### Statistical Analysis Assignment#### Given:(Source: 8th edition of Understandable Statistics, pp 598-599)| X weight | 3.0 | 5.0 | 9.0 | 11.0 | 15.0 | 17.0 | 19.0 | 21.0 ||-----------|-----|-----|-----|------|------|------|------|------|| Y metabolic rate | 1.4 | 2.7 | 5.0 | 6.0 | 7.1 | 7.8 | 8.3 | 8.8 |#### Instructions:1. **Refer to Section 10.1 #14.** a. Use Excel to make a scatter diagram with a best fit hand-drawn line through the points. Tape your diagram below. Remember to add title and axis labels. b. Do you think the correlation is a) low, moderate, or strong? b) Positive or negative? **Ans. a:** ____________________ **Ans. b:** ____________________ c. Use Excel to a) determine the correlation coefficient, b) does this coefficient imply that y will increase or decrease as x increases? **Ans. a:** ____________________ **Ans. b:** ____________________#### Analysis:1. **Scatter Diagram:** - Use the provided data to create a scatter diagram in Excel. - Plot the X (weight) values on the horizontal axis and Y (metabolic rate) values on the vertical axis. - Hand draw a line of best fit through the scattered points to visually represent the relationship between X and Y.2. **Correlation Assessment:** - After plotting the scatter diagram, visually analyze the data points to determine the strength and direction of the correlation. - Answer if the correlation appears to be low, moderate, or strong and whether it is positive or negative.3. **Correlation Coefficient:** - Use Excel to calculate the correlation coefficient using the CORREL function. - Based on the sign and magnitude of the correlation coefficient, determine if Y (metabolic rate) will increase or decrease as X (weight) increases. This assignment will help you understand how to visually and numerically assess the correlation between two sets of data using scatter diagrams and correlation coefficients.

a) Step-by-step software procedure to draw scatter plot using Excel software is given below:…

5.0 9.0 11.0 15.0 17.0 19.0 21.0 X weight Y metabolic rate 3.0 1.4 2.7 5.0 6.0 7.1 7.8 8.3 8.8 1. Refer to 10.1 #14. a. Use Excel to make a scatter diagram with a best fit hand drawn line through the points. Tape your diagram below. Remember to add title and axis labels. b. Do you think the correlation is a) low, moderate or strong? b) Positive or negative? Ans. a Ans. b С. Use Excel to a) determine the correlation coefficient, b) does this coefficient imply that y will increase or decrease as x increases?

5.0 9.0 11.0 15.0 17.0 19.0 21.0 X weight Y metabolic rate 3.0 1.4 2.7 5.0 6.0 7.1 7.8 8.3 8.8 1. Refer to 10.1 #14. a. Use Excel to make a scatter diagram with a best fit hand drawn line through the points. Tape your diagram below. Remember to add title and axis labels. b. Do you think the correlation is a) low, moderate or strong? b) Positive or negative? Ans. a Ans. b С. Use Excel to a) determine the correlation coefficient, b) does this coefficient imply that y will increase or decrease as x increases?

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

100%

### Statistical Analysis Assignment

#### Given:
(Source: 8th edition of Understandable Statistics, pp 598-599)

| X weight | 3.0 | 5.0 | 9.0 | 11.0 | 15.0 | 17.0 | 19.0 | 21.0 |
|-----------|-----|-----|-----|------|------|------|------|------|
| Y metabolic rate | 1.4 | 2.7 | 5.0 | 6.0 | 7.1 | 7.8 | 8.3 | 8.8 |

#### Instructions:

1. **Refer to Section 10.1 #14.**

a. Use Excel to make a scatter diagram with a best fit hand-drawn line through the points. Tape your diagram below. Remember to add title and axis labels.

b. Do you think the correlation is a) low, moderate, or strong? b) Positive or negative?

**Ans. a:** ____________________

**Ans. b:** ____________________

c. Use Excel to a) determine the correlation coefficient, b) does this coefficient imply that y will increase or decrease as x increases?

**Ans. a:** ____________________

**Ans. b:** ____________________

#### Analysis:

1. **Scatter Diagram:**
- Use the provided data to create a scatter diagram in Excel.
- Plot the X (weight) values on the horizontal axis and Y (metabolic rate) values on the vertical axis.
- Hand draw a line of best fit through the scattered points to visually represent the relationship between X and Y.

2. **Correlation Assessment:**
- After plotting the scatter diagram, visually analyze the data points to determine the strength and direction of the correlation.
- Answer if the correlation appears to be low, moderate, or strong and whether it is positive or negative.

3. **Correlation Coefficient:**
- Use Excel to calculate the correlation coefficient using the CORREL function.
- Based on the sign and magnitude of the correlation coefficient, determine if Y (metabolic rate) will increase or decrease as X (weight) increases.

This assignment will help you understand how to visually and numerically assess the correlation between two sets of data using scatter diagrams and correlation coefficients.

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