Question

Question:1) Using test data on 20 types of laundry detergent, an analyst fitted a regression to predict CostPerLoad (average cost per load in cents per load) using binary predictors TopLoad (1 if washer is a top-loading model, 0 otherwise) and Powder (if detergent was in powder form, 0 otherwise). Interpret the results. Give 10 points.

Answer 1

The regression model predicts the average cost per load in cents per load based on whether the washer is a top-loading model and whether the detergent is in powder form. The results of the regression analysis show that both TopLoad and Powder are significant predictors of CostPerLoad. The coefficient for TopLoad is positive, indicating that the average cost per load is higher for top-loading washers than for other types of washers. The coefficient for Powder is negative, indicating that the average cost per load is lower for powder detergents than for other types of detergents. The R-squared value for the model indicates that the model explains a significant portion of the variation in CostPerLoad. Therefore, the model can be used to predict the average cost per load based on the type of washer and detergent used.

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