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R12.4 Long legs Construct and interpret a 95% confidence interval for the slope of the population regression line. Assume that the conditions for inference are met. Explain how the interval provides more information than the test in R12.3.

Short Answer

Expert verified

A 95% confidence level that the true regression line's slope is between -1.3168396 and -0.5253604.

Step by step solution

01

Given information

To construct and interpret a 95% confidence interval for the slope of the population regression line

02

Explanation

A analysis was conducted to see if taller students needed fewer steps to go a certain distance. The box plot in the question indicates the link between height and the number of steps needed to walk down the school corridor. And it's been assumed that the inference requirements are met.
As a result, it is assumed that
n=36
α=0.05
The slope b1 is calculated as follows in the computer output's row "Height" and column "Coef":
b1=-0.9211
In the row "Height" and the column "SE Coef" of the given computer output, the standard error of the slope SEb1is provided as:
SEb1=0.1938

03

Explanation

To find the degrees of freedom, as follows:
df=n-2
=36-2
=34
The t-value can then be discovered in the T-distribution table of the student.
t*=2.042
As a result, the confidence interval is as follows:
b-t*×SEb
=-0.9211-2.042×0.1938
=-1.3168396
b+t*×SEb
=-0.9211+2.042×0.1938
=-0.5253604
As a result, a 95% confidence level that the true regression line's slope is between -1.3168396 and -0.5253604.

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Most popular questions from this chapter

Exercises T12.4–T12.8 refer to the following setting. An old saying in golf is “You drive for show and you putt for dough.” The point is that good putting is more important than long driving for shooting low scores and hence winning money. To see if this is the case, data from a random sample of 69 of the nearly 1000 players on the PGA Tour’s world money list are examined. The average number of putts per hole (fewer is better) and the player’s total winnings for the previous season are recorded and a least-squares regression line was fitted to the data. Assume the conditions for
inference about the slope are met. Here is computer output from the regression analysis:

T12.8 Which of the following would make the calculation in Exercise T12.7 invalid?

a. If the scatterplot of the sample data wasn’t perfectly linear.

b. If the distribution of earnings has an outlier.

c. If the distribution of earnings wasn’t approximately Normal.

d. If the earnings for golfers with small putting averages was much more variable than the earnings for golfers with large putting averages.

e. If the standard deviation of earnings is much larger than the standard deviation of putting average.

Which of the following statements about the t distribution with degrees of freedom dfis (are) true?

I. It is symmetric.

II. It has more variability than the t distribution with df+1degrees of freedom. III. III. As df increases, the t distribution approaches the standard Normal distribution.

a. I only

b. II only

c. III only

d. I and III

e. I, II, and III

Multiple Choice Select the best answer for Exercises 23-28. Exercises 23-28 refer to the following setting. To see if students with longer feet tend to be taller, a random sample of 25students was selected from a large high school. For each student, x=footlength&y=heightere recorded. We checked that the conditions for inference about the slope of the population regression line are met. Here is a portion of the computer output from a least-squares regression analysis using these data:

26. Which of the following is the best interpretation of the value 0.4117in the computer output?

a. For each increase of 1cmin foot length, the average height increases by about0.4117cm

b. When using this model to predict height, the predictions will typically be off by about 0.4117cm.

c. The linear relationship between foot length and height accounts for 41.17%of the variation in height.

d. The linear relationship between foot length and height is moderate and positive.

e. In repeated samples of size 25the slope of the sample regression line for predicting height from foot length will typically vary from the population slope by about 0.4117.

Heart weights of mammals Here are some data on the hearts of various mammals:

a. Make an appropriate scatterplot for predicting heart weight from length. Describe what you see.

b. Use transformations to linearize the relationship. Does the relationship between heart weight and length seem to follow an exponential model or a power model? Justify your answer.

c. Perform least-squares regression on the transformed data. Give the equation of your regression line. Define any variables you use.

d. Use your model from part (c) to predict the heart weight of a human who has a left ventricle6.8 cm long.

Click-through rates Companies work hard to have their website listed at the top of an Internet search. Is there a relationship between a website’s position in the results of an Internet search (1=top position,2=2nd position, etc.) and the percentage of people who click on the link for the website? Here are click-through rates for the top 10 positions in searches on a mobile device:

a. Make an appropriate scatterplot for predicting click-through rate from the position. Describe what you see.

b. Use transformations to linearize the relationship. Does the relationship between click-through rate and position seem to follow an exponential model or a power model? Justify your answer.

c. Perform least-squares regression on the transformed data. Give the equation of your regression line. Define any variables you use.

d. Use your model from part (c) to predict the click-through rate for a website in the 11th position.

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