.17E+08	108.2876	2.7611E-09
Residual	19	20592210	1083801
Total	20	1.38E+08
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-32511.2	3408.723	-9.53766	1.12E-08	-39645.78693	-25376.7	-39645.8	-25376.7
X Variable 1	408.6026	39.26555	10.40613	2.76E-09	326.4188809	490.7864	326.4189	490.7864

Highlighted column gives multiple R, R square, & Adjusted R square.

Since calculated value of f is greater than significant f.

We conclude that regression is significant. that is we can accept the result.

If we increase temperature by 1 sales will increased by 408.606