To examine the linear correlation between adult age and weight, data was collected from 10 adults. See the table below. Age Weight (Years) (pounds) 28 139 31 192 32 123 33 206 39 210 41 219 45 184 48 122 50 173 55 172 Does this result suggest that the correlation is statistically significant? Use a = 0.10. Important Note: Round your value for r to three decimals before computing the STS. DO NOT use the built- in LinRegTTest on a calculator because you might get marked wrong. When computing the P-value, use the rounded STS. 1. Select the correct statement: O Even if the correlation is found to be statistically significant, that does not necessarily mean that changes in x cause changes in y Olf the correlation is found to be statistically significant, that means that changes in x cause changes in y The hypotheses are: O Ho:r 2 0; Ha:r < 0 O Ho:p 2 0; Ha:p<0 Ho:r <0; Ha:r>0 O Ho:p = 0; Ha:p# 0 Ho:r = 0; Ha:r #0 O Ho:p S0; Ha:p> 0 %3D
To examine the linear correlation between adult age and weight, data was collected from 10 adults. See the table below. Age Weight (Years) (pounds) 28 139 31 192 32 123 33 206 39 210 41 219 45 184 48 122 50 173 55 172 Does this result suggest that the correlation is statistically significant? Use a = 0.10. Important Note: Round your value for r to three decimals before computing the STS. DO NOT use the built- in LinRegTTest on a calculator because you might get marked wrong. When computing the P-value, use the rounded STS. 1. Select the correct statement: O Even if the correlation is found to be statistically significant, that does not necessarily mean that changes in x cause changes in y Olf the correlation is found to be statistically significant, that means that changes in x cause changes in y The hypotheses are: O Ho:r 2 0; Ha:r < 0 O Ho:p 2 0; Ha:p<0 Ho:r <0; Ha:r>0 O Ho:p = 0; Ha:p# 0 Ho:r = 0; Ha:r #0 O Ho:p S0; Ha:p> 0 %3D
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 2BGP
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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:To examine the linear correlation between adult age and weight, data was collected from 10 adults. See
the table below.
Age
Weight
(Years)
(pounds)
28
139
31
192
32
123
33
206
39
210
41
219
45
184
48
122
50
173
55
172
Does this result suggest that the correlation is statistically significant? Use a = 0.10.
Important Note: Round your value for r to three decimals before computing the STS. DO NOT use the built-
in LinRegTTest on a calculator because you might get marked wrong. When computing the P-value, use the
rounded STS.
1. Select the correct statement:
O Even if the correlation is found to be statistically significant, that does not necessarily mean that
changes in x cause changes in y
O If the correlation is found to be statistically significant, that means that changes in x cause changes
in y
The hypotheses are:
O Ho:r 2 0; Ha:r < 0
O Ho:p 2 0; Ha:p< 0
O Ho:r <0; Ha:r> 0
O Ho:p = 0; Ha:p+ 0
O Ho:r = 0; Ha:r # 0
O Ho:p<0; Ha:p > 0
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Transcribed Image Text:2. This is a O twoO leftO right tailed test and the distribution used is
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The Degrees of Freedom are
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ON/A; this is a Z-test
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3. The STS (round to 3 decimals) is:
The P-value (round to 4 decimals) is:
4. The decision at a = 0.10 is:
O Reject Ho since P > a
O Reject Ho since P < a
O Do not reject Ho since P > a
O Do not reject Ho since P<a
The conclusion is:
O There is sufficient evidence to conclude that there is a statistically significant linear correlation
O There is insufficient evidence to conclude that there is a statistically significant linear correlation
O There is insufficient evidence to conclude that there is not a statistically significant linear
correlation
O There is sufficient evidence to conclude that there is not a statistically significant linear correlation
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