An online marketplace retailer performed a study that compared the average domesticshipping time of 98 sellers with their overall seller satisfaction rating (as a percent). Thestudy yielded a sample correlation coefficient of r = -0.161. Test the claim that there isLno linear correlation between the seller's average shipping time and their overallsatisfaction rating at the 5% level of significance.T-Distribution Tablea. Calculate the test statistic.t=Round to three decimal places if necessary4SearchEIDSAMSUNGSUBMIT QUESTIONWSAVE PROGRESSSUBMIT a. Calculate the test statistic.Round to three decimal places if necessaryb. Determine the critical value(s) for the hypothesis test.14c. Conclude whether to reject the null hypothesis or not based on the test statistic.ReiertEntiSAMSUNGSUBMIT QUESTIONSAVE PROGRESSSUBMIT

The given sample correlation coefficient is -0.161.

Answered: An online marketplace retailer…

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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Statistics Question
The table lists weights (pounds) and highway mileage amounts (mpg) for seven automobiles. 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? 2425 Weight (Ib) Highway (mpg) 2725 2875 3480 4070 4090 3125 34 33 30 25 24 36 31 Which scatterplot below shows the data? O A. OB. C. O D. 40- 40- 40 20+ 2000 20- 2000 Weight (Ib) 20어 2000 20- 2000 Weight (Ib) 5000 5000 5000 5000 Weight (Ib) Weight (Ib) Is there a linear relationship between weight and highway mileage? O A. No, there appears to be no relationship. O B. Yes, as the weight increases the highway mileage increases. O C. No, there appears to be a relationship, but it is not linear. Click to select your answer. 4:21 PM a 17 梦 * v 6/4/2021 W 0 門 e Type here to search Chp ins prt sc delet fg ho ト f8 144 f6 10 f5 f4 IOI esc back & #3 $4 4 T. 6, 00 %24 (6 d) AamH 3. (B dw) Am
A study of new home prices was conducted in a neighborhood of 2000 homes. The median price of a new home is reported to be $172,400 and the mean price is reported to be $196,000. describe the distribution of new home prices, explaining the relationship between the given median and mean. How many new homes cost more than $172,400?
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 study was undertaken to see how accurate food labeling for calories on food that is considered reduced calorie. The group measured the amount of calories for each item of food and then found the percent difference between the measured and labeled amount of calories. The group also looked at food that was nationally advertised, regionally distributed, or locally prepared. Do the data indicate that at least one of the mean percent differences between the three groups is different from the others? The data is summarized in the table below. National Mean Standard Deviation Sample Size Local -2.1 Regional 27.1667 143.125 Fill in the hypotheses below: Ho: Select an answer Ha: Select an answer 10.3257 20.797 53.5922 20 12 8
Click this Video for Finding Correlation Coefficient by Using Formula. Yessica thought that there was a correlation between the amount of time students slept the evening before their final exam and their final exam grade. She took an SRS of 5 students in her class and recorded the sleep time the evening before their final exam, and their final exam score. Let the sleep time the evening before the final exam represents the explanatory variable, and the final exam score be the response variable. Below is a sample data set. x (hour) 8 9 3 9 1 2 3 4 5 Calculate the sample correlation coefficient (r) to three decimal places. r= 9 Why would we expect the correlation coefficient to be positive? As the sleep time increases, exam score increases As the sleep time increases, exam score decreases As the sleep time decreases, exam score increases There is no change in exam score to sleep time C E y (score) 91 94 51 100 90 C A
2. State whether the variables described have a positive correlation, a negative correlation, or no correlation. (a) Income and SAT scores (b) Length of a person's hair and how far they sit from the screen in a movie theater. (c) Hours of exercise per week and blood pressure.
It is generally believed that there is a relationship between a college’s acceptance rate and its graduation rate. I wanted to know how strong this relationship is within the top universities in the country so I collected the graduation rate and acceptance rate data of a randomly selected sample of universities from all the top U.S. universities (with an acceptance rate at or below 30%). The data set is in Tab Q2 of the Excel data file. a.) Create a scatter plot between the two variables using Excel. Paste the plot here and format it into an APA-styled “figure” (see Assignment Guides for APA format).Be sure to submit the Excel file that you used to create the scatter plot. b) Calculate the mean and standard deviation for the two variables separately. c) Calculate the Z scores for all the scores of the two variables, separately.Tips: It may help to prevent error and to increase clarity if the process and/or the answers (z scores) are listed in a table format. d) Calculate…
A pediatrician wants to determine the relation that may exist between a child's height and head circumference. She randomly selects 8 children, measures their height and head circumference, and obtains the data shown in the table. The pediatrician wants to use height to predict head circumference. Compute the linear correlation coefficient between the height and head circumference of a child. Height Head Circumference (inches) (inches) 27.5 25 (Round to three decimal places as needed.) 17.3 17.1 26 25.25 27.25 26.75 25.75 27 25 17.2 17 17.6 17.4 17.2 17.3 Enter your answer in the answer box and then click Check Answer. All parts showing Clear All Check Answer Type here to search TOUG Panasonic CF-54 CDSS-4852 TERMO TOGA O O O O D () Scre Loc PrtSc Num Lock F10 F11 F12 F7 F8 F9 SysRq F5 F6 F3 F4 A 8 F1 F2 Esc & 7 0 8 B 90 5 A2 24 近 %#3
Listed below are the 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 α=0.01. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) 31.65 53.83 87.10 103.64 60.34 109.80 Tip (dollars) 3.74 5.76 14.73 16.86 7.44 20.73 1. The linear correlation coefficient is r= 2. What are the null and alternative hypotheses? 3. The test statistic is t= 4. The P-Value is P=
Assume that you have paired values consisting of heights (in inches) and weights (in lb) from 40 randomly selected men. The linear correlation coefficient r is 0.594. Find the value of the coefficient of determination. What practical information does the coefficient of determination provide? Choose the correct answer below. O A. The coefficient of determination is 0.353. 64.7% of the variation is explained by the linear correlation, and 35.3% is explained by other factors. O B. The coefficient of determination is 0.647. 35.3% of the variation is explained by the linear correlation, and 64.7% is explained by other factors. O C. The coefficient of determination is 0.647. 64.7% of the variation is explained by the linear correlation, and 35.3% is explained by other factors. O D. The coefficient of determination is 0.353. 35.3% of the variation is explained by the linear correlation, and 64.7% is explained by other factors.
A university would like to describe the relationship between the GPA and the starting monthly salary of a graduate who earned a business degree from the university. The accompanying table shows the monthly starting salaries for eight graduates of the business school along with their corresponding GPAS. Determine the sample correlation coefficient between the starting salary and the GPA of a business graduate of the university. Click the icon to view the salary and GPA data. Starting salary and GPA data (Round to three decimal places as needed.) Starting Salary GPA Starting Salary GPA 2,500 3.1 3,100 3.7 2,800 3.4 2,900 3.9 2,300 2.6 2,000 2.5 2,600 3.5 2,400 3.2 4o5

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