Question 8You know that there is a strong correlation between the consumption of ice cream and body weight. The Pearson's r = 0.78. You also know that the average consumption of ice cream per week is five grams with a standard deviation of 1.5 grams. The average weight is 65 kg with a standard deviation of 15 kg. What is the formula of the regression line?1 pointŷ = 26 + 7.8x ŷ = 7.8 + 26xŷ = -502 + 0.078x ŷ = 0.078 - 502x

For a set of data, x is the explanatory variable. Its mean is 8.2, and its standard deviation is 1.92. For the same set of data, y is the response variable. Its mean is 13.8, and its standard deviation is 3.03. The correlation was found to be 0.223.Select the correct slope and y-intercept for the least-squares line. Answer choices are rounded to the hundredths place.Slope = 0.35y-intercept = 10.93Slope = 0.14y-intercept = 6.27Slope = 0.35y-intercept = 3.37Slope = 0.14y-intercept = 12.65

The following observations are given for two variables.Daily demand (y)Unit price (x)     18.00       3.00     20.00       5.00     22.00     11.00     24.00     12.00Average21.007.75Standard deviation2.584.43 Correlation coefficient is

Assuming a linear relationship between X and Y, if the coefficient of correlation (r) equals – 0.30, A. the variance of X is negative. B. variable X is larger than variable Y.                          C. there is no correlation.                                      D.  the slope (b1) is negative.

The following data represents the scores of two variables, x and y: x: 10, 15, 20, 25, 30 y: 20, 25, 30, 35, 40 The correlation coefficient between x and y is:a.0.7b.0.8c.0.9d.1

Bone mineral density and cola consumption has been recorded for a sample of patients. Let 𝑥 represent the number of colas consumed per week and 𝑦 the bone mineral density in grams per cubic centimeter. Based on the data shown below answer the questions rounding your final answers to four decimal places.(a) Create a scatter plot with linear regression line for the data. (2 points)y = x + (b) Interpret the slope of the regression equation in a complete sentence.