Your Turn: Data Set 1 Instructions: Use the technology of your choice (calculator, Excel, GeoGebra, Google Sheets) to find the regression line, the correlation coefficient of the following data sets, and interpolate or extrapolate the requested data. (Round all numbers to the nearest hundredth, when necessary.) Data Set: {(0, 7), (1, 5), (1.5, 3), (2, 5), (2.3, 3.2), (3, 2), (3.5, 4)} 1. The regression line is: y = 2. Based on the regression line, we would expect the value of response variable to be when the explanatory variable is 0. (NOTE: This is the y-intercept.) 3. For each increase of 1 in of the explanatory variable, we can expect a(n) * of in the response variable. (NOTE: This is the slope.)
Your Turn: Data Set 1 Instructions: Use the technology of your choice (calculator, Excel, GeoGebra, Google Sheets) to find the regression line, the correlation coefficient of the following data sets, and interpolate or extrapolate the requested data. (Round all numbers to the nearest hundredth, when necessary.) Data Set: {(0, 7), (1, 5), (1.5, 3), (2, 5), (2.3, 3.2), (3, 2), (3.5, 4)} 1. The regression line is: y = 2. Based on the regression line, we would expect the value of response variable to be when the explanatory variable is 0. (NOTE: This is the y-intercept.) 3. For each increase of 1 in of the explanatory variable, we can expect a(n) * of in the response variable. (NOTE: This is the slope.)
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
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
Transcribed Image Text:Your Turn: Data Set 2
Data Set: {(-3, 4), (–2, 3), (–1, 3), (0, 7), (1, 5), (2, 6), (3, 1)}
1. The regression line is: y =
2. Based on the regression line, we would expect the value of
response variable to be
when the explanatory variable is
0.
3. For each increase of 1 in of the explanatory variable, we can
expect a(n)
* of
in the response variable.
4. If x = -3.5, the ŷ =
This is an example of
5. The correlation coefficient isr =
(Round to the
nearest hundredth.)
Check
Transcribed Image Text:Your Turn: Data Set 1
Instructions: Use the technology of your choice (calculator, Excel,
GeoGebra, Google Sheets) to find the regression line, the correlation
coefficient of the following data sets, and interpolate or extrapolate the
requested data. (Round all numbers to the nearest hundredth, when
necessary.)
Data Set: {(0, 7), (1, 5), (1.5, 3), (2, 5), (2.3, 3.2), (3, 2), (3.5, 4)}
1. The regression line is: y =
2. Based on the regression line, we would expect the value of
response variable to be
when the explanatory variable is
0. (NOTE: This is the y-intercept.)
3. For each increase of 1 in of the explanatory variable, we can
expect a(n)
+ of
in the response variable.
(NOTE: This is the slope.)
4. If x = 2.5, the ŷ =
This is an example of
5. The correlation coefficient isr =
Check
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
This is a popular solution!
Trending now
This is a popular solution!
Step by step
Solved in 4 steps
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Recommended textbooks for you
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman