DATA MANAGEMENT INSTRUCTIONS: Search for bivariate data (in a magazine, a newspaper, on the Internet, or data available in your household) that can be closely modeled by a linear equation. (Bivariate data could be two sets of data coming from two variables that are dependent on each other or one is dependent on the other - independent and dependent variables.) Example: number of COVID-19 cases and the average temperature ( of different countries) 1. Make a report about each data The report includes graph and brief discussion presenting some statistical measures which you can obtain using statistical software or application. 2. Find the relationship of the variables using your data and find an equation of showing the relationship. This requires you to compute the correlation coefficient and set up the regression equation to describe the nature of the relationship. 3. Use your equation to predict a range of values for a specific value of the variable. This requires you to apply the equation in 2 for some given value of the independent variable or maybe a value of the dependent variable.

DATA MANAGEMENT INSTRUCTIONS: Search for bivariate data (in a magazine, a newspaper, on the Internet, or data available in your household) that can be closely modeled by a linear equation. (Bivariate data could be two sets of data coming from two variables that are dependent on each other or one is dependent on the other - independent and dependent variables.) Example: number of COVID-19 cases and the average temperature ( of different countries) 1. Make a report about each data The report includes graph and brief discussion presenting some statistical measures which you can obtain using statistical software or application. 2. Find the relationship of the variables using your data and find an equation of showing the relationship. This requires you to compute the correlation coefficient and set up the regression equation to describe the nature of the relationship. 3. Use your equation to predict a range of values for a specific value of the variable. This requires you to apply the equation in 2 for some given value of the independent variable or maybe a value of the dependent variable.

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

ull SUN
8:36 PM
90%
Exercise5
O 0o
Exercise No. 5
DATA MANAGEMENT
INSTRUCTIONS:
Search for bivariate data (in a magazine, a newspaper, on the Internet, or
data available in your household) that can be closely modeled by a linear
equation.
(Bivariate data could be two sets of data coming from two variables that
are dependent on each other or one is dependent on the other -
independent and dependent variables.)
Example: number of COVID-19 cases and the average temperature
( of different countries)
1. Make a report about each data
The report includes graph and brief discussion presenting some
statistical measures which you can obtain using statistical software or
application.
2. Find the relationship of the variables using your data and find an
equation of showing the relationship.
This requires you to compute the correlation coefficient and set up
the regression equation to describe the nature of the relationship.
3. Use your equation to predict a range of values for a specific value of
the variable.
This requires you to apply the equation in 2 for some given value of
the independent variable or maybe a value of the dependent variable.

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