An electronics retailer would like to investigate the relationship between the selling price of a certain digital camera model and the demand for it. The accompanying table shows the weekly demand for the camera in one particular market along with the corresponding price. Determine the sample correlation coefficient between the selling price and the demand for this camera. Demand Price 16 340 22 350 16 360 12 370 11 380 9 390 4 400

Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print lengths and heights of males. 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. Click to view the data on shoe print lengths and heights. Construct a scatterplot. Choose the correct graf Shoe Print Lengths versus Heights of Males O B. OD. 210- 200- 190- 180- 170- 160- 20 24 28 32 36 40 Shoe Print Length (cm) 210 200 190 180 170 160 2101 200- Shoe Print 190- Length (cm) Height (cm) 176.0 180- 170- 160- 20 24 28 32 36 40 31.4 28.9 181.2 31.5 194.5 Shoe Print Length (cm) 32.3 172.9 30.4 174.0 The linear correlation coefficient is r= 32.9 190.5 (Round to three decimal places as needed.) 31.0 176.6 30.8 170.0 30.5 171.9 32.3 175.5 30.5 200.1 32.6 199.3…

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 Attendence 6 170 10 151 14 171 18 160 22 172 26 179 30 130 Но: р %3D 0 Ha: p = 0 Find the Linear Correlation Coefficient Find the p-value p-value = The p-value is O Less than (or equal to) a O Greater than a

Jim and Larry run a soup stand. The data below represents the sales of soup that they had on 8 randomly selected days, along with the high temperature on that day.   a) Create a scatter diagram for this data set and comment on whether there is a positive or negative relationship between these variables.b) Calculate the correlation coefficient between temperature and sales.c) Does a linear relationship exist between these variables? Explain to me why or why not this is the case.d) Using excel, calculate the least squares regression equation for this data set. e) Using your equation, predict the soup sales on a day where the temperature is 29 degrees.f) Interpret the slope of this equation.g) Can we use this data set and regression equation to predict the sales on a day when the average temperature is 102 degrees? Why or why not?h) What is the R-squared for this equation? How do you interpret that R-squared?

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

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…

Men's and women's winning national championship bowling scores are shown for a random sample of years. Is there a linear relationship between the men's and women's winning scores? Men 823 858 812 832 833 826 Women 752 754 771 736 792 763 A. There is NOT a linear relationship because the linear correlation coefficient is close to 1 or -1. B. There is NOT a linear relationship because the linear correlation coefficient is close to 0. C. There is a linear relationship because the linear correlation coefficient is close to 0. D. There is a linear relationship because the linear correlation coefficient is close to 1 or -1. Click to select your answer. ?

Does a major league baseball team's record during spring training indicate how the team will play during the regular season? Over a six-year period, the correlation coefficient between a team's winning percentage in spring training and its winning percentage in the regular season is . Shown are the winning percentages for the American League teams during a season. Team SpringTraining RegularSeason   Team SpringTraining RegularSeason               Baltimore Orioles 0.409 0.424   Minnesota Twins 0.492 0.542 Boston Red Sox 0.426 0.588   New York Yankees 0.579 0.559 Chicago White Sox 0.411 0.535   Oakland A's 0.690 0.468 Cleveland Indians 0.578 0.492   Seattle Mariners 0.492 0.379 Detroit Tigers 0.578 0.459   Tampa Bay Rays 0.722 0.601 Kansas City Royals 0.540 0.461   Texas Rangers 0.640 0.491 Los Angeles Angels 0.724 0.619   Toronto Blue Jays 0.442 0.533   a. What is the correlation coefficient between the spring training and the regular season winning percentages…

An economist wants to determine whether there is a linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. The data are shown in the table below. c. Compute and interpret the correlation coefficient. d. Compute and interpret the coefficient of determination. e. Test for the significance of the linear relationship. Use a 0.05 level of significance. State your conclusion. Hint: Your conclusion is either of the following. • There is a significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. • There is no significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. GDP 1.6 3.6 4.9 1.1 0.9 2.9 2.7 2.3 1.6 1.5 (trillion dollars) Carbon Dioxide Emissions 428.2 828.8 1214.2 444.6 264 415.3 571.8 454.9 358.7 573.5 (millions of metric tons)

The following table compares the completion percentage and interception percentage of 55 NFL quarterbacks. Completion Percentage 58 59 62 65 66 Interception Percentage 4.5 4 3 2.5 1.5 Copy Data Determine if r is statistically significant at the 0.01 level.   Yes or No? the correlation coefficient is/ is not statistically significant.