Group:
Hayden Derk Strikwerda

Abstract:
Why is it needed in this case?
When dealing with defects in a business it is easy to quantify what percentage of your product is defective, it is not as easy to pinpoint where those defects come from. When various inputs are required to make a certain output it is harder to quantify how dependent a product is from one input. This is where simple linear regression plays a role in helping continuous improvement specialists eliminate defects in various products. 
How does it work? 
Simple Linear Regression works by plotting the data in a scatterplot and then running the linear regression line through the data points. Y = a + bX + e is the equation that is used in graphing the line. Y is the value of the output. A is the estimated Y intercept. ‘b’ is the correlation from -1 to 1 which signifies the relationship form input to output. e is an error term representing the unexplained or residual variance. 
How does it relate to Linear Algebra 
	When computing this line we use the least squares method. When using the least squares method there are techniques in linear algebra to find a, b, x, and e.
What we are going to do?
	We will use these techniques to see if we can find causal relationships not just correlations in the defects we are seeing in our service.