Linear Regression

Calculaiton

Week	Old process	Old	Calculations	Week	New process	New	Calculation
1		Slope	ERROR:#DIV/0!	1		Slope	ERROR:#DIV/0!
2		Intercept	ERROR:#DIV/0!	2		Intercept	ERROR:#DIV/0!
3		correlation coefficient (r)	ERROR:#DIV/0!	3		correlation coefficient (r)	ERROR:#DIV/0!
4		coefficient of determination (r^2)	ERROR:#DIV/0!	4		coefficient of determination (r^2)	ERROR:#DIV/0!
5		Average	ERROR:#DIV/0!	5		Average	ERROR:#DIV/0!
6		Lineat Regression	Y=b+mx	6		Linear Regression	Y=b+mx
7				7
8				8
9				9
10				10
11				11
12				12
		EXAMPLE ON HOW TO INTERPRET RESULTS
	Interpretations		These are for the new process
	For every increase of one unit there is a decrease of 1.12 in predicted y
	When there is an absence of x values the predicted y value is 56.0
	There is a negative and weak association between the variables
	11.2% of the variability present in predicted y can be explained by variability present in
	the model. Another interpretation ends with th phrase: variability present in x.
	In this example the equation for the LSRL is : y = -1.12x + 56.0

Old Process

Old process

New Process

New process