Problem #4: (2 points) Find a 100(1 - a)% confidence interval for 0, given X₁,,X, i.i.d. with pdf f(x0) = 1,0-0.5 < x < 0+0.5. f(x10) = 2x/02, 0 < x < 0,0 > 0.
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- I got wrong!!Here, mean of X is 3 and the mean of Y is 7. The regression line that predicts Y from X necessarily goes through the point (3,7). True FalseA trucking company considered a multiple regression model for relating the dependent variable y = total daily travel time for one of its drivers (hours) to the predictors x₁ = distance traveled (miles) and x₂ = the number of deliveries made. Suppose that the model equation is Y = -0.800+ 0.060x₁ +0.900x₂ + e (a) What is the mean value of travel time when distance traveled is 50 miles and four deliveries are made? hr (b) How would you interpret ₁ = 0.060, the coefficient of the predictor x₁? O When the number of deliveries is constant, the average change in travel time associated with a ten-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The total daily travel time increases by 0.060 hours when the distance traveled increases by 1. O When the number of deliveries is held fixed, the average change in travel time associated with a one-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The average change in travel time associated with a one-mile (i.e.…
- (2) Sdr= 1 x=. V1-x2The line of best fit through a set of data isy=46.539+4.023xy=46.539+4.023xAccording to this equation, what is the predicted value of the dependent variable when the independent variable has value 40?y = Round to 1 decimal place.The line of best fit through a set of data is y = 60.638 – 0.836x || According to this equation, what is the predicted value of the dependent variable when the independent variable has value 190? y = Round to 1 decimal place.
- A trucking company considered a multiple regression model for relating the dependent variable y = total daily travel time for one of its drivers (hours) to the predictors x, = distance traveled (miles) and x, = the number of deliveries made. Suppose that the model equation is Y = -0.800 + 0.060x, + 0.900x2 + € (a) What is the mean value of travel time when distance traveled is 50 miles and four deliveries are made? 5.8 v hr (b) How would you interpret ß1 = 0.060, the coefficient of the predictor X1? o When the number of deliveries is held fixed, the average change in travel time associated with a one-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The total daily travel time increases by 0.060 hours when the distance traveled increases by 1. O When the number of deliveries is constant, the average change in travel time associated with a ten-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The average change in travel time associated with a…Suppose a logistic regression model is fitted for the probability of car ownership for residents of a certain city in Oman (Y=1 if a resident owns a car, Y=0 if a resident does not own a car). Suppose the explanatory variables used are x1=no. of years a resident spent in schooling and x2 is gender of the resident of the city (x2=1 for a male and x2=0 for a female resident) a) Interpret el and e82 b) if BO= -1.6, B1=0.4 and B2=3, estimate the probability of a resident in the city owning a car.Suppose the following regression equation was generated from the sample data of 50 cities relating number of cigarette packs sold per 1000 residents in one week to tax in dollars on one pack of cigarettes and if smoking is allowed in bars: PACKS, 58803.462982-1005.438507TAX, +284.030008BARS, + BARS, 1 if city / allows smoking in bars and BARS,= 0 if city i does not allow smoking in bars. This equation has an R² value of 0.305162, and the coefficient of BARS, has a value of 0,088136. Which of the following conclusions is valid? Answer Keypad Keyboard Shortcuts m Tables O If there is no cigarette tax in a city that allows smoking in bars, the approximate number of cigarette packs sold per 1000 people is 58803. O According to the regression equation, cities that allow smoking in bars have lower cigarette sales than cities that do not allow smoking in bars. O More than half of the variation in cigarette sales is explained by cigarette taxes and whether or not a city allows smoking in bars.…
- the regression line always passes through mcqSuppose the following regression equation was generated from the sample data of 50 cities relating number of cigarette packs sold per 1000 residents in one week to tax in dollars on one pack of cigarettes and if smoking is allowed in bars: PACKS, = 59682.369232-1108.267218TAX + 176.926159BARS; + eį. BARS 1 if city i allows smoking in bars and BARS; = 0 if city i does not allow smoking in bars. This equation has an R² value of 0.347972, and the coefficient of BARS, has a P-value of 0.133971. Which of the following conclusions is valid? Answer 2 Points Keypad Keyboard Shortcuts According to the regression equation, cities that allow smoking in bars have lower cigarette sales than cities that do not allow smoking in bars. Regardless of whether or not there is a smoking ban, if a city increases its cigarette tax by one dollar cigarette sales will increase by approximately 1108 packs. ○ If there is no cigarette tax in a city that allows smoking in bars, the approximate number of cigarette…I want to solve this. Help me plz.