state the limitations of using a cubic function with inflection point to model the side of a hill. What assumptions have been made that may affect the reasonableness of your solutions?
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state the limitations of using a cubic function with inflection point to model the side of a hill. What assumptions have been made that may affect the reasonableness of your solutions?
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- In attempting to formulate a model of the passenger arrival data on cruise ships over time would a nonlinear (perhaps a multiplicative exponential) model be preferable to a linear model of cruise ship arrivals against time? What about in the case of the passenger arrivals by ferry against time?Suppose that in the country of Sudland, when the yearly rate of economic growth fell from 3.0% to 1.5%, the yearly rate of increase in airborne pollutants fell from 6% to 5%. What is the average slope of a nonlinear curve between these points using the arc method? The average slope isIn a regression problem with one output variable and one input variable, we set up two cutpoints z1 and z2 for the input variable and we fit a step function regression model based on these two cutpoints of the input variable. If you write the regression problem in matrix form y = X%*%β + ε, how many rows would the vector β have?
- Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary=11,722.40+3182.56(Education)+1202.44(Experience)Estimated Salary=11,722.40+3182.56(Education)+1202.44(Experience) Suppose an employee with 66 years of education has been with the company for 33 years (note that education years are the number of years after 8th8th grade). According to this model, what is his estimated annual salary?Consider the following data regarding students' college GPAs and high school GPAs. The estimated regression equation is Estimated College GPA=1.85+0.4743(High School GPA).Estimated College GPA=1.85+0.4743(High School GPA). GPAs College GPA High School GPA 3.843.84 2.562.56 3.573.57 3.903.90 2.072.07 3.143.14 4.004.00 3.223.22 3.873.87 2.882.88 2.212.21 2.082.08 Copy Data Step 1 of 3 : Compute the sum of squared errors (SSE) for the model. Round your answer to four decimal places.Using Y as the dependent variable and X1, X2, X3, X4 and X5 as the explanatoryvariables, formulate an econometric model for data that is (i) time series data (ii)cross-sectional data and (iii) panel data – (Hint: please specify the specific model herenot its general form).
- Consider the simple linear regression model given by E(y) = 1.5 + 0.23*x where y is measured in litres and x is measured in dollars. What must be the value of the slope coefficient if x is measured in thousands of dollars while the unit of measurement of y is unchanged (i.e., x is divided by 1000)? Answer:In a regression problem with 1 output variable and with a total number of 100 possible input variables, what is the number of all possible models with three input variables?Using the data below, what is the slope coefficient from a regression of Quantity on Price? It is probably easiest to use either Gretl or Jamovi as in the powerpoint example. (round your answer to the nearest 0.1, and it can be either positive or negative.) Quantity 17 24 23 39 55 54 60 76 71 80 Price 93 77 62 64 47 35 38 12 29 2
- True or False For a linear regression model including only an intercept, the OLS estimator of that intercept is equal to the sample mean of the independent variable.A realtor was investigating the price of real estate based on the size of the house in square feet x1 and if the house was within walking distance of an "A" rated public school. The indicator variable is defined as x = 1 if the house is within walking distance of an "A" rated public school and x = 0 if the house is NOT within walking distance of an "A" rated public school. If there was interaction in the regression problem, an appropriately fit regression model would have…? a) A different slope and different y-intercept for those within walking distance and those not. b) A different y-intercept for those that were within walking distance and those that were not; the slope would not change. c) A different slope, but not a different y-intercept for those within walking distance and those not. d) Cannot be determined1.1 Which of the following is NOT a good reason for including a disturbance term in a regression equation?/ A. To allow for random influences on the dependent variable/ B. To allow for errors in the measurement of the dependent variable/ C. It captures omitted determinants of the dependent variable D. To allow for the non-zero mean of the dependent variable/ 1.2 Consider the equation Y = B1 + B2X2 + u. A null hypothesis of H0: B2 = 0 means that/ A. X2 has no effect on the expected value of Y / B. B2 has no effect on the expected value of Y/ C. X2 has no effect on the expected value of B2 / D. Y has no effect on the expected value of X2/ 1.3 The OLS residuals in the multiple regression model/ A. can be calculated by subtracting the fitted values from the actual values / B. are zero because the predicted values are another name for forecasted values / C. are typically the same as the population regression function errors / D. cannot be calculated because there…