The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccerplayers are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r= 0.707. At a = 0.05, is there enough evidence toconclude that there is a significant linear correlation between the variables?: Click the icon to view the soccer player data,Determine the null and alternative hypotheses.Ho:p = 0H:p + 0Determine the critical value(s).to = - 2.228,2.228(Round to three decimal places as needed. Use a comma to separate answers as needed.)Determine the standardized test statistic.(Round to three decimal places as needed.)

For the given data test statistic (t ) =?

Answered: The maximum weights (in kilograms) 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 random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
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=
The trend of thinner beauty pageant winners has generated charges that the contest encourages unhealthy diet habits among young women. Listed below are body mass indexes (BMI) for beauty pageant winners from two different time periods. Find the coefficient of variation for each of the two sets of data, then compare the variation. The coefficient of variation for the BMI's of beauty pageant winners from the 1920s and 1930s is %
For a sample of eight bears, researchers measured the distances around the bears' chests and weighed the bears. Minitab was used to find that the value of the linear correlation coefficient is r = 0.862. Using a = 0.05, determine if there is a linear correlation between chest size and weight. What proportion of the variation in weight can be explained by the linear relationship between weight and chest size? Click here to view a table of critical values for the correlation coefficient. a. Is there a linear correlation between chest size and weight? O A. No, because the absolute value of r exceeds the critical value of 0.707. O B. Yes, because r falls between the critical values of -0.707 and 0.707. O C. Yes, because the absolute value of r exceeds the critical value of 0.707. O D. The answer cannot be determined from the given information. b. What proportion of the variation in weight can be explained by the linear relationship between weight and chest size? (Round to three decimal…
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.
The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r=0.692. At a =0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? E Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho: p o Maximum Weights and Jump Heights Ha: p o Maximum Jump height, y Determine the critical value(s). weight, x 190 60 to = (Round to three decimal places as needed. Use a comma to separate answers as needed.) 185 56 155 55 Determine the standardized test statistic. 180 59 175 55 t= (Round to three decimal places as needed.) 170 65 What is the conclusion? 150 52 160 52 Ho. There V enough evidence at the 5% level of significance to conclude that there is a significant linear correlation between the…
For a data set of chest sizes (distance around chest in inches) and weights (pounds) of twelve anesthetized bears that were measured, the linear correlation coefficient is r= 0.276. Use the table available below to find the critical values of r. Based on a comparison of the linear correlation coefficient r and the critical values, what do you conclude about a linear correlation? Click the icon to view the table of critical values of r. The critical values are Table of Critical Values of r IT Number of Pairs of Data n Critical Value of r 4 0.950 0.878 0.811 7 0.754 0.707 0.666 10 0.632 11 0.602 12 0.576
determine whether suicide and homicide rates in metropolitan areas around the country are correlated. a sample of 10 metropolitan areas with their rates (number per 100,000), of suicide and homicide. computed the correlation coefficient of 0.70.
For a data set of chest sizes (distance around chest in inches) and weights (pounds) of seven anesthetized bears that were measured, the linear correlation coefficient is r=0.147. Use the table available below to find the critical values of r. Based on a comparison of the linear correlation coefficient r and the critical values, what do you conclude about a linear correlation? LOADING... Click the icon to view the table of critical values of r. The critical values are nothing. (Type integers or decimals. Do not round. Use a comma to separate answers as needed.) Since the correlation coefficient r is ▼ between the critical values in the right tail above the positive critical value in the left tail below the negative critical value , there ▼ is not is sufficient evidence to support the claim of a linear correlation.
Complete the following instructions:i. Identify the independent and dependent variables.ii. Calculate and interpret the Pearson correlation coefficient r for the paired data. Be sure to indicate if the correlation is positive or negative, and whether it is strong, moderate, or weak, or if there does not appear to be any significant correlation. A researcher for a gasoline retailer examines the relationship between the volume of gasoline purchased in kL(i.e. 1000 L) compared to the price of gasoline (in $/L), over a course of several days, to see if there is a correlation between the data: Amount of Gasoline Purchased Price of Gasoline 2.257 1.079 3.126 1.015 2.793 1.046 4.671 0.973 2.137 1.021 5.916 0.939 2.775 0.995 4.88 0.927 3.162 0.964 7.498 0.899 2.971 0.982 3.596 0.945 1.372 1.129 3.961 1.059 i. Independent Variable: Dependent Variable: ii. Pearson correlation coefficient (r): Round to 3 decimal…
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:…
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=0.05. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) 33.75 52.16 86.46 91.98 62.80 95.27 Tip (dollars) 4.16 4.74 7.99 15.64 11.53 9.20 The linear correlation coefficient is r= (Round to three decimal places as needed.) Determine the null and alternative hypotheses. (Type integers or decimals. Do not round.) The test statistic is t= (Round to two decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value of the linear correlation coefficient is ▼ greater than or…

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