The Cadet is a popular model of sport utility vehicle, known for itsrelatively high resale value. The bivariate data given below were takenfrom a sample of sixteen Cadets, each bought new two years ago, andeach sold used within the past month. For each Cadet in the sample, wehave listed both the mileage x (in thousands of miles) that the Cadet hadon its odometer at the time it was sold used and the price y (inthousands of dollars) at which the Cadet was sold used. With the aim ofpredicting the used selling price from the number of miles driven, wemight examine the least-squares regression line, y=41.57 – 0.49.x. This line isshown in the scatter plot in Figure 1.Used selling price,Mileage, x(in thousands)(in thousands ofdollars)25.926.128.126.240-21.131.424.027.53527.230.938.721.430.34.625.537.223.515.634.025-23.828.020.930.920.23.132.728.030.34029.228.1Figure 124.029.623.031.5Send data to Excel 1. Fill in the blank: For these data, used selling prices that are greaterthan the mean of the used selling prices tend to be paired withmileages that are.Choose onethe mean of the mileages.2. Fill in the blank: According to the regression equation, for anincrease of one thousand miles in Cadet mileage, there is acorrespondingprice.Choose oneof 0.49 thousand dollars in the used selling3. From the regression equation, what is the predicted used sellingprice (in thousands of dollars) when the mileage is 23.8 thousandmiles? (Round your answer to at least one decimal place.)4. From the regression equation, what is the predicted used sellingprice (in thousands of dollars) when the mileage is 25.3 thousandmiles? (Round your answer to at least one decimal place.)

Regression Line y = 41.57-0.49x

2. Fill in the blank: According to the regression equation, for an increase of one thousand miles in Cadet mileage, there is a corresponding price. Choose one of 0.49 thousand dollars in the used selling 3. From the regression equation, what is the predicted used selling price (in thousands of dollars) when the mileage is 23.8 thousand miles? (Round your answer to at least one decimal place.) 4. From the regression equation, what is the predicted used selling price (in thousands of dollars) when the mileage is 25.3 thousand miles? (Round your answer to at least one decimal place.)

2. Fill in the blank: According to the regression equation, for an increase of one thousand miles in Cadet mileage, there is a corresponding price. Choose one of 0.49 thousand dollars in the used selling 3. From the regression equation, what is the predicted used selling price (in thousands of dollars) when the mileage is 23.8 thousand miles? (Round your answer to at least one decimal place.) 4. From the regression equation, what is the predicted used selling price (in thousands of dollars) when the mileage is 25.3 thousand miles? (Round your answer to at least one decimal place.)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

The Cadet is a popular model of sport utility vehicle, known for its
relatively high resale value. The bivariate data given below were taken
from a sample of sixteen Cadets, each bought new two years ago, and
each sold used within the past month. For each Cadet in the sample, we
have listed both the mileage x (in thousands of miles) that the Cadet had
on its odometer at the time it was sold used and the price y (in
thousands of dollars) at which the Cadet was sold used. With the aim of
predicting the used selling price from the number of miles driven, we
might examine the least-squares regression line, y=41.57 – 0.49.x. This line is
shown in the scatter plot in Figure 1.
Used selling price,
Mileage, x
(in thousands)
(in thousands of
dollars)
25.9
26.1
28.1
26.2
40-
21.1
31.4
24.0
27.5
35
27.2
30.9
38.7
21.4
30.
34.6
25.5
37.2
23.5
15.6
34.0
25-
23.8
28.0
20.9
30.9
20.
23.1
32.7
28.0
30.3
40
29.2
28.1
Figure 1
24.0
29.6
23.0
31.5
Send data to Excel

1. Fill in the blank: For these data, used selling prices that are greater
than the mean of the used selling prices tend to be paired with
mileages that are.
Choose one
the mean of the mileages.
2. Fill in the blank: According to the regression equation, for an
increase of one thousand miles in Cadet mileage, there is a
corresponding
price.
Choose one
of 0.49 thousand dollars in the used selling
3. From the regression equation, what is the predicted used selling
price (in thousands of dollars) when the mileage is 23.8 thousand
miles? (Round your answer to at least one decimal place.)
4. From the regression equation, what is the predicted used selling
price (in thousands of dollars) when the mileage is 25.3 thousand
miles? (Round your answer to at least one decimal place.)

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