6. Two separate tests are designed to measure a student's ability to solve problems. Several students are randomly selected to take both tests and the results are given below. (x)TestA 48 52 58 44 43 43 40 51 59 (y)TestB| 73 67 73 59 58 56 58 64 74 a. Plot the scatter diagram below. Label x and y axes. Do a rough sketch. b. Find the value of the linear correlation coefficient r by the TI83 shortcut- state calculator screen name c) Test the claim of no linear relation by the TI83 p-value method. a .05 claim null hypothesis. alternative hypothesis... Calculator Screen Name..... test statistic pvalue/alpha comparison.….... decision Conclusion d) Find the estimated equation of the regression line by T183 shortcut e) Plot the regression line on the scatter diagram in part a). f) Assuming a significant linear correlation, predict the score a student would get on Test B, given he got a 90 on Test A. g) What percentage of the total variation can be explained by the regression line

6. Two separate tests are designed to measure a student's ability to solve problems. Several students are randomly selected to take both tests and the results are given below. (x)TestA 48 52 58 44 43 43 40 51 59 (y)TestB| 73 67 73 59 58 56 58 64 74 a. Plot the scatter diagram below. Label x and y axes. Do a rough sketch. b. Find the value of the linear correlation coefficient r by the TI83 shortcut- state calculator screen name c) Test the claim of no linear relation by the TI83 p-value method. a .05 claim null hypothesis. alternative hypothesis... Calculator Screen Name..... test statistic pvalue/alpha comparison.….... decision Conclusion d) Find the estimated equation of the regression line by T183 shortcut e) Plot the regression line on the scatter diagram in part a). f) Assuming a significant linear correlation, predict the score a student would get on Test B, given he got a 90 on Test A. g) What percentage of the total variation can be explained by the regression line

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Description: 6. Two separate tests are designed to measure a student's ability to solve problems.Several students are randomly selected to take both tests and the results are givenbelow.(x)TestA 48 52 58 44 43 43 40 51 59(y)TestB| 73 67 73 59 58 56 58 64 74a. Pl

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

Inverse Normal Distribution

The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.

Mean, Median, Mode

It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.

Z-Scores

A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.

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Question

6. Two separate tests are designed to measure a student's ability to solve problems.
Several students are randomly selected to take both tests and the results are given
below.
(x)TestA 48 52 58 44 43 43 40 51 59
(y)TestB| 73 67 73 59 58 56 58 64 74
a. Plot the scatter diagram below. Label x and y axes. Do a rough sketch.
b. Find the value of the linear correlation coefficient r by the TI83 shortcut- state
calculator screen name
c) Test the claim of no linear relation by the TI83 p-value method. a
.05
claim
null hypothesis.
alternative hypothesis...
Calculator Screen Name.....
test statistic
pvalue/alpha comparison.…....
decision
Conclusion
d) Find the estimated equation of the regression line by T183 shortcut
e) Plot the regression line on the scatter diagram in part a).
f) Assuming a significant linear correlation, predict the score a student would get on
Test B, given he got a 90 on Test A.
g) What percentage of the total variation can be explained by the regression line

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