Suppose you obtain the following regression model, E[ln(y)]=98+0.65*ln(x1). What is the impact of a 100% change on y (in terms of percent, not decimal)?
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Suppose you obtain the following regression model, E[ln(y)]=98+0.65*ln(x1). What is the impact of a 100% change on y (in terms of percent, not decimal)?
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- Data was recorded for the temperature, in degrees Celsius, of a cup of coffee over a 30-minute period. Given the regression equation, In(Temp) = 4.20 0.023(Time), what is the predicted temperature after 3 minutes? 33.45 °C 62.24 °C 65.17 °C 66.69 °CConsider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,815.11 +2563.46 (Education) +897.49(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make? Answer Tables Keypac Keyboard ShortcuConsider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,135.60 + 2525.21( Education 7.35(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make? Answer +1047.35 Tables Keypad Keyboard Shortcuts
- Consider the following model, known as the exponential regression model: Y; = BoefiXi + ui Do you think that you can estimate the model parameters using OLS? Explain. What do you suggest how to estimate the model parameters? How do you think one can proceed estimating these by trial-and-error, or iterative, process?Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,896.07 + 2755.34 (Education) + 773.89 (Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8.years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make?What happened to the standard error of educ after adding KWW to the model? Discuss. Do you agree or disagree with the following statement? “If the log of the dependent variable appears in the regression, changing the unit of measurement of any independent variable affects both the slope and intercept coefficients”. Discuss by providing the resource.
- The following table gives the regression results of consumption behaviour between female and male. Consumption (C), in RM Model 1 Model 2 Constant 0.7515 0.6587 (0.024) (0.037) Y 0.8603 0.5442 (0.0301) (0.2881) Gen 0.2001 (0.0004) Y*Gen 0.3105 (0.0076) Adjusted R 0.78 0.78 No. of Observations 47 47 Note: Y=income (RM) Gen= Gender ( It is equal to 1 if person is female; 0 is for male) Figures in the parentheses are p- values a) Identify which are the qualitative, quantitative and interaction variable. Refer to Model 1: b) Write the regression equations for female and male. Draw the regression lines for female and male on the same diagram. What can you c) say? d) Interpret all the estimated slope coefficients. e) Conduct an appropriate test to determine whether variable gender is statistically significant at 5%. Should this variable be dropped from this regression model.3. A study of beer consumption using the annual data from 1980 -2001 produced the following regression: Y = 0.41 +0.052.X₁; −0.047X2; +0.032X3; −0.018X4i (0.027) (0.011) (0.009) (0.008) (0.009) R² = 0.94 F = 66.58 DW statistic=1.32, figures in the brackets are standard errors Where: Y₁ = Annual aggregate beer consumption in year t (billion pints) X₁₁ = Real disposable income income in year t ($ billions at 2001 prices) X2i = Price of beer in year t (index number with 2001 = 100) X31 Price of wine and sprits in year t (index number with 2001 = 100) = X4₁ = Price of cigarettes in year t (index number 2001 = 100) (a) What is the effect of a change in the price of beer on beer consumption? Does it have the correct sign? Explain. (b) Comment on the signs of the other three coefficients. Are they as expected? (c) Tests the significance of the coefficients on each of the variables Xit i = 1, 2, 3, 4. What assumptions have you made in carrying out these tests? (d) What conclusion do you draw…For this exercise, round all regression parameters to three decimal places.The following table shows national health care costs, measured in billions of dollars. Date 1970 1980 1990 2000 2010 Costs inbillions 75 253 714 1353 2570 (a) Plot the data. (Let t be years since 1970 and H the costs in billions of dollars.) b) Find an exponential function that approximates the data for health care costs. (Let t be years since 1970 and H the costs in billions of dollars.) H = 3120.372 × 0.916t H = 993.002 × 1.002t H = 94.414 × 1.091t H = 2560.371 × 0.872t H = 72.438 × 1.143t (c) By what percent per year were national health care costs increasing during the period from 1970 through 2010? (Use the model found in part (b). Round your answer to one decimal place.) %(d) Use functional notation to express how much money was spent on health care in the year 2015. (Let t be years since 1970.) H Estimate that value. (Use the model found in part (b). Round your answer to…
- Not long ago, Car and Driver magazine ran several sports cars as fast as they could down a 1-mile runway. The data they collected on one of the cars (a Lola Champ Car) is shown below.y=y= time (sec) speed (mph) 3.1 60 5.6 100 8.6 150 9.9 161.4 15 188.3 19.7 196.2 22 200 24.2 203.3 Use logarithmic regression to find a logarithmic function that best fits this data. y= Use logistic regression to find an logistic function that best fits this data.y=Consider the following regression equation representing the linear relationship between the Canada Child Benefit provided for a married couple with 3 children under the age of 6, based on their annual family net income: ŷ =121.09−0.57246xR2=0.894 where y = annual Canada Child Benefit paid (in $100s) x = net annual family income (in $1000s) Source: Canada Revenue Agency a. As the net annual family income increases, does the Canada Child Benefit paid increase or decrease? Based on this, is the correlation between the two variables positive or negative?The Canada Child Benefit paid .The correlation between the two variables is .b. Calculate the correlation coefficient and determine if the relationship between the two variables is strong, moderate or weak.r= , the relationship is . Round to 3 decimal places c. Interpret the value of the slope as it relates to this relationship. For every $1 increase in annual family net income, there is a $0.57246 decrease in…Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,160.10 +3147.75(Education) + 1230.34(Experience) Suppose an employee with 8 years of education has been with the company for 20 years (note that education years are the number of years after 8th grade). According to this model, what is his estimated annual salary? Answer Tables Keypad Keyboard Shortcuts