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- Below is data of lobster sales volume from a seafood company. We're are using exponential smoothing (α = 0.5) and 3-year moving average to forecast it. a) Fill the blanks above and write your processes below. b) What are the mean absolute deviations (MADs) of the two methods? Whichmethod will you choose based on the results? *Please solve for a-b, either type your work and answers or write them neatly on paper* thank you!For a logistic regression looking at the log-odds of obesity among 20 to 70 year olds, age was included as a predictor. Age was recorded into categories: 20-29, 30-39. 40-49, 50-59, and 60-70. Given it is an ordinal variable, the statistician acknowledged that age could be included in the logistic regression model as continuous or categorical. Suppose that the statistician used loglikelihood ratio test of nested models to examine whether age could be treated as continuous. First, what is the null hypothesis? O Age is not a predictor of obesity Age is appropriate as a continuous variable O Age is appropriate as a categorical variable O Age is a predictor of obesityExplain the concept of Asymptotic Distribution of the OLS Estimatorand t-Statistic in the multi regression model?
- Illustrate the Regression Discontinuity Estimators?A company manufactures products in its factory in Turkey for sale in Asia. Products sold in different countries differ in terms of the power outlet as well as the language of the manuals. Currently, the company assembles and packs products for sale in individual countries. The distribution of weekly demand in different countries is normally distributed with means and standard deviations as shown in the table Assume that demand in countries to be independent. Given that the lead time from the Turkey factory is (X/4) weeks, how much safety inventory does the company require in Asia if it targets a CSL level of 95 percent?X= 96 b. The company builds a distribution center in Asia. It will ship base products to this center. When an order is received, the center will assemble power supplies, add manuals, and ship the products to the appropriate country. The base products are still to be manufactured in Turkey with the same lead time. How much saving of safety inventory can the company expect…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…
- 11. What is the standard error of the slope of the regression line (SEb)? Please put the answer in bold.The residual is the difference between the observed value of the independent variable and the predicted value of the independent variable. TRUE FALSEFiske Corporation manufactures a popular regional brand of kitchen utensils. The design and variety has been fairly constant over the last three years. The managers at Fiske are planning for some changes in the product line next year, but first they want to understand better the relation between activity and factory costs as experienced with the current products. Discussions with the plant supervisor suggest that overhead seems to vary with labor-hours, machine-hours, or both. The following data were collected from last three year's operations: Quarter Machine-Hours 18,850 4 5 6 7 8 9 10 11 12 18,590 17,480 19,240 21,280 19,630 19,240 18,850 18,460 20,670 17,550 18,460 Labor-Hours 15,605 15,484 16,727 15,990 17,508 17,376 15,297 14,373 16,001 17,002 14,285 17,651 Factory costs $ 3,395,671 3,425,836 3,617,844 3,573,940 3,812,984 3,778,012 3,532,426 3,369,802 3,513, 187 3,731,434 3,325,615 3,724,486 Required: Prepare a scatter graph based on the factory cost and labor-hour data. Note: 1.…
- The daily price of orange juice 30-day futures is normally distributed. InMarch through April 2007, the mean was 145.5 cents per pound, and standarddeviation = 25.0 cents per pound.4 Assuming the price is independent from day today, find P (x < 100) on the next day.П. 2. What is the degrees of freedom in a multiple regression model( with n values in each variable) with 14 independent variables when doing a t-test for the individual regression coefficients determined?Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables margin; - the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and • home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: regress margin home if team==== "Brooklyn Nets" Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1 80 Coef. Std. Err. MS 81 206.320988 8.439024 3.049595 -5.219512 2.156389 1459.95122 190.65061 t Number of obs F (1, 80) Prob > F R-squared. Adj R-squared = Root MSE P>|t| 2.77 0.007 -2.42 0.018 82 7.66 0.0070 0.0874 0.0760 13.808 [95% Conf. Interval]…