2. The owner of a car wants to study the relationship between the age of a car and its sellingprice. Listed below is a random sample of 12 used cars sold at a dealership during the lastyear. Determine the (a) Pearson correlation coefficient; (b) Spearman rank correlationcoefficient. Interpret these resultsCarAge (years)Selling Price($1000)19273118.1 6.0 3.64124.09 10 111012 65.0 10.0 7.6 8.0 8.06.05867788118.61268.0

Correlation is used to measure the association between the two numerical variables. There are two…

Answered: 2. The owner of a car wants to study…

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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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…
1. A professor is interested in how attendance is related to grades her class. She goes through her records and determines each student’s final average and the number of days absent. The scores for her sample are given in the table below. a. Construct a scatter plot of the relationship between final averages and the number of days absent. b. Is there a significant relationship between final averages and the number of days absent? Calculate and interpret the correlation and report it in proper APA format. c. Compute r2 for the data. What percent of the variability in final averages is accounted for by the number days absent?
Listed below are amounts of bills for dinner and the amounts of the tips that were left. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a = 0.01. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) Tip (dollars) 31.80 52.94 85.82 102.16 60.17 111.77 D 5.46 6.07 15.82 15.40 11.15 20.32 Construct a scatterplot. Choose the correct graph below. O A. O B. Oc. D. Q 25- 25- 25 0- 30 0- 30 Bill Amount ($) 0+ 30 Bill Amount (S) 0- 30 Bill Amount (S) 120 120 120 Bill Amount (S) 120 The linear correlation coefficient is r= 0.954 (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: p H,: P (Type integers or decimals. Do not round.) Tip Amount ($) ip Amount ($) Tip Amount ($) Tip Amount ($)
Susan, a personal trainer, was interested in whether or not there was a linear relationship between the number of visits her clients made to the gym each week and the average amount of time her clients exercised per visit. She took the following data. Client 1 2 3 4 5 6 Number of visits per week 1 3 4 2 3 5 Average time spent exercising per visit (hours) 2 1.5 1 2 2 0.30 Is the correlation coefficient significant? Group of answer choices No Yes Perhaps Insufficient Information to make a decision
find linear correlation coefficient, P value, and test statistic.
A group of university researchers wanted to determine the relationship that exists between the number of hours spent by a student in social media in a day (X) and their grade weighted average (Y). Twelve randomly selected students produced the following findings: Number of GWA Hours 4.0 95 8.0 85 87 89 91 85 89 86 84 96 82 85 7.0 6.5 5.5 9.0 4.0 10.0 7.5 2.0 12.0 9.0
The accompanying table shows the earnings per share (in dollars) and the dividends per share (in dollars) for 6 companies in a recent year. Complete parts (a) through (d) below. Click here to view the data table. Click here to view the table of critical values for the Pearson correlation coefficient. (a) Display the data in a scatter plot. Choose the correct.graph below. OA. OB. В. Oc. OD. 3- 9- Q Q 2- 6- 6- 3- 3- 04 3. Eamings per share (S) Eamings per share ($) 0. Eamings per share (S) Eamings per share (S) (b) Calculate the sample correlation coefficient r. - X Data Table (Round to three decimal places as needed.) (c) Describe the type of correlation, if any, and interpret the correlation in the context of the data. Earnings per share, x Dividends per share, y O 1.36 1 There is V linear correlation. 4.3 0.59 3.56 8.27 1.74 2.47 Interpret the correlation. Choose the correct answer below. 1.19 0.67 1.6 2.82 O A. Increases in companies' eamings per share cause their dividends per share…
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…
The data shown below consists of the price (in dollars) of 7 events at a local venue and the number of people who attended. Determine if there is significant negative linear correlation between ticket price and number of attendees. Use a significance level of 0.05 and round all values to 4 decimal places. Ticket Price Attendence 6. 109 10 114 14 139 18 142 22 139 26 132 30 154 Но: = 0 На: р Find the Linear Correlation Coefficient r = Find the p-value p-value = %3D The p-value is Less than (or equal to) a Greater than a The p-value leads to a decision to Reject Ho Аcсept Ho Do Not Reject Ho The conclusion is There is a significant linear correlation between ticket price and attendance. There is a significant negative linear correlation between ticket price and attendance. There is a significant positive linear correlation between ticket price and attendance. There is insufficient evidence to make a conclusion about the linear correlation between ticket price and attendance.
Example 3. Calculate Correlation Coefficient from the data given below by direct method i.e., without taking deviations of items from actual or assumed mean Roll No. of Students : Marks in Maths : Marks in Stat : 2 3 4. 48 35 17 23 47 45 20 40 25 45.
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)
7. A real estate agent believes that the monthly rents of houses depend on the size of the houses. A sample of seven houses is a residential area was selected and the information gathered is shown in table below. Compute the value of correlation coefficient. Interpret your finding. Monthly rent (RM '00), y Size ('00 square feet), X 12.11 10.61 16.07 9.41 15.06 17.08 9.14 14.12 8.16 12.09 14.91 7.17 16.13 11.15

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