Jit Labs

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University of Minnesota-Twin Cities *

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2550

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Statistics

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Feb 20, 2024

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docx

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Jit Lab 8 plot(Sales ~ Budget, data=TeddyBearSales, main="scatterplot for budget vs. sales teddy",xlab ="Budget",ylab ="sales") abline(a=0, b=1,col="Blue", lty=2,lwd=3) abline(lm(Sales ~ Budget, data= TeddyBearSales),col="Red", lty=1,lwd=3) lm(Sales ~ Budget, data= TeddyBearSales) Independent Variable: Budget (x) Dependent Variable: Sales (y) Regression budget on sales: sales~budget Regression equation: S_hat (ŷ) = -0.1 +0.7*Budget (x) Jit Lab 11 What is the residual standard error for this regression? Write up an interpretation for the same ● The residual standard error for this regression is 0.9765 on 115 degrees of freedom. Considering the RSE is close to zero, our model is ideal. We want RSE to be as close to 0 as possible. What percent of the variation in the dependent variable is explained by the independent variables? (Interpret R-squared). ● 91.1% of variance in response is explained by a linear combination of bpm, danceability, valence, and duration. Since there are multiple variables the percentage increases, hence the high number. Does the overall global model have significant explanatory power? (Interpret F-Test).
● 294.1 with p-val of 2.2e-16 → 2.2e-16 = 0.000 < 0.05. The overall fit of the data is significant.
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