A2. A study of test results at different schools shows that as the student-to-teacher ratio increases the average test result tends to decrease, although the relationship is quite weak. Which of the following is plausible value for the correlation between student-to- teacher ratio and average test results? B -0.3 A -0.9 C -0.01 D 0.3 E 0.9
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- 4 2. Which of the following correlation coefficients would correspond to a strong linear relationship in a data set? OA. O OB. 0.5 O c. 0.9 OD 100An r value of .8 indicates a strong positive correlation. True FalseA student wants to compute the correlation coefficient with two data pairs. What value or values of r should he expect? A. -1 B. 1 C. 0 D.|1| Given a set of paired data (X,Y), if Y is dependent on X, then what value of a correlation coefficient wouldyou expect? A. -1 B. 1 C. 0 D.|1|
- Provide answer.. 26 You are given : Variance of X = 9 The Regression Equations are 8 X - 10 Y + 66 = 0 40 X - 18 Y = 214 Find (1) Average values of X andY (ii) Correlation Coefficient between the two variables (iii) Standard Deviation of Y.A survey was taken in 2018 that asked people about their saving habits. Researchers wanted to know if people who saved more also spent less. The scatterplot below shows their results when comparing two variables: the amount people reported that they put into savings each month, and the amount they reported that they spent on clothes. The researchers found the correlation coefficient for this data to be -0.239. Which of the following is true about these variables? a. There is no relationship between savings and money spent on clothes each month.b. There is a weak, positive linear relationship between savings and money spent on clothes each month.c. There is a perfect, negative linear relationship between savings and money spent on clothes each month.d. There is a weak, negative linear relationship between savings and money spent on clothes each month.
- If the linear association between two numerical variables is studied and the correlation coefficient is 0.32, it can be concluded that:a. The relationship between the variables is inverse and weak. b. The percentage of variability observed in the data that is explained by the error is 89.76%. c. The percentage of observed variability in the data that is explained by the model is 32%. d. None is correct Please explain clearly, thank you8.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 9.0
- 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…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 sold