Exploring data review

Question

1. A manager at the Camden Walmart is interested in learning more about the relationship between the number of customers in a checkout line and the total time it takes to check out. She selects a random sample of 11 customers and measured the number of customers who were in front of the selected customer in line and the time until that customer had finished checking out. An analysis of the data is provided below.

a)Identify and interpret the y-intercept of the least squares regression line in context.

b)Identify the coefficient of determination, r2. Interpret it in context.

C)One of the data points appears to be an outlier. Describe this point and explain why it is considered an outlier.

Answer 1

a) The coefficient for "constant" is the predictor for the constant (b₀) in the regression equation. This is the y intercept and represents the average amount of time to checkout if you have 0 people in front of you when you get in the line at the checkout. (72.95 sec)

b) this is even easier to find. look for the R² . That value is the coefficient of determination (the Adj R² is an adjusted value for the number of predictor. Good for multiple regression, but it is still called the adjusted R², not the R² . The coefficient of determination is the proportion of the variance in the dependent variable that is predictable from the independent variable. In this case it indicates that 73.33% of the y variance is predicted by the x.

c). The point near (3,100) appears to be an outlier. Why? because it appears to be more than 3 times the standard error of the residual (vertically) from the regression line.