Consider this set of bivariate data: (10, 23), (30, 85), and (40, 96). Calculate the covariance.
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Consider this set of bivariate data: (10, 23), (30, 85), and (40, 96). Calculate the
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- 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 value of the correlation r = (x,y) for the information would be: n = 8, Sum(x) = 609, Sum(y) = 504, Sum (x)^2 = 47995, Sum (y)^2 = 32954, and Sum (xy) = 395650 Choose answer from the following: a. 0.855 b.0.174Find the new data point (x,y) in which x=2 from the data points (1,3) and (4,12)
- What information is provided by r2? What are the primary uses of partial correlations?A nutritionist collects data from 25 popular breakfast cereals. For each cereal, the number of calories per serving is plotted on the x-axis against the number of milligrams of sodium on the y-axis. The value of r for the resulting scatterplot is 0.83. How would the value of the correlation coefficient, r, change if sodium was plotted on the x-axis and calories plotted on the y-axis? The value of r would increase. The value of r would not change. The value of r would change to –0.83. The value of r could increase or decrease, depending of the strength of the new relationship.A chi square test tells us: a. Whether two continuous variables are correlated with each other. b. Whether two discrete variables are independent of each other c. The amount of variation in one variable explained by the other d. Which categories of one variable are associated with which categories of the other variable
- What does it mean if the linear correlation coefficient is A) 0? B) -1?A researcher is studying the intensity of hurricanes that entered the Gulf of Mexico between 1975-2015 and the average water temperature of the Gulf of Mexico at the hurricane's peak strength. What is the independent and dependent variable in this study?Freshcrim specializes in the sales of ice cream from street trolleys in the centers of many cities. Some factorsthat may determine the sales of ice cream are: the atmospheric temperature, the location of the trolley, therain and the humidity. However, there exists a hypothesis that the sales of ice cream during the summer aresignificantly correlated only with atmospheric temperature. They defined two variables: X : the meanatmospheric temperature and Y : the sales. They considered the month of July of this year in a randomsample of 30 cities. For each city in the sample, let x be the mean temperature in degrees Fahrenheit and ythe mean sales per day in dollars per 100,000 residents. The data are given below. A regression model wasrun, with Y as the dependent variable and X as the independent variable.
- Consider a two-dimensional scatterplot representing the relationship between two continuous variables. If the correlation coefficient is -1, then: a. All points lie in a straight line with a slope of -1. b. All points lie in a straight line with an unknown negative slope. c. All points do not lie in a straight line but the best fitting regression line has a slope of -1 d. There is a strong positive relationship between the two variables.Seedlings of understory trees in mature tropical rainforests must survive and grow using intermittent flecks of sunlight. How does the length of exposure to these flecks of sunlight (fleck duration) affect growth? Researchers experimentally irradiated seedlings of the Southeast Asian rainforest tree with flecks of light of varying duration while maintaining the same total irradiance to all the seedlings. Below is the data. Fit a linear model to the data. Tree Mean Fleck (min) Relative growth rate (mm/mm/week 1 3.4 0.013 2 3.2 0.008 3 3 0.007 4 2.7 0.005 5 2.8 0.003 6 3.2 0.003 7 2.2 0.005 8 2.2 0.003 9 2.4 0 10 4.4 0.009 11 5.1 0.01 12 6.3 0.009 13 7.3 0.009 14 6 0.016 15 5.9 0.025 16 7.1 0.021 17 8.8 0.024 18 7.4 0.019 19 7.5 0.016 20 7.5 0.014 21 7.9 0.014 a)What is the rate of change in relative growth…Calculate the Spearman correlation coefficient between two sets of data: set A = [6, 8, 10, 12, 14] and set B = [2, 4, 6, 8, 10].
