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- 8.A group of university researchers wanted to determine the relationship that exists between the number of hours spent by a student in social media in a day (X) and their grade weighted average (Y). Twelve randomly selected students produced the following findings: Number of GWA Hours 4.0 95 8.0 85 87 89 91 85 89 86 84 96 82 85 7.0 6.5 5.5 9.0 4.0 10.0 7.5 2.0 12.0 9.0A 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…
- Which of the following correlation coefficients indicate the strongest relationship between two variables? A .20 B .87 C .80 D -.956. Which of these relationships would be better described with a Spearman's rank coefficient than with a Pearson's coefficient? a. The association between income and educational attainment (measured in years of school) b. The association between hours of sleep and score on an exam C. The association between years aged and price of wine d. The association between ice cream sales and crime rates e. The association between number on NY Times Best Seller List and copies of book soldIf when measuring two quantitative variables on an individual, we find that increases in the first variable x correspond to decreases in the second variable y, we say that A. there is a positive association between the two variables. b. there is a negative association between the two variables. c. there is no correlation between the two variables. d. there is a cause-and-effect relationship between the two variables.
- e. Compute the covariance and correlation coefficient r between the right tire pressure. f. How do you know the relationship between pressure in the left and right tires is positive. g. What value would a correlation coefficient (r) be close to if there was no (linear) relationship between the 2 tire pressures?A statistic teacher recorded the Math and Science test scores of twelve students from one section. Using 0.05 as the level of significance, is there a significant relationship between the test scores in Mathematics and Science? Student number Math Scores (X) Science Scores (Y) 1 18 20 2 16 18 3 11 12 4 15 17 5 15 15 6 11 14 7 11 12 8 13 14 9 8 10 10 9 13 11 13 12 12 7 96. Which of the following are true? Select all that apply. a. The coefficient of determination is the proportion of variation in the response variable that is explained by the regression line. b. We often use the symbol r to represent the coefficient of determination. c. In simple linear regression, the coefficient of determination equals the square of the linear correlation coefficient r. d. The closer the regression line comes to the data points, r should go to eleven.
- 5If the linear correlation coefficient between the weights (in kg) and heights (in inches) of 6 randomly selected males is 0.95, then 95% of the variation in weights of males can be explained by the linear correlation between height and weight? 1. True 2. FalseA psychologist has calculated the correlation between two variables as 0.9. Which of the following statements is correct? a. The average value of y changes by 0.9 when x is increased by 1. b. The average value of x changes by 0.9 when y is increased by 1. c. The explanatory variable ( x ) explains 0.9 of the variation in the response variable ( y ) d. The explanatory variable ( x ) explains 0.81 of the variation in the response variable ( y )A statistic teacher recorded the Math and Science test scores of twelve students from one section. Using 0.05 as the level of significance, is there a significant relationship between the test scores in Mathematics and Science? Student number Math Scores (X) Science Scores (Y) 1 18 20 2 16 18 3 11 12 4 15 17 5 15 15 6 11 14 7 11 12 8 13 14 9 8 10 10 9 13 11 13 12 12 7 9 What does the value of r means? a) moderate positive correlation b) perfect positive correlation c) low positive correlation d) very high positive correlation e) moderate negative correlation
