1) The population regression function for the 2-variable model is Y,= B, + B,X, +U, Where Ui is used as a surrogate for all the variables omitted from the regression but collectively effect Y₁, why then not use a multiple regression with all the necessary variables included?
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- We estimate a simple regression Grade-B,+B,Effort + u where the red line represents Qur estimate for Grade relative to Effort, and the dots represent our data points. Which OLS assumption is violated in this regression?What are the Assumptions of Extended Least Squares in the Multiple Regression Model?Find the means of X and Y variables and the coefficient of correlation between them from the ff two regression equations: 2Y-X-50 = 0 3Y-2X-10 = 0
- A) A linear regression has a =6 and b=5 what is y predicted as when x=9? B) A linear regression has b=3 and a=4.What is the predicted Y for x=7?Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is y=82.25 -0.48x. ^ Birthrate, x (number of births per 1000 people) 35.5 44.9 29.7 19.9 13.7 27.0 51.9 15.0 50.9 49.7 39.6 24.4 Send data to calculator Send data to Excel Female life expectancy, y (in years) 67.9 57.9 61.7 71.4 72.5 73.5 55.4 76.5 58.2 60.6 64.4 74.4 Based on the sample data and the regression line, complete the following. Female life expectancy (in years) 85 80+ 75+ 70- 65+ 60- 55+ 50 x X x ++ 10 15 20 25 (b) According to the regression equation, for an increase of one (birth per 1000 people) in birthrate, there is a corresponding decrease…In a study, data collected for 40 observations were used to model the dependent variable y with 8 independent variables under consideration, x1, x2, .. , Xg. Consider a stepwise regression run on the data. 1. What is the form of the model fit in step 1? How many models are fit? How is the "best" independent variable selected in this step? 2. What is the form of the model fit in step 2? How many models are fit? How is the "best" independent variable selected in this step? 3. What is the form of the model fit in step 3? How many models are fit? How is the "best" independent variable selected in this step? 4. The variables x3, x4, and x6 were deemed the best variables for predicting y. How do you recommend the researchers proceed from here? Why?
- The maintenance manager at a trucking company wants to build a regression model to forecast the time (in years) until the first engine overhaul based on four predictor variables: (1) annual miles driven (in 1,000s of miles), (2) average load weight (in tons), (3) average driving speed (in mph), and (4) oil change interval (in 1,000s of miles). Based on driver logs and onboard computers, data have been obtained for a sample of 25 trucks. A portion of the data is shown in the accompanying table. Time Miles Load Speed Oil 7.7 42.9 22.0 44.0 16.0 0.8 98.3 20.0 47.0 34.0 6.3 61.1 22.0 62.0 15.0 E Click here for the Excel Data File b. Estimate the regression model. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) Time = Miles Load Speed oil + + d. What is the predicted time before the first engine overhaul for a particular truck driven 60,000 miles per year with an average load of 25 tons, an average driving speed of 53 mph, and 21,000 miles…Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is y = 82.17 -0.47x. Birthrate, x (number of births per 1000 people) 14.3 27.4 51.1 46.8 24.9 29.9 18.2 41.6 49.4 14.1 33.9 49.3 Send data to calculator Female life expectancy, y (in years) 75.6 70.5 58.2 59.0 73.3 62.7 73.6 65.2 62.4 74.3 67.0 53.9 Send data to Excel Female life expectancy (In years) Based on the sample data and the regression line, answer the following. 85+ 80+ 75+ 70+ 65 60 55+ 50 (a) From the regression equation, what is the predicted female life expectancy (in years) when the birthrate is 29.9 births per 1000 people? Round your answer to…A researcher collected statistics on the sales amount of a product in 120 different markets and the advertising budgets used in TV, radio and newspaper media channels for each of these markets. The sales amount are expressed in 1000 units, and the budgets are expressed in 1000 $. The researcher wants to create a simple linear regression model by choosing one among the TV, radio and newspaper advertising budgets to explain the amount of sales.a) Which variable should this researcher choose as an independent variable to the simple regression model? Explain your decision by providing its statistical basis.(use formula)b) Construct the simple linear regression model using the argument you chose and write the equation of the model. Comment b0 and b1.(not excel use formula please)c) Test whether there is a statistically significant, linear relationship between the independent variable and the dependent variable by establishing the relevant hypotheses at the level of α = 0.05 significance.…
- If I want to estimate the regression of a model by using OLS on Eveiws , and I chose the "keep it as general as possible" approach, what tests can I apply through the estimation and inference process to validate the model and the variables?Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is y= 82.15 – 0.47x. 00 Birthrate, x Female life expectancy, y (in years) (number of births per 1000 people) 40.4 65.2 85- 50.4 59.0 80+ 18.4 71.6 75- 26.5 69.9 70 32.0 64.5 65- 51.7 52.9 60- 34.4 67.2 14.6 75.9 50.1 45.8 59.2 49.9 62.1 Birthrate 73.7 26.2 (number of births per 1000 people) 73.7 14.4 Save For Later Submit Assignment Check 2 Accessibility O 2022 McGraw Hill LLC AN Rights Reserved. Terms of Use / Privacy Center DO 80 DIl 110 17 Da SO FA F4 esc F2 & delete %24 % 8 %23 6 7 3 4 7. U T K LA G S D Female life expectancy (in years)How could we provide evidence for the positive association between two variables through linear regression model and hypothesis testing? What are the steps?