A study was conducted to determine whether the final grade of a student in an introductory psychology course is linearly related tohis or her performance on the verbal ability test administered before college entrance. The verbal scores and final grades for 10 studentsare shown in the table below..Student 1 2 3 4 5 6 7 8 9 1038 33 52 29 25 7661 66 73 70ScoreGrade 7466 64 9482777463 63 100Find the following:(a) The correlation coefficient: r =(b) The least squares line: y =-(c) The predicted grade for the eighth student:(d) The residual for the eighth student:⠀⠀

Student Score Grade 1 38 74 2 33 66 3 52 64 4 29 94 5 25 82 6 76 77 7 61 74 8 66 63…

Answered: A study was conducted to determine…

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 student of Engineering conducted a research to determine the correlation between performance of 2 lathes in the workshop. Assessments were conducted on weekly basis, and the following data were obtained. Calculate the coefficient of correlation using Karl Pearson's method, and discuss the level of the relationship. Table 2. The performance of the lathes on weekly basis. Week(s) 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th Lathe A 42 48 40 28 46 90 28 56 16 22 Lathe B 56 78 72 24 60 42 36 82 28 34 良

Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? 484 534 Lemon Imports Crash Fatality Rate 229 15.8 266 15.7 359 15.5 15.3 14.8 What are the null and alternative hypotheses? OA. H₂: p=0 H₁: p0 OD. Ho: p*0 H₁: p=0 OC. Ay 17+ 16- ܕ 15 14+ HHHH ▬▬▬▬▬ % do 6 200 400 600 G O D. Aу 17- 16 :|||||||* 15- 14+ 0 H °. C M o do 200 400 600 Q C sufficient evidence to support the claim that there is a linear correlation between lemon imports and crash fatality rates for a significance level of a = 0.05.
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…
The data obtained in a study on the number of absences in virtual class and the final grades of seven randomly selected students from a mathematics class. The data are shown below. To determine the significance of the correlation coefficient at 0.05 level of significance, what is the calculated or computed value (CV)? Number of absences x Final in a virtual class grade y 82 6 86 15 43 9. 74 58 5 90 78 a. -1.59 b. 2.32 C. -2.32 d. 1.59
You have been asked to find if there is a correlation between the amount of calories per serving in a bowl of cereal versus the amount of sugar (in grams) in the cereal. The following data has been given Which variable is the predictor and which variable is the response Sugar Calories 18 200 23 210 12 170 12 190 37 220 19 175 23 201 22 210 32 210 11 190 11 197 29 205
Imagine that a professor of sociology has two teaching assistants (TAS) who will help him grade assignments for the duration of the semester. The professor wants to make sure that he and the TAS are well calibrated with one another, so he has all three of them grade the first assignment independently. Because the professor grades every assignment on a curve, he first converts the students' scores to z-scores for each grader. The following table shows the z-scores for a population of 10 students in his class for each grader. Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Student 7 Student 8 Student 9 Student 10 Professor Teaching Assistant #1 Teaching Assistant #2 0.70 0.83 -0.98 2.21 -0.54 0.43 -1.03 -0.01 -0.54 -1.07 1.27 -0.64 0.38 0.80 -1.34 0.10 -2.09 0.85 0.48 0.20 1.27 -1.55 -0.14 0.92 -1.06 0.30 -1.50 1.14 0.57 0.04 The professor is going to use the z-scores to calculate the correlation coefficient between his scores and those of his TAS. To calculate the…
The accompanying table shows the ages (in years) of 11 children and the numbers of words in their vocabulary. Complete parts (a) through (d) below. Age, x Vocabulary size, y 1 5 2 240 3 560 4 1200 5 1900 6 2600 3 540 5 2200 2 280 4 1300 6 2300 (a) Display the data in a scatter plot. (b) Calculate the sample correlation coefficient r. (c) Describe the type of correlation, if any, and interpret the correlation in the context of the data. (d) Use the table of critical values for the Pearson correlation coefficient to make a conclusion about the correlation coefficient. Let α=0.01.
A random sample of ten professional athletes produced the following data. The first row is the number of endorsements the athlete has and the second row is the amount of money made (in millions of dollars) by the athlete.   What is the linear correlation coefficient? Round to three decimal places. Number of Endorsements 0 3 2 1 5 5 4 3 0 4 Profit (in Millions) 2 8 7 3 13 12 9 9 3 10
grocery store manager did a study to look at the relationship between the amount of time (in minutes) customers spend in the store and the amount of money (in dollars) they spend. The results of the survey are shown below. Time 12 26 5 28 11 24 20 21 16 Money 37 84 34 84 53 92 72 92 75 Find the correlation coefficient: r=r= Round to 2 decimal places. The null and alternative hypotheses for correlation are:H0:H0: P == 0 H1:H1: P ≠≠ 0 The p-value is: (Round to four decimal places) r2 = (Round to two decimal places)
Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? 484 534 Lemon Imports Crash Fatality Rate 229 15.8 266 15.7 359 15.5 15.3 14.8 OC. Ho: p=0 H₁: p=0 Construct a scatterplot. Choose the correct graph below. O A. Ay 17+ 16- 15- 14- 0 200 400 600 Q Q The linear correlation coefficient is r= (Round to three decimal places as needed.) The test statistic is t- (Round to three decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value is OB. Ax 17+ 16- 15 14+ 6 than the significance level 0.05, there % 0 200 400 400 600 Q Q G OD. H₂:p#0 H₁:…
Milan.m.m
What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman's weight? The time on the phone and weight for 8 women are shown in the table below. Time 82 24 64 52 82 12 77 89 Pounds 181 125 156 142 158 103 148 161 Find the correlation coefficient: r=r= Round to 2 decimal places. The null and alternative hypotheses for correlation are:H0:H0: ? μ ρ r == 0H1:H1: ? r ρ μ ≠≠ 0 The p-value is: (Round to four decimal places) Use a level of significance of α=0.05α=0.05 to state the conclusion of the hypothesis test in the context of the study. There is statistically insignificant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the use of the regression line is not appropriate. There is statistically insignificant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone. There…

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