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Which of the following is not a characteristic of the least-squares regression line?

a. The slope of the least-squares regression line is always between –1 and 1.

b. The least-squares regression line always goes through the point (x¯,y¯) .

c. The least-squares regression line minimizes the sum of squared residuals.

d. The slope of the least-squares regression line will always have the same sign as the correlation.

e. The least-squares regression line is not resistant to outliers.

Short Answer

Expert verified

The correct option is (a) The slope of the least-squares regression line is always between-1 and 1

Step by step solution

01

Given information

The properties of the least square regression line can be seen in five different ways.

02

Explanation

The equation of the regression line is:

y=a+bxa=y-interceptb=Slopecoefficient

line's values are not limited in any way. It might be positive or negative and have any value. As a result, the slope of the regression line cannot be considered to be between -1and 1

Thus, option (a) is not the characteristic of the regression line.

Hence, the correct option is (a).

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Most popular questions from this chapter

It’s still early We expect that a baseball player who has a high batting average in the first month of the season will also have a high batting average for the rest of the season. Using 66 Major League Baseball players from a recent season,33 a least-squares regression line was calculated to predict rest-of-season batting average y from first-month batting average x. Note: A player’s batting average is the proportion of times at-bat that he gets a hit. A batting average over 0.300 is considered very good in Major League Baseball.

a. State the equation of the least-squares regression line if each player had the same batting average the rest of the season as he did in the first month of the season.

b. The actual equation of the least-squares regression line is y^=0.245+0.109x

Predict the rest-of-season batting average for a player who had a 0.200 batting average the first month of the season and for a player who had a 0.400 batting average the first month of the season.

c. Explain how your answers to part (b) illustrate regression to the mean.

More Starbucks In Exercises 6 and 12, you described the relationship between fat (on Page Number: 204 grams) and the number of calories in products sold at Starbucks. The scatterplot shows this relationship, along with two regression lines. The regression line for the food products (blue squares) is y^=170+11.8x. The regression line for the drink products

(black dots) is y^=88+24.5x

a. How do the regression lines compare?

b. How many more calories do you expect to find in a food item with 5 grams of fat compared to a drink item with 5 grams of fat?

More crying? Refer to Exercise 16Does the fact that r=0.45 suggest that making an infant cry will increase his or her IQ later in life? Explain your reasoning.

Teenagers and corn yield Identify the explanatory variable and the response variable for the following relationships, if possible. Explain your reasoning.

a. The height and arm span of a sample of 50 teenagers.

b. The yield of corn in bushels per acre and the amount of rain in the growing season.

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