Determine the share (proportion) of person trips by each of two modes (Private auto and mass transit) using the multinomial logit model and given and following information

← Café Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the price being charged. Based on historical observations, Gary has gathered the following data, which show the numbers of these coffees sold over six different price values: Price $2.50 $3.50 $1.90 $4.20 $3.20 $4.10 Number Sold 760 515 980 250 320 490 D Using simple linear regression and given that the price per cup is $1.75, the forecasted demand for mocha latte coffees will be 1862.8 cups (enter your response rounded to one decimal place). 88

In the model Y = Bo +B 1X 1 + B 2X 2 + 8, which of these parameters represents a coefficient of an independent variable? the Y the X1 the B1 the e

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5. (26 points) The following two equations were estimated using a sample of births for the year 2010. The variable bwght is birth weight, in ounces, faminc is annual family income, in thousands of dollars, cigs is number of cigarettes the mother smoked per day while pregnant, motheduc is mother's education (in years), and fatheduc is father's education (in years): log (bŵght) = 4.73+ 0.146 log( faminc) - (0.03) (0.076) n=1,191 R² = 0.264 0.031 cigs (0.016) (5.1) log (bŵght) = 4.73+ 0.136 log( faminc) - (0.03) (0.076) - 0.051 cigs (0.010) 0.040 motheduc+ 0.041 fatheduc (0.030) n=1,191 R² = 0.286 (0.026) (5.2) (a) In terms of the model parameters, (i) state the null hypothesis that, after controlling for faminc, motheduc, and fatheduc, cigs has no effect on birth weight against the alternative that cigs has a negative effect; and (ii) carry out the test at the 10% significance level (4 points). (b) Controlling for cigs, is faminc individually significant at the 1% level against a two-…

In your company (electrical goods manufacturing), you want to forecast demand as well of a particular range of Smart TVs. Its monthly sales previous year, are presented in the table below: Month Sales January 400 February 650 March 1,150 April 1,700 May 500 June 900 July 1,150 August 1900 September 600 October 650 November 1,600 December 2050 Based on the above historical sales data: A) Create the corresponding graph and comment on the demand (sales) in terms of in trend, seasonality and periodicity please draw the diagram!!!!

3. Boyoung is writing a paper about the effect of Sunday liquor sales on drunk driving. She has panel data on which states allow liquor to be sold on Sunday in which years and wishes to estimate a difference-in-differences model. She writes the following regression equation: Year DUIRate;; = atate +a? + BTreatmentt +yControl;t + Eit i Which of the following changes does Boyoung need to make? a) She should include a constant in the regression equation. b) She should not include controls because they're already accounted for by fixed effects. c) She should include a time trend instead of time-fixed effects. d) None of the above are changes she needs to make.

4- The manager of Collins Import Autos believes the number of cars sold in a day(Q) depends on two factors: (1) the number of hours the dealership is open (H) and (2) the number of salespersons working that day (S ). After collecting data for two months (53 days), the manager estimates the following log-linear model: Q = aHbSc ----- a. Explain how to transform this log-linear model into a linear form that can be estimated using multiple regression analysis. b. How do you interpret coefficients b and c? If the dealership increases the number of salespersons by 20 percent, what will be the percentage increase in daily sales? c. Test the overall model for statistical significance at the 5 percent significance level.