Step 1: State the null and alternative hypotheses.Ho:p =v0H.:P#v 0(So we will be performing a two-tailedtest.)Part 2 of 4Step 2: Determine the features of the distribution used to test the significance of thecorrelation coefficient.To test the significance of the correlation coefficient, we will use a t-distributionwith8x degrees of freedom.Question Help: O Post to forum Can we infer a students score on their final exam based on how many class meetings they missed?The table below gives this information for 13 students. (Comma separated lists of the data are alsoprovided below the table to ease in copying the data to R.)Number of Missed Classes (x)Percent Score on Final Exam (y)50481462503783946.727464714736.6237959x: 4, 4, 4, 5, 3, 3, 6, 7, 4, 4, 6, 3, 7y: 50, 81, 62, 50, 78, 94, 72, 46, 71, 73, 62, 79, 59Conduct a hypothesis test with a 9% level of significance to determine whether or not there is asignificant linear correlation between the number of classes a student misses and their score on thefinal exam.Step 1: State the null and alternative hypotheses.Ho:p =v

Answered: Image /qna-images/answer/327fea5b-9b4d-4330-8927-7fa64bc93faf.jpg

x: 4, 4, 4, 5, 3, 3, 6, 7, 4, 4, 6, 3, 7 y: 50, 81, 62, 50, 78, 94, 72, 46, 71, 73, 62, 79, 59 Conduct a hypothesis test with a 9% level of significance to determine whether or not there is a significant linear correlation between the number of classes a student misses and their score on the final exam. Step 1: State the null and alternative hypotheses. Ho: pE Ha:p #v

x: 4, 4, 4, 5, 3, 3, 6, 7, 4, 4, 6, 3, 7 y: 50, 81, 62, 50, 78, 94, 72, 46, 71, 73, 62, 79, 59 Conduct a hypothesis test with a 9% level of significance to determine whether or not there is a significant linear correlation between the number of classes a student misses and their score on the final exam. Step 1: State the null and alternative hypotheses. Ho: pE Ha:p #v

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

Step 1: State the null and alternative hypotheses.
Ho:p =v0
H.:P#v 0
(So we will be performing a two-tailed
test.)
Part 2 of 4
Step 2: Determine the features of the distribution used to test the significance of the
correlation coefficient.
To test the significance of the correlation coefficient, we will use a t-distribution
with
8
x degrees of freedom.
Question Help: O Post to forum

Can we infer a students score on their final exam based on how many class meetings they missed?
The table below gives this information for 13 students. (Comma separated lists of the data are also
provided below the table to ease in copying the data to R.)
Number of Missed Classes (x)
Percent Score on Final Exam (y)
50
4
81
4
62
50
3
78
3
94
6.
72
7
46
4
71
4
73
6.
62
3
79
59
x: 4, 4, 4, 5, 3, 3, 6, 7, 4, 4, 6, 3, 7
y: 50, 81, 62, 50, 78, 94, 72, 46, 71, 73, 62, 79, 59
Conduct a hypothesis test with a 9% level of significance to determine whether or not there is a
significant linear correlation between the number of classes a student misses and their score on the
final exam.
Step 1: State the null and alternative hypotheses.
Ho:p =v

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