Problem #2 - - The table below shows the same actual sales of a Product X sold by Company Y from January to December of 2019, as presented in Problem #1. Month 2-Month Moving Average Forecast-Sales (# of Product X) Actual Sales Absolute Value (# of Product X) of Errors 1,860 2,033 3,556 4,211 6,250 7,990 Jan/19 Feb/19 Mar/19 Apr/19 May/19 Jun/19 Jul/19 Aug/19 Sep/19 Oct/19 Nov/19 Dec/19 Jan/20 10,250 9,850 9,980 9,990 7,895 5,353 - Calculate the 2-month Moving Average Forecast for sales from March/2019 to a) January/2019 and enter them in the table above. b) Calculate the Absolute Value of Error for every forecasted month, from March/2019 to January/2020. Enter those values on the table above. c) Mean Absolute Percent Error (MAPE) for the 2-month Moving Average Forecast you created for Product X from March/2019 to January/2020. - Calculate the Mean Absolute Deviation (MAD), the Mean Squared Error (MSE) and the

Following is standard tableau for LP. Just do Step 1-3 in Phase 1. 俄 -1 -2 2 -1 |0.1 -1 2 10 0 -1 -2 (a) 1 0 -1-3 2. -1 -2 0 -3 1 2 -6 -1l 3 -1 2 -1|0.1 -2 -1 10 -1 1 -0.1 0 3. (6) 3. -2 -6 -1 2-110.1 -2 -1 10 0.1 -1 3. 3. -1 2. 3. 7-777 17 1. 1. (6)

5. How is the flow of investors' money into stock mutual funds related to the flow of money into bond mutual funds? Data are collected on the net new money flowing into stock and bond mutual funds in the years 1985 to 2000, in billions of dollars. "Net" means that funds flowing out are subtracted from those flowing in. If more money leaves than arrives, the net flow will be negative. To eliminate the effect of inflation, all dollar amounts are in "real dollars" with constant buying power equal to that of a dollar in the year 2000. Below is Minitab output for a regression line using the stock values as the explanatory variable. Regression Analysis: Bonds versus Stocks The regression equation is Bonds = 53.4 - 0.196 Stocks Predictor Coef SE Coef T P Constant 53.41 22.99 2.32 0.036 Stocks -0.1962 0.1550 -1.27 0.226 S= 59.8813 R-Sq = 10.3% R-Sq(adj) = 3.9% (a) What is the conclusion from a test of the slope of the regression line at the 0.05 significance level? Recall that the hypotheses…

Two sectors of some economy are Sector 1 and Sector 2. The input-output table involving these two sectors results in the following value for (I-4)-, where 1.21 0.155 (I-A)-! = 0.002 1.1242 How many additional dollars worth of production of Sector 2 must be produced to meet a $1 increase in the demand for products of Sector 1? a. $0.155 O b. $1.21 O c. $1.1242 O d. $0.002 O e. $0.9692

9. When using logistic regression to look at the effect of level of satisfaction with an educational program on whether a student obtained a job at graduation, including satisfaction as a continuous variable in the logistic regression would provide similar results to which of the following contingency table methods (list all that apply): a. CMH (row 2) with satisfaction as the column variable b. CMH (row 1) c. CMH (row 2) with obtained job as the column variable d. CMH (row 3) Pearson chi-square

6. In the table beloe provides predicted population data about the world and India.RegionPredicted Population (millions)Region:                2035                2050World  :                8,933               9766India   :              1,655.7               1670.1 (d) Calculate the absolute change in the percent of the world population that liives in India between 2035 and 2050. Round your results to one decimal place. (e) The predicted population of India is incresing while the percentage of the world population predicted to live is decresing. How can that happen? Explain in full sentences.

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45. Table 1.2 shows the mean annual compensation of construction workers. bab Abor Cesaione TABLE 1.2 Construction Workers' Average Annual Compensation Annual Total Compensation (dollars) Year 1999 42,598 2000 44,764 2001 47,822 2002 48,966 Source: U.S. Bureau of the Census, Statistical Abstract of the United States, 2004-2005. (a) Find the linear regression equation for the data. (b) Find the slope of the regression line. What does the slope represent? (c) Superimpose the graph of the linear regression equation on a scatter plot of the data. (d) Use the regression equation to predict the construction workers' average annual compensation in the year 2008. Tabl

4 Chemical Oxygen Demand (COD) is a necessary water fine parameter due to the fact similar to BOD, it affords an index to examine the effect discharged wastewater will have on the receiving environment. Table 4 shows the means for the removal reduction of COD in wastewater by three different treatment methods. Test the hypothesis that the reduction percentage is no different for each treatment method. Use the 5% level of significance.

In economics we are often faced with causal problems where the endogeneity arises because of simultaneity. A classic example is that if you are interested in estimating a demand curve, the issue is what you observe in the data are equli- birum and prices and quantity which is not only a function of demand but also a function of supply. In this excercise we will generalize the problem of simultaneity bias. Consider a situation where we are interested in the effect of Ti on Yi, i.e. obtaining a consistent estimate of α. But Yi also effects Ti. Let Xi be some exogenous covariates affecting both Yi and Ti. Let us imagine you have an exogenous variable Z which only effects Ti but does not directly effect Yi. In particular, consider the following structural equations: Yi = αTi+Xi′β+ui (1) Ti = ρYi+Xi′γ+Ziδ+νi (2) where E(ui | Xi,Zi) = 0 and E(vi | Xi,Zi) = 0 (a)  Show why you cannot you use OLS to estimate α consistently in model 1? (b)  Solve for the reduced form equation for Ti…