### Analyzing Weight and Highway Mileage DataThe table lists weights (in pounds) and highway mileage amounts (in miles per gallon) for seven automobiles. The sample data is used to construct a scatterplot. You will use the weight variable for the x-axis.#### Data Table:| Weight (lb) | 2725 | 2875 | 3480 | 4070 | 4350 | 4245 | 3125 ||-------------|------|------|------|------|------|------|------|| Highway (mpg) | 34 | 33 | 30 | 25 | 24 | 26 | 31 |### ScatterplotsYou need to determine which of the provided scatterplots correctly represents the data above.#### Options:- **Scatterplot A**- **Scatterplot B**- **Scatterplot C**- **Scatterplot D**### Question:Is there a linear relationship between weight and highway mileage?#### Choices:- **A.** No, there appears to be no relationship.- **B.** Yes, as the weight increases the highway mileage increases.- **C.** No, there appears to be a relationship, but it is not linear.Click to select your answer.### Graph and Diagram Analysis:1. Each scatterplot has `Weight (lb)` on the x-axis, ranging from 2000 to 5000 pounds.2. Each scatterplot has `Highway (mpg)` on the y-axis, ranging from 20 to 40 miles per gallon.3. To determine the correct scatterplot: - Plot each pair of data points from the table. - Observe the pattern they form.Analyzing the data:- As weight increases, highway mileage generally decreases.- You should observe a negative correlation in the correct scatterplot.Use this information to select the scatterplot that accurately represents the data and identify the relationship between weight and highway mileage.

The graphically represented data in an axial format for two variables can be called a scatter…

The table lists weights (pounds) and highway mileage amounts (mpg) for seven automobiles. Use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? Weight (Ib) Highway (mpg) 2725 34 2875 33 4070 25 4090 24 2425 3125 3480 30 36 31 Which scatterplot below shows the data? OA. OB. OC. OD. a 40- 40 - a 40- a 40- Q 20 2000 H 20- 2000 Weight (b) H 20- 2000 Weight (b) 20 2000 Weight (b) 5000 5000 5000 5000 Weight (b) Is there a linear relationship between weight and highway mileage? O A. No, there appears to be no relationship. O B. Yes, as the weight increases the highway mileage increases O C. No, there appears to be a relationship, but it is not linear. Click to select your answer.

The table lists weights (pounds) and highway mileage amounts (mpg) for seven automobiles. Use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? Weight (Ib) Highway (mpg) 2725 34 2875 33 4070 25 4090 24 2425 3125 3480 30 36 31 Which scatterplot below shows the data? OA. OB. OC. OD. a 40- 40 - a 40- a 40- Q 20 2000 H 20- 2000 Weight (b) H 20- 2000 Weight (b) 20 2000 Weight (b) 5000 5000 5000 5000 Weight (b) Is there a linear relationship between weight and highway mileage? O A. No, there appears to be no relationship. O B. Yes, as the weight increases the highway mileage increases O C. No, there appears to be a relationship, but it is not linear. Click to select your answer.

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

### Analyzing Weight and Highway Mileage Data

The table lists weights (in pounds) and highway mileage amounts (in miles per gallon) for seven automobiles. The sample data is used to construct a scatterplot. You will use the weight variable for the x-axis.

#### Data Table:
| Weight (lb) | 2725 | 2875 | 3480 | 4070 | 4350 | 4245 | 3125 |
|-------------|------|------|------|------|------|------|------|
| Highway (mpg) | 34 | 33 | 30 | 25 | 24 | 26 | 31 |

### Scatterplots
You need to determine which of the provided scatterplots correctly represents the data above.

#### Options:
- **Scatterplot A**
- **Scatterplot B**
- **Scatterplot C**
- **Scatterplot D**

### Question:
Is there a linear relationship between weight and highway mileage?

#### Choices:
- **A.** No, there appears to be no relationship.
- **B.** Yes, as the weight increases the highway mileage increases.
- **C.** No, there appears to be a relationship, but it is not linear.

Click to select your answer.

### Graph and Diagram Analysis:
1. Each scatterplot has `Weight (lb)` on the x-axis, ranging from 2000 to 5000 pounds.
2. Each scatterplot has `Highway (mpg)` on the y-axis, ranging from 20 to 40 miles per gallon.
3. To determine the correct scatterplot:
- Plot each pair of data points from the table.
- Observe the pattern they form.

Analyzing the data:
- As weight increases, highway mileage generally decreases.
- You should observe a negative correlation in the correct scatterplot.

Use this information to select the scatterplot that accurately represents the data and identify the relationship between weight and highway mileage.

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