A researcher wants to determine if there is a relationship between the number of hours spent by students on social media sites and self-esteem levels. A random sample of 10 statistics students was part of the study. Use manual calculations at α = 0.05 to calculate whether there is a significant relationship between the two variables. Show all your calculations.

Summarize the definitions for linear correlation, quadratic correlations and exponential correlations. Provide an example graph of each of the types of correlation along with your summarized definitions.

A researcher investigates the relationship between study habits and college achievement.  College seniors were administered the Inventory of Study Habits Survey (X) to measure study habits and the College BASE (Y) was used to measure overall college achievement.  The correlation between the study habits and achievement was found to be 0.784.  The researcher concluded that students with higher scores on the Study Habits Survey will always have higher college achievement scores on the College BASE.  Is the researcher's conclusion correct?  Why or why not?

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…

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…

State the empirical rule for variables.

Suppose the correlation between height and weight for adults is +0.40.What proportion (or percent) of the variability in weight can be explained by the relationship with height?

Please anwser using SPSS!

In a data set with 25 scores, if the value 16 occurs 12 times, what is its relative frequency?