Solve the following statistical problems using correlation. 1. The final test and exam averages for 20 randomly selected students taking a course in engineering statistics and a course in operations research follow. Assumethat the final averages are jointly normally distributed.Find the regression line relating the statistics final average to the OR final average.Statistics8675697590OR8081758192Statistics9483867165OR9580817672Statistics8471629083OR8572659381Statistics7571768497OR7073728098(c) Manually compute for the correlation coefficient.

Answered: 1. The final test and exam averages for…

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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A professor at the University of New Hampshire was interested in evaluating the effect of the unemployment rate on the incarceration rate. Using data from 50 states and the District of Columbia (n = 51), the researcher computed the Pearson’s correlation coefficient between the two variables. The results are presented below. Correlations Incarceration Unemployment Incarceration Pearson Correlation 1 .209 Sig. (2-tailed) .142 N 51 51 Unemployment Pearson Correlation .209 1 Sig. (2-tailed) .142 N 51 51 Using an alpha level of 0.05 and the four steps of the hypothesis testing process, test the research hypotheses that unemployment increases incarceration. Step 3 Step 4 Based on your decision to step 4 what type of error might you be making?
A biologist looked at the relationship between number of seeds a plant produces and the percent of those seeds that sprout. The results of the survey are shown below. Seeds Produced 68 56 61 Sprout Percent 60.6 69.2 = 0 48 64.7 64.6 #0 a. Find the correlation coefficient: b. The null and alternative hypotheses for correlation are: H₂: ? H₁: 2 The p-value is: 63 64.1 40 Round to 2 decimal places. 63 62 65.1 68.4 84 (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. O There is statistically significant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the regression line is useful. O There is statistically insignificant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. O There is statistically significant…
Solve the second one
This is an exercise. What is Pearson’s correlation coefficient? And how to use it?
A2. A study of test results at different schools shows that as the student-to-teacher ratio increases the average test result tends to decrease, although the relationship is quite weak. Which of the following is plausible value for the correlation between student-to- teacher ratio and average test results? A -0.9 B -0.3 C -0.01 D 0.3 E 0.9
Squaring the Pearson correlation coefficient (r2) tells us that
A past STAT 200 student tells you that there is a very strong positive linear association between the STAT 200 final exam score and the WeBWork Assignment total. What is a plausible value of the correlation coefficient (r)? OA. -1.1 OB. 0.95 OC. -0.95 OD. 0.01 OE. 1.1 OF. 0.56
The scatterplot below shows the relationship between two random variables X and Y. (a) Is the correlation a good metric for describing the relationship between X and Y for these data? Why or why not? Regardless of your answer suppose you calculated the sample correlation between X and Y and found that r = -0.15. Explain in one sentence what this means. (b) If, as noted in (a), r = -0.15 then what is the value of the correlation between 2X and 5Y? (c) Based on (b) draw your best approximation to the least squares regression line that fits the data above. Also, make a rough sketch of the corresponding residual plot.
Which correlation value suggests the strongest correlation? 0.7 -0.1 O -0.8 O 0.4
Milan.m.m
A materials engineer wants to understand the relationship between the strength of plastic cases and the temperature at which the strength measurements were made. The engineer collects several samples from the manufacturer and records the following observations. Using the data below and what you have learned in Forecasting, determine the following (use four decimal places for values): 1) Which is the explanatory variable? 2) What would be the value of the coefficient of correlation between the two variables? 3) What would be the complete interpretation of the relationship between the two variables (consider sign and value)?

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