The weight (in pounds) and height (in inches) for a child were measured every few months over a two-year period. The results are given in the table. Using technology, what is the correlation coefficient -0.997 -0.503 Weight (x) 12 24 30 32 35 37 40 8 18 O 0.503 Height (y) 26 32 33 35 36 38 22 23 30 0.997
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- 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 linear correlation between ticket price and number of attendees. Use a significance level of 0.01 and round all values to 4 decimal places. Ticket Price 6 10 14 18 22 26 30 r= Ho: p= 0 Ha: p=0 Find the Linear Correlation Coefficient Find the p-value p-value= Attendence 151 146 146 145 The p-value is 138 137 137 O Less than (or equal to) a O Greater than a The p-value leads to a decision to Accept Ho Reject Ho Do Not Reject Ho The conclusion is There is insufficient evidence to make a conclusion about the 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 a significant linear correlation between ticket price and attendance.A pediatrician wants to determine the relation that may exist between a child's height and head circumference She randomly selects 8 children from her practice, measures their height and head circumference, and obtains the 27.5 data shown in the table. Complete parts (a) through (e) below. Click here to see the Table of Critical Values for Correlation Coefficient. Height (in.) Head Circumference (in.) O 17.4 25.75 26.75 25 17.1 17.1 16.9 27.5 17.5 26.75 17.2 17.1 25.75 26.75 17.3 (a) If the pediatrician wants to use height to predict head circumference, determine which variable is the explanatory variable and which is the response variable. Choose the corect answer below O The explanatory variable is head circumference and the response vanable is height O The explanatory variable is height and the response variable is head circumference (b) Draw a scatter diagram. Choose the correct graph below. O D. OA. B. Click to select your answer(s). VI 9:31 acer -> esc & backspace @ 2$ % 7 8 1 r…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 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…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 = 0.05. Based on these results, can you expect to get higher quality by purchasing a more expensive LCD television? Quality 76 74 71 70 69 68 65 62 62 60 59 Cost 27 24 12 11 21 27 30 38 24 21 11 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. OA. Ho: rs = 0 OB. Ho: rs #0 H₁: rs =0 H₁: rs #0 O C. Ho: Ps #0 H₁: Ps=0 Determine the correlation coefficient. 's (Round to three decimal places as needed.) Determine the critical value(s) of the correlation coefficient. D. Ho: Ps=0 H₁: Ps #0 (Round to three decimal places as needed. Use a comma to separate answers as needed.) Choose the correct answer below. O A. Fail to reject the…Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit . Use a significance level of 0.05 and round all values to 4 decimal places. Advertising Cost Profit 3 19 4 16 24 6 29 7 25 27 10 30 Ho: p = 0 На: р * 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is O Less than (or equal to) a O Greater than a The p-value leads to a decision to O Do Not Reject Ho O Accept Ho O Reject Ho The conclusion is O There is a significant negative linear correlation between advertising expense and profit. O There is a significant linear correlation between advertising expense and profit. O There is a significant positive linear correlation between advertising expense and profit. O There is insufficient evidence to make a conclusion about the linear correlation between advertising expense and…
- A food truck owner recorded the temperature at noon, in degrees Fahrenheit, and the number of bowls of soup sold during the lunch hour for a random sample of 5 days. The data are shown in the following table. Temperature (degrees Fahrenheit) 57 75 43 68 67 Number sold 17 12 20 8 13 The mean temperature of the sample is 62 degrees Fahrenheit, and the mean number sold is 14. What is the correlation between the temperature and the number sold? A -0.85 B -0.68 0.68 D 0.73 E 0.85Fifty-four wild bears were anesthetized, and their weights and chest sizes were measured. Results are showing in the graph below. IS there sufficient evidence to support the claim that there is a linear correlation between weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Correlation Results Correlation coeff r:0.963141 Critical r ±0.2680855 P-value (two-tailed) 0.000The 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.
- 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)Can you please check my workThe data in the table below show years of teaching experience and annual salary in dollars for 12 randomly selected mathematics instructors in Illinois colleges/ universities for the 2013/2014 school year. Is there a linear correlation between a mathematics instructor’s years of experience and his or her annual salary? Number of Years:7 9 6 7 11 12 11 3 3 7 9 1 Salary (in Dollars): 48,897 62,866 54,585 56,611 53,541 53,541 47,027 47,970 46,668 48,029 46,735 45,000