plain five consequences of omitting a relevant variable(s) from a model.
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Explain five consequences of omitting a relevant variable(s) from a model.
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- 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.…2. In your own words, please describe the difference between the regression equation ŷ = b + b₁x and the regression equation y = P + ₁x (Section 10-3).State University has increased its tuition for in-state and out-of-state students in each of the past 5 years to offset cuts in its budget allocation from the state legislature. The university administration always thought that the number of applications received was independent of tuition; however, drops in applications and enrollments the past 2 years have proved this theory to be wrong. University admissions officials have developed the following relationships between the number of applicants who accept admission and enter State and the cost of tuition per semester (in-state) (out-of-state) The university would like to develop a planning model that will indicate the in-state and out-of-state tuitions, as well as the number of students that could be expected to enroll in the freshman class. The university doesn’t have enough classroom space for more than 1,400 freshmen, and it needs at least 700 freshmen to meet all its class-size x2 = 35,000 - 6t2 x1 = 21,000 - 12t1 (xi) (ti):…
- This dataset continues our saga of modeling the price of this popular Honda automobile. The dataset has now been cleaned to remove the columns with the dealership where the car was offered for sale and specific trim. (a) write out your model in econometric notation. Be very precise! (b) using the 93 observations in the dataset, estimate a model where price is a function of age, mileage and trim of the car. Be sure to avoid the dummy variable trap!! Fully report the results of your model. In this case, interpretation of the coefficients on the dummy variables is particularly important. (c) test the hypothesis that the specific trim does not affect the price of a Civic. Be sure to do all parts of the hypothesis test. (please fully describe steps if you are using Excel) Price Years Old KM EX EXT SE Sport Touring 6555 9 290363 0 0 0 0 0 9999 9 142258 0 0 0 0 0 10281 6 132644 0 0 0 0 0 12480 5 167125 0 0 0 0 0 12991 7 57398 0 0 0 0 0 12991 6 93046 0 0 0 0 0 12991…Explain about the least square regression line?How could we provide evidence for the positive association between two variables through linear regression model and hypothesis testing? What are the steps?
- Suppose we obtain data on prices of big-screen televisions and estimate the following model: In(Price) = 4.06 + 0.06 * Size +0.23 * Wide + 0.34 * Plasma + 0.21 * LCD+0.09 * Memory where the dependent variable has been transformed, Size is the screen size measured in inches, Wide is a dummy variable equal to one if the television is a widescreen, Plasma is a dummy variable equal to one if the television is a Plasma screen, LCD is equal to one if the television is an LCD screen, and Memory is a dummy variable equal to one if the television has any memory card slots. What is the estimated price of a 42" Widescreen Plasma television with 2 memory card slots? Select one: O a. 7.24 O b. 7.33 1525.38 O d. 1394.09 • e 1881.83 Clear my choice35. The regression analysis below relates US annual energy consumption in trillions of BTUs to the independent variables "US Gross Domestic Product (GDP) in trillions of dollars" and "average gas mileage of all passenger cars in miles per gallon (mpg)." Which of the two independent variables is significant at the 0.01 level? GDP only Average car gas mileage only Both independent variables Neither independent variable mergy Consumption, GDP, and Gas Mileage ource US Energy Consumption (in trillion BTUs) vs. GDP (in $trillions) and Average Car Gas Mileage (in mpg) Regression Statistics Multiple R R² Adjusted R Standard Error Observations Intercept GDP (Strillions) Avg. car gas mileage (mpg) 0.9709 0.9426 0.9359 1,943 20 F test Results F value Signif. F 139.64 Coefficients Std Error t Stat 63,672. 9,749 3,853 696 -70.50 697 6.53 5.53 -0.10 0.0000 P-value 0.0000 0.0000 0.9206To properly examine the effect of a categorical independent variable in a multiple linear regression model we use an interaction term. True O False
- when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?Can a causal relationship be established between a variable y and a variable x by running the following regressions: i) y = f(x) and ii) x = f(y). Explain in less than 75 words.18)The regression equation is intended to be the “best fitting” straight line for a set of data. Whatis the criterion for “best fitting”?