An exercise scientist wants to know if there is a relationship between explosive leg power and standing jump height.  To determine if a relationship exists, a group of 30 participants' (N = 30) Leg power was measured  by recording each participants' single squat weight max (in pounds). Next, each participant was asked to perform a standing jump and their Jump height was recorded (in meters). Using the variables “Leg power” and “Jump height”, conduct a Pearson's Correlation, at α = 0.05, to determine if leg power and jump height are correlated   Interpret r. What type of correlation exists between leg strength and jump height?   A. A negative correlation B. No correlation C. A positive correlation D. We cannot know based on the available information

For each of a number of cities across Canada, the number of people with Cantonese as a mother tongue and the number of people with Mandarin as a mother tongue were rocorded. A scatterplot of the data is shown in the figure below. The correlation between the number of Cantonese speakers in a city aud the number of Mandarin speakers is 0.980. Do you think this correlation is a reasonable summary of the relationship? Why, or why not? (a) If the two largest cities (Toronto and Vancouver) were removed, the correlation would be even higher. (b) No, because there are outliers and/or influential points. (c) Yes, because the relationship is more or less linear. (d) No, because the relationship is clearly curved. (e) Yes, because there are no influential points.

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=0.707. At & = 0.05, is there enough evidence to conclude 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 = 0 Ha:p # 0 Determine the critical value(s). to = (Round to three decimal places as needed. Use a comma to separate answers as needed.)

Please explain

A study was done asking people how much money they spend per month on their natural gas bill and how much money per month they spend on their electric bill. The correlation r was found to be 0.94 and the p- value for correlation was 0.0003. Then a person with a high natural gas bill will also have a high electric bill. O true false

A researcher measures GPA and height for a group of high school students. What kind of correlation is likely to be obtained for these two variables?​

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…

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…

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…

A set of n=15 pairs of scores (x and y values) has Ssx =200, Ssy=60, and Sp=30.What is the Pearson correlation for these data?