A panel of judges was rating the taste of different brands of potato chips. Ayane noticed a linear

relationship between the prices and the ratings for 20 different brands. Here is computer output from a

least squares regression analysis for predicting rating from price:

Predictor

Coef

-0.39

Constant

SE Coef

0.57

0.283

-0.687 0.499

8.9 0.000

Price

2.52

S = 0.7387

R-sq = 77.3%

Use this model to predict the rating of a brand that costs $3.00 per bag.

You may round your answer to the nearest whole number rating.

Predicted rating:

Show Calculator

The rating of a brand that costs $3.00 per bag is 7.

Step-by-step explanation:

A simple linear regression equation is used to estimate the value of the dependent variable based upon the independent variable.

The general form of a simple linear regression equation is:

Here,

y = dependent variable

x = independent variable

a = intercept

b = slope

The output of the least squares regression analysis for predicting rating from price is provided.

So, the dependent variable is the ratings and the independent variable is the price.

The regression equation for predicting rating from price is:

Predict the rating of a brand that costs $3.00 per bag as follows:

Thus, the rating of a brand that costs $3.00 per bag is 7.

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