a) explain the box jenkins paradigm in the aspects of: i) identification ii) estimation iii) diagnostics iv) forecasting b) given arima (p, d, q) models. where p is order of autoregressive process, d is degree of differencing involved and q is order of moving avarage process. if yt is timeseries process and et white noise process, then formulate and name the econometric equations for the following i) ARIMA (0, 0, 0) ii) ARIMA (0, 1, 0) iii) ARIMA (1, 0, 0) iv) ARIMA (0, 0, 1)

In terms of composition and importance, what is the differnece of mission statements of a fortune 500 comapny?

I need help with c

A scatter plot shows data for the cost of a vintage car from a dealership (y in dollars) in the year a years since 1990. The least squares regression line is given by y-25,000 + 500z. Interpret the y intercept of the least squares regression line. Select the correct answer below O The predicted cost of a vintage car from a dealership in the year is 820.000 O The predicted cost of a vintage car from a dealershpin the year 1090 is 85,000. O The predicted cost of a vintage car from a dealershp in the year 1990 is sse. The yintercept should not be interpreted.

Please provid the breakdown of coordinates for the graph and other answers with explanation:   Note:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.

Describe the recommended approach towards determining model specification.How does the R2 help in determining an appropriate model? Is theideal model the one with the highest R2? Should a regressor be included in the model if it increases the model R2?

Do not solve list all the X and Y variables, objective function and contraints for the below problem                                  ASW Publishing, Inc., a small publisher of college textbooks, must make a decision regarding which books to publish next year. The books under consideration are listed in the following table, along with the projected three­year sales expected from each book.     Book Subject Type of Book Projected Sales (000s)   Business calculus New 20   Finite mathematics Revision 30   General statistics New 15   Mathematical statistics New 10   Business statistics Revision 25   Finance New 18   Financial accounting New 25   Managerial accounting Revision 50   English literature New 20   German New 30   The books that are listed as revisions are texts that ASW already has under contract; these texts are being considered for publication as new editions. The books that are listed as new have been reviewed by the company, but contracts have not yet been signed.The company…

q5-

(a) Interpret the elasticity of cigarette consumption with respect to prices. (b) Does this regression model return the expected sign for this relationship? Explain. (c) Is the independent variable's coefficient statistically significant at a = 0.05? Explain. (d) As you have noticed, both the dependent and independent variables are defined in logs. Does this fact violate the linearity portion of CLRM Assumption I? Explain your answer. (e) A Shapiro-Wilk test on this model's residuals returns a p-value of 0.5329. Given this fact, is CLRM Assumption VII satisfied? Explain.

As an auto insurance risk analyst, it is your job to research risk profiles for various types of drivers. One common area of concern for auto insurance companies is the risk involved when offering policies to younger, less experienced drivers. The U.S. Department of Transportation recently conducted a study in which it analyzed the relationship between 1) the number of fatal accidents per 1000 licenses, and 2) the percentage of licensed drivers under the age of 21 in a sample of 42 cities. Your first step in the analysis is to construct a scatterplot of the data. FIGURE. SCATTERPLOT FOR U.S. DEPARTMENT OF TRANSPORATION PROBLEM U.S. Department of Transportation The Relationship Between Fatal Accident Frequency and Driver Age 4.5 3.5 3 2.5 1.5 1 0.5 6. 10 12 14 16 18 Percentage of drivers under age 21 Upon visual inspection, you determine that the variables do have a linear relationship. After a linear pattern has been established visually, you now proceed with performing linear…