Baseball owners believe that the more runs scored, the higher the attendance. Is there evidence that more fans attend games if the eams score more runs? Data collected midway through the season indicate a correlation of 0.848 between runs scored and the number of people at games. a) Does the scatterplot indicate that it's appropriate to calculate a correlation? Explain. O A. Yes, because the relationship between number of runs scored and attendance appears to be straigl O B. Yes, because the association between the number of runs scored and attendance is positive. 37500- OC. No, because there are too many outliers for a numerical correlation to be appropriate. 30000- O D. No, because the number runs scored and attendance are not quantitative variables. 22500- b) Describe the association between attendance and runs scored. 320 360 400 440 480 O A. The association between attendance and runs scored is negative, straight, and moderate. Runs O B. The association between attendance and runs scored is positive, straight, and moderate. OC. The association between attendance and runs scored is negative, straight, and strong. O D. The association between attendance and runs scored is positive, straight, and weak. c) Does this prove that the owners are right, that more fans will come to games if the teams score more runs O A. No, there is no evidence of an association between attendance and runs scored. O B. Yes, there is évidence of an association between attendance and runs scored. Oc. Yes, there is basis make a claim of causation. O D. No, there is no basis to make a claim of causation.
Baseball owners believe that the more runs scored, the higher the attendance. Is there evidence that more fans attend games if the eams score more runs? Data collected midway through the season indicate a correlation of 0.848 between runs scored and the number of people at games. a) Does the scatterplot indicate that it's appropriate to calculate a correlation? Explain. O A. Yes, because the relationship between number of runs scored and attendance appears to be straigl O B. Yes, because the association between the number of runs scored and attendance is positive. 37500- OC. No, because there are too many outliers for a numerical correlation to be appropriate. 30000- O D. No, because the number runs scored and attendance are not quantitative variables. 22500- b) Describe the association between attendance and runs scored. 320 360 400 440 480 O A. The association between attendance and runs scored is negative, straight, and moderate. Runs O B. The association between attendance and runs scored is positive, straight, and moderate. OC. The association between attendance and runs scored is negative, straight, and strong. O D. The association between attendance and runs scored is positive, straight, and weak. c) Does this prove that the owners are right, that more fans will come to games if the teams score more runs O A. No, there is no evidence of an association between attendance and runs scored. O B. Yes, there is évidence of an association between attendance and runs scored. Oc. Yes, there is basis make a claim of causation. O D. No, there is no basis to make a claim of causation.
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
Transcribed Image Text:Baseball owners believe that the more runs scored, the higher the attendance. Is there evidence that more fans attend games if the
teams score more runs? Data collected midway through the season indicate a correlation of 0.848 between runs scored and the number
of people at games.
a) Does the scatterplot indicate that it's appropriate to calculate a correlation? Explain.
O A. Yes, because the relationship between number of runs scored and attendance appears to be straight.
O B. Yes, because the association between the number of runs scored and attendance is positive.
37500-
OC. No, because there are too many outliers for a numerical correlation to be appropriate.
30000-
O D. No, because the number of runs scored and attendance are not quantitative variables.
b) Describe the association between attendance and runs scored.
22500-
320 360 400 440 480
O A. The association between attendance and runs scored is negative, straight, and moderate.
Runs
O B. The association between attendance and runs scored is positive, straight, and moderate.
OC. The association between attendance and runs scored is negative, straight, and strong.
O D. The association between attendance and runs scored is positive, straight, and weak.
c) Does this prove that the owners are right, that more fans will come to games if the teams score more runs?
O A. No, there is no evidence of an association between attendance and runs scored.
O B. Yes, there is évidence of an association between attendance and runs scored.
Oc. Yes, there is basis
make a claim of causation.
O D. No, there is no basis to make a claim of causation.
Click to select your answer.
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