A toaster company wanted to see if they could predict customer satisfaction levels based on the price of the toaster.  They collected a random sample of 6 toasters and compared the price and the percentage of customers who were satisfied.  Then they used this data to run a simple linear regression analysis.

The regression run on Excel using the data shown gave the output shown below the data.

 

Price	Customer Satisfaction
13	72
35	84
31	76
38	94
43	93
46	97
SUMMARY OUTPUT
Regression Statistics
Multiple R	0.903562019
R Square	0.816424323
Adjusted R Square	0.770530403
Standard Error	4.950490172
Observations	6
ANOVA
	df	SS	MS	F	Significance F
Regression	1	435.9705882	435.9705882	17.78937894	0.013501976
Residual	4	98.02941176	24.50735294
Total	5	534
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	58.73529412	6.772852103	8.672165466	0.000972952	39.93084205	77.53974619	39.93084205	77.53974619
Price	0.794117647	0.188280115	4.217745718	0.013501976	0.271368244	1.31686705	0.271368244	1.31686705

What percentage of the variation in customer satisfaction is explained by variation in price? Enter your answer as a percentage but do not enter a % symbol in your answer, just the number. No decimals are necessary.