The data in the table to the right are based on the results of a survey comparing -UO A.70-460+0110Time (min)QQO B.1100-6070Time (min)O C.470+60+0Commute TimeHCCScore110QQWell-BeingO D.110+OTH60Score70QQP(c) Determine the linear correlation coefficient between commute time and well-being score.r= (Round to three decimal places as needed.)(d) Does a linear relation exist between the commute time and well-being index score? Select the correct choice below and fill in the answer box to complete yourchoice. KThe data in the table to the right are based on the results of a survey comparingthe commute time of adults to their score on a well-being test. Complete parts (a)through (d) below.Click the icon to view the table of critical values of the correlation coefficient.C(a) which variable is likely the explanatory variable and which is the response variable?Commute Time(in minutes)4162335487298Well-BeingScore69.268.467.267.166.566.163.8O A. The explanatory variable is commute time and the response variable is the well-being score because well-being score affects the commute time score.OB. The explanatory variable is commute time and the response variable is the well-being score because commute time affects the well-being score.OC. The explanatory variable is the well-being score and the response variable is commute time because commute time affects the well-being score.O D. The explanatory variable is the well-being score and the response variable is commute time because well-being score affects the commute time.1

Commute time (in minutes) Well-Being Score 4 69.2 16 68.4 23 67.2 35 67.1 48 66.5 72…

Answered: The data in the table to the right are…

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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use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? FORECAST AND ACTUAL TEMPERATURES The table lists actual high temperatures and the high temperatures that were previously forecasted for these same days. The table includes data for ten different days near the author’s home. What does the result suggest about the accuracy of five-day predicted high temperatures?
Statistics Question
You wish to determine if there is a positive linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 66 20 75 32 44 31 44 36 19 23 65 29 61 22 58 25 71 27 Ho: ρ = 0Ha: ρ > 0 Find the Linear Correlation Coefficient r = Find the p-value p-value =
Need only a handwritten solution only (not a typed one).
(e)
You wish to determine if there is a positive linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 64 32 55 30 72 36 34 30 31 18 16 29 21 22 32 18 46 24 46 31 Ho: ρ = 0Ha: ρ > 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Greater than αα Less than (or equal to) αα The p-value leads to a decision to Do Not Reject Ho Reject Ho Accept Ho The conclusion is There is a significant linear correlation between driver age and number of driver deaths. There is a significant negative linear correlation between driver age and number of driver deaths. There is a significant positive linear correlation between driver age and number of driver deaths. There is…
A magazine tested LCD televisions. The table below shows the overall quality score and cost in hundreds of dollars. Use the rank correlation coefficient to test for a correlation between the two variables. Use a significance level of x=0.01. Based on these results, can you expect to get higher quality by purchasing a more expensive LCD television? Quality 78 77 73 71 68 65 64 62 Cost 26 29 36 23 21 10 62 59 55 12 10 21 26 23 Click the icon to view the critical values of Spearman's rank correlation coefficient. Determine the null and alternative hypotheses for this test. Choose the correct answer below. O A. Ho: rs = 0 OB. Ho: Ps #0 H₁: Ps=0 H₁: rs #0 OC. Ho: Ps = 0 H₁: Ps #0 C Determine the correlation coefficient. rs = (Round to three decimal places as needed.) Determine the critical value(s) of the correlation coefficient. O D. Ho: rs #0 H₁: rs=0 (Round to three decimal places as needed. Use a comma to separate answers as needed.) Choose the correct answer below. A. Reject the null…
The data in the table to the right are based on the results of a survey comparing the commute time of adults to their score on a well-being test. Complete parts (a) through (d) below. LOADING... Click the icon to view the table of critical values of the correlation coefficient. a) Which variable is likely the explanatory variable and which is the response variable? Critical Values for Correlation Coefficient n 3 0.997 4 0.950 5 0.878 6 0.811 7 0.754 8 0.707 9 0.666 10 0.632 11 0.602 12 0.576 13 0.553 14 0.532 15 0.514 16 0.497 17 0.482 18 0.468 19 0.456 20 0.444 21 0.433 22 0.423 23 0.413 24 0.404 25 0.396 26 0.388 27 0.381 28 0.374 29 0.367 30 0.361 n (a) Which variable is likely the explanatory variable and which is the response variable? The explanatory variable is…
Susan, a personal trainer, was interested in whether or not there was a linear relationship between the number of visits her clients made to the gym each week and the average amount of time her clients exercised per visit. She took the following data. Client 1 2 3 4 5 6 Number of visits per week 1 3 4 2 3 5 Average time spent exercising per visit (hours) 2 1.5 1 2 2 0.30 Is the correlation coefficient significant? Group of answer choices No Yes Perhaps Insufficient Information to make a decision
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For the accompanying data set, (a) draw a scatter diagram of the data, (b) by hand, compute the correlation coefficient, and (c) determine whether there is a linear relation between x and y. Click here to view the data set. Click here to view the critical values table. Critical values for the correlation coefficient Critical Values for Correlation Coefficient Data set 3 0.997 4 0.950 2 4 6. 6. 7 0.878 0.811 y 4 8. 12 14 19 7 0.754 8 0.707 0.666 10 0.632 11 0.602 12 0.576 13 0.553 14 0.532 15 0.514 16 0.497 17 0.482 18 0.468 19 0.456 20 0.444 21 0.433 22 0.423 23 0.413 24 0.404 25 0.396 26 0.388 27 0.381 28 0.374 29 0.367 30 0.361 Print Done n
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. Click here to view the data table. Click here to view the table of critical values for the Pearson correlation coefficient. Data table Critical values for the pearson correlation coefficient (a) Display the data O A. Age, x Vocabulary size, y Critical Values for the 1 6 3000- 2400- 1800- 1200- Pearson Correlation Coefficient 210 3 590 4 1300 The correlation is significant when the absolute value of is greater than the value in the table. 600- 2200 6 4 6 0 2 Age (year 2600 a = 0.05 0.950 a = 0.01 0.990 4 6 8 years) 3 680 4 2100 0.878 0.959 (b) Calculate the sa 280 6 0.811 0.917 7 0.754 0.875 4 1100 0.834 0.798 8 0.707 (Round to three de 6. 2300 0.666 10 0.632 0.765 (c) Describe the ty 11 0.602 0.735 12 0.576 0.708 There is 13 0.553 0.684 Done 0.661 0.532 0.514 0.497 Print 14 15 0.641 Interpret the correla 16 0.623 17 0.482 0.606 O A. As age…

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