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- The marketing research department of a large company knows that the company's monthly sales are influenced by the way in which it spends money on marketing. For example, monthly expenditures such as the ones listed below are known to have an effect on y, the company's total monthly sales (in millions of dollars). X1 = money spent on television advertising (in 1000's of dollars) X2 money spent on promotion (i.e., free samples) X3 = money spent on newspaper advertising (in 1000's of dollars) X4 average discounts offered to retail outlets (in %) Using data from the previous 18 months, the company decides to collect data on 6 of the independent variables to use in a multiple regression model for estimating monthly sales. If the R´ for this model is 0.93, fill in the missing entries in the ANOVA table associated with this model. Do all calculations to at least three decimal places.The variance of temperatures (Fahrenheit) in Denver, Colo. is 328.87. What is this variance if temp is re-expressed in Celsius? [Hint: Conversion between Fahrenheit and Celsius is a linear transformation: Fahrenheit = Celsius*1.80 + 32, or Celsius = Fahrenheit*(1/1.80) - (32/1.80)]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…
- How would you write a Log-Linear regression with interaction terms? Log-Linear- Log(Y) = B0 + B1(x) + u interaction terms- Y = B0+ B1X1 + B2X2 + B3X1X2 + u Can you please provide an example if possible and how you would interpret the model.The authors of the paper "Predicting Yolk Height, Yolk Width, Albumen Length, Eggshell Weight, Egg Shape Index, Eggshell Thickness, Egg Surface Area of Japanese Quails Using Various Egg Traits as Regressors"t used a multiple regression model with two independent variables where y = quail egg weight (g), X, = egg width (mm), and X2 = egg length (mm). The regression function suggested in the paper is -21.658 + 0.828x, 0.373x2. + (a) What is the mean egg weight for quail eggs that have a width of 20 mm and a length of 48 mm? (Enter your answer to three decimal places.) (b) Interpret the value of B,. O When width is fixed, the mean increase in weight associated with a 1-mm increase in length is 0.373 g. When length is fixed, the mean increase in weight associated with a 1-mm increase in width is 0.373 g. O When length is fixed, the mean increase in weight associated with a 1-mm increase in width is 0.828 g. O When width is fixed, the mean increase in weight associated with a 1-mm increase…In a snow geese feeding trial, a model was constructed relating gosling** weight change (Y), to digestion efficiency (X1) which is measured on a scale from 1 to 10, depending on how well nutrition is absorbed by the goosling, and diet (either plants or duck chow). Using Bi, etc. to represent the coefficients of independent variables, and defining any independent variables you create and use, write out the following: [WRITE OUT THE FULL MODELS IN SINGLE EQUATIONS IN EACH SECTION BELOW, NOT BROKEN DOWN INTO SEPARATE SUB-EQUATIONS] Define your independent variables here a) a first order model that allows for different intercepts but the same slope for each diet b) a first order model that allows for different slopes and intercepts for each diet (c) a first order model that allows for different slopes and the same intercept for each diet
- I need help with part b please to find the two models which use the best subset of variables. thanksHow can Spearman's Rank Correlation or Spearman's Product Moment Correlation Coefficient be applied to a real-life problem?The variance of temperatures (Fahrenheit) in Las Vegas, Nev. is 327.84. What is this variance if temp is re-expressed in Celsius? [Hint: Conversion between Fahrenheit and Celsius is a linear transformation: Fahrenheit = Celsius*1.80 + 32, or Celsius = Fahrenheit*(1/1.80) - (32/1.80)]
