An analyst at Starbucks has collected data from a random sample of company stores and built a regression model to predict the daily sales ($) at each store.

REGRESSION MODEL FIT

Determine the number of observations in the sample used to build this prediction model.

Determine r-squared for this prediction model.

What is the regression degrees of freedom for this prediction model?

What is the residual degrees of freedom for this prediction model?

What is the sum of squares error (SSE) for this prediction model?

MODEL COEFFICIENTS

What is the t-statistic used in testing a hypothesis that there is a relationship between Drive-Thru and DailySales (USD)?

What is the p-value used in a hypothesis test of the relationship between CompetitorsWithinMile and DailySales (USD)?

What is the amount of acceptable error in each tail (/2) used in a hypothesis test or confidence interval for intercept or slope if the confidence level is 96%? Provide the value as a decimal, not a percentage.

What is the critical t-value (t_/2) required to obtain a 96% confidence level?

What is value of the lower limit of the 96% confidence interval for the PopulationWithinMile coefficient/slope?

What is value of the upper limit of the 96% confidence interval for the PopulationWithinMile coefficient/slope?

What is the most correct statistical interpretation of the coefficient for PopulationWithinMile?

(a)

About 0.226 of the variance in DailySales (USD) is explained by PopulationWithinMile.

(b)

For an additional 0.226 PopulationWithinMile, we predict one additional DailySales (USD).

(c)

The probability that the coefficient is zero in the population is p = 0.226.

(d)

An additional $0.226 of DailySales (USD) is predicted for each additional PopulationWithinMile.

What is the correctly specified model/equation for predicting DailySales (USD) given this regression output? Specify all coefficients regardless of statistical significance.

(a)

y = b₀ * x

(b)

y = b₀ + b₁x₁ + b₂x₂ + b₃x₃ + b₄x₄

(c)

y = b₀ + b₁x₁ + b₂x₂

(d)

b₀ = y