La Cabaa, a popular motel chain in the southwest, is interested in developing a regression model that can predict the occupancy rate % of its motels. Currently, the company is interested in using two explanatory variables to predict occupancy. They want to use the amount of advertising in $ used by each motel and if the particular location a franchised location. Some regression information is presented below:

Summary measures
Multiple R	0.5358
R-Square	0.2871
Adj R-Square	0.2223
StErr of Estimate	7.582
Regression coefficients
	Coefficient	Std Err	t-value	p-value
Constant	43.118	11.4263	3.7735	0.0010
Advertising	0.0013	0.0006	2.4119	0.0247
Franchise	3.038	3.1759	0.9567	0.3491

If we write the linear regression model aswhere X1 is Advertising, and X2 is Franchise, then from the above information, we can infer that a is

b is,

and c is,

percentage of the variation in the occupancy can be explained by this regression equation. (Please keep two decimal points.)

From the p-values, we may conclude that at 5% confidence level, all the coefficients are statistically

after refining the regressors. (Please only fill in "significant" or "insignificant".)