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Actual consumption Refer to Exercise 48. Use the equation of the least-squares regression line and the residual plot to estimate the actual fuel consumption of the car when driving 20 kilometers per hour.

Short Answer

Expert verified

The actual fuel consumption when driving 20 kilometers per hour is approximately 13.2426 liters per 100 km driven.

Step by step solution

01

Given information

It is given that:

y=11.03580.01466x

The figure is

02

Concept

The formula used:Residual=yy

03

Calculation

Let's start by determining the regression line's anticipated weight, which can be done by evaluating the regression line's equation, which is:

y=11.03580.01466x=11.03580.01466(20)=10.7426

In the residual plot, we can see that the residual corresponding to 20kilometers per hour is around 2.5

Thus, the residual will be:

Residual=2.5

The residual, as we know, is the actual value reduced by the anticipated value, so

Residual=yyy=Residual+y=2.5+10.7426=13.2426

As a result, the fuel consumption units are in litres per 100 kilometres driven, and the actual fuel consumption at 20 kilometres per hour is roughly 13.2426 litres per 100 kilometres driven.

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Most popular questions from this chapter

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.

Will I bomb the final? We expect that students who do well on the midterm exam in a course will usually also do well on the final exam. Gary Smith of Pomona College looked at the exam scores of all 346 students who took his statistics class over a 10-year period. 17 The least-squares line for predicting final-exam score from midterm-exam score was y=46.6+0.41x . Octavio scores 10 points above the class mean on the midterm. How many points above the class mean do you predict that he will score on the final? (This is an example of the phenomenon that gave “regression” its name: students who do well on the midterm will on the average do less well, but still above average, on the final.)

Crickets chirping The scatterplot shows the relationship between x = temperature in degrees Fahrenheit and y = chirps per minute for the striped ground cricket, along with the regression line y^=−0.31+0.212x

a. Calculate and interpret the residual for the cricket who chirped 20 times per minute when the temperature was 88.6°F.

b. About how many additional chirps per minute do you expect cricket to make if the temperature increases by 10°F?

The scatterplot shows the relationship between the number of people per television set and the number of people per physician for 40 countries, along with the least-squares regression line. In Ethiopia, there were 503 people per TV and 36,660 people per doctor. Which of the following is correct?

a. Increasing the number of TVs in a country will attract more doctors.

b. The slope of the least-squares regression line is less than 1.

c. The correlation is greater than 1.

d. The point for Ethiopia is decreasing the slope of the least-squares regression line.

e. Ethiopia has more people per doctor than expected, based on how many people it has per TV.

Born to be old? Is there a relationship between the gestational period (time from conception to birth) of an animal and its average life span? The figure shows a scatterplot of the gestational period and average life span for 43 species of animals.

a. Describe the relationship shown in the scatterplot.

b. Point A is the hippopotamus. What effect does this point have on the correlation, the equation of the least-squares regression line, and the standard deviation of the residuals?

c. Point B is the Asian elephant. What effect does this point have on the correlation, the equation of the least-squares regression line, and the standard deviation of the residuals?

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