Quarter Year 1 Year 2 Year 3 1 4 6 7 2 0 1 4 3 3 5 6 4 5 7 8

Suppose that X, Y, and Z are jointly distributed random variables, that is, they are defined on the same sample space. Suppose that we also have the following. E(X)=-1 E(Y) = 4 E (Z)=0 Var(X)=20 Var(Y) = 27 Var (Z) = 38 Compute the values of the expressions below. E (5Z-2) = 0 2Z+X -5 Var(2X-3) = 0 E = E (32²) = 0 Explanation Check X O hp Ⓒ2022 McGraw Hill LLC. All Rights Reserved. Term

1. Question: Malaria is a leading cause of infectious disease and death worldwide. It is also a popular example of a vector-borne disease that could be greatly affected by the influence of climate change. Table 1 is a summary from a linear regression that uses dewpoint (°C) to predict malaria prevalence in West Africa.Fig. 1: Regression(a) Write the equation of the least square regression line. (b) Find the correlation coefficient r. (c) IsthereastrongcorrelationbetweendewpointandmalariaprevalenceinWestAfrica? (d) Is there a negative association between dewpoint and malaria prevalence in West Africa?

QUESTION THREE The following table shows, for eight vintages of select wine, purchases per buyer (y) and the buyer's rating in a year (x): X 3.6 3.2 3.1 6.0 4.1 2.5 3.0 5.1 Y 20 22 23 17 28 25 20 28 (a) Estimate the regression of purchases per buyer on the buyer's rating. (b) Interpret the slope of the estimated (c) Find and interpret the coefficient of determination (d) Find and interpret a 90%, confidence interval for the slope of the population regression line. (e) Find a 90% confidence interval for expected purchases per buyer for a vintage for which the buyer a rating is 2.0. (f) Test at 5% level of significance whether there is a significant linear between purchases per buyer and the buyer's rating.

Question 8 please

What would be the simple linear regression (trend projection) forecast for week 4 and for week 53 for Small Town Restaurant (see file) if the regression equation for our data is:   y = 3061.7 + 0.2364x ? Provide two decimal places and use normal rounding.

46. Table 1.3 lists the ages and weights of nine girls. TABLE 1.3 Girls' Ages and Weights Age (months) Weight (pounds) 22 19 23 21 24 25 27 28 29 31 31 28 34 32 38 34 43 39 (a) Find the linear regression equation for the data. (b) Find the slope of the regression line. What does the slope represent? (c) Superimpose the graph of the linear regression equation on a scatter plot of the data. (d) Use the regression equation to predict the approximate weight of a 30-month-old girl..

An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation and the naive approach. The linear trend equation is F+ = 122 +1.9t, and it was developed using data from periods 1 through 10. Based on data for periods 11 through 20 as shown in the table, which of these two methods has the greater accuracy if MAD and MSE are used? (Round your intermediate calculations and final answers to 2 decimal places.) t 11 12 13 14 15 16 17 18 19 20 Units Sold 143 149 152 145 155 152 154 159 159 162 Click here for the Excel Data File MAD (Naive) MAD (Linear) MSE (Naive) MSE (Linear))

Question 4 - 6 refer to following variables:  Dependent variable: Sentence Months Independent variable: Year of Education After calculating the regression slope of the two variables, explain what the slope refers to by selecting two correct answers (NO PATIAL CREDIT). Form: For one unit increase in [a], [b] is predicted to [c] by the slop.   For one unit increase in Sentence Months,   For one unit increase in Year of Education,   Sentence Months is predicted to increase by the slop   Sentence Months is predicted to decrease by the slop   Year of Education is predicted to increase by the slop   Year of Education is predicted to decrease by the slop

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