x 11 7 12 14 7 y 7.59 6.64 7.89 8.93 6.3 5.94 www OA. OB. O C. 25 25- 25 20 20 20 15 15 105 15: 10 10 $3000 5 89 5- 1980 5 0 0 0 5 10 15 20 25 0 0 5 10 15 20 25 0 5 10 15 20 25 Find the equation of the regression line. y= (Round the y-intercept two decimal places as needed. Round the slope to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. OA. There is no characteristic of the data that is ignored by the regression line. B. The data has a pattern that is not a straight line. OC. There is an influential point that strongly affects the graph of the regression line. OD. There is no trend in the data. 13 10 13.32 6.78 Q Ay Ay 7 4 13 5.83 5.44 8.05 Q Q G 5 C Ay Q OD. 25- 20 155 10 5- 10 0 5 10 15 20 25 see s see s see se 88.3 76.5 85.8
x 11 7 12 14 7 y 7.59 6.64 7.89 8.93 6.3 5.94 www OA. OB. O C. 25 25- 25 20 20 20 15 15 105 15: 10 10 $3000 5 89 5- 1980 5 0 0 0 5 10 15 20 25 0 0 5 10 15 20 25 0 5 10 15 20 25 Find the equation of the regression line. y= (Round the y-intercept two decimal places as needed. Round the slope to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. OA. There is no characteristic of the data that is ignored by the regression line. B. The data has a pattern that is not a straight line. OC. There is an influential point that strongly affects the graph of the regression line. OD. There is no trend in the data. 13 10 13.32 6.78 Q Ay Ay 7 4 13 5.83 5.44 8.05 Q Q G 5 C Ay Q OD. 25- 20 155 10 5- 10 0 5 10 15 20 25 see s see s see se 88.3 76.5 85.8
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
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![**Title: Understanding Regression Lines and Scatterplots**
### Introduction
In this lesson, we will use provided data to determine the equation of a regression line. We will also examine scatterplots to identify specific characteristics in the data that the regression line may overlook.
### Data Set
The given data pairs (x, y) are as follows:
| x | 11 | 17 | 13 | 10 | 12 | 14 | 4 | 13 | 7 | 5 |
|----|-----|-----|-----|-----|-----|-----|---|-----|---|---|
| y | 7.59 | 6.64 | 13.32 | 6.78 | 7.89 | 8.93 | 5.83 | 5.44 | 8.05 | 6.3 | 5.94 |
### Finding the Regression Line
The equation for the regression line takes the form:
\[ \hat{y} = a + bx \]
We solve for 'a' (y-intercept) and 'b' (slope) by using statistical formulas or tools. Remember to:
- Round the y-intercept to two decimal places.
- Round the slope to three decimal places.
### Scatterplots Analysis
Four scatterplots, labeled A, B, C, and D, illustrate different distributions of the data points.
#### Diagram Descriptions:
1. **Scatterplot A:**
The points are closely clustered in an upward direction but with notable dispersion.
2. **Scatterplot B:**
Points seem randomly distributed with no clear pattern.
3. **Scatterplot C:**
One point appears significantly higher compared to others, indicating a potential outlier.
4. **Scatterplot D:**
Points indicate a linear trend but with considerable dispersion around the line.
### Identifying Characteristics Overlooked by the Regression Line
Determining a characteristic from the data that the regression line might ignore involves selecting one of the following options:
- **Option A:** There is no characteristic of the data that is ignored by the regression line.
- **Option B:** The data has a pattern that is not a straight line.
- **Option C:** There is an influential point that strongly affects the graph of the regression line.
- **Option D:** There is no trend in the data.
### Learning Objectives
1. **Understand the concept of](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F96fb4f59-e2d0-4223-b88e-b1f942117eac%2F05486d19-1dde-4d45-a39e-c975f53ee6b9%2Fxbtw4uw_processed.jpeg&w=3840&q=75)
Transcribed Image Text:**Title: Understanding Regression Lines and Scatterplots**
### Introduction
In this lesson, we will use provided data to determine the equation of a regression line. We will also examine scatterplots to identify specific characteristics in the data that the regression line may overlook.
### Data Set
The given data pairs (x, y) are as follows:
| x | 11 | 17 | 13 | 10 | 12 | 14 | 4 | 13 | 7 | 5 |
|----|-----|-----|-----|-----|-----|-----|---|-----|---|---|
| y | 7.59 | 6.64 | 13.32 | 6.78 | 7.89 | 8.93 | 5.83 | 5.44 | 8.05 | 6.3 | 5.94 |
### Finding the Regression Line
The equation for the regression line takes the form:
\[ \hat{y} = a + bx \]
We solve for 'a' (y-intercept) and 'b' (slope) by using statistical formulas or tools. Remember to:
- Round the y-intercept to two decimal places.
- Round the slope to three decimal places.
### Scatterplots Analysis
Four scatterplots, labeled A, B, C, and D, illustrate different distributions of the data points.
#### Diagram Descriptions:
1. **Scatterplot A:**
The points are closely clustered in an upward direction but with notable dispersion.
2. **Scatterplot B:**
Points seem randomly distributed with no clear pattern.
3. **Scatterplot C:**
One point appears significantly higher compared to others, indicating a potential outlier.
4. **Scatterplot D:**
Points indicate a linear trend but with considerable dispersion around the line.
### Identifying Characteristics Overlooked by the Regression Line
Determining a characteristic from the data that the regression line might ignore involves selecting one of the following options:
- **Option A:** There is no characteristic of the data that is ignored by the regression line.
- **Option B:** The data has a pattern that is not a straight line.
- **Option C:** There is an influential point that strongly affects the graph of the regression line.
- **Option D:** There is no trend in the data.
### Learning Objectives
1. **Understand the concept of
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