The logit regression between bankruptcy and the profit margin is as follows. bankruptcy = b0 + b1*profit_margin + e coefficient t-stat b0 0.21 1.23 b1 -0.95 -2.41 The "bankruptcy" is a dummy variable with the value one for the bankrupted firm and zero otherwise. "profit_margin" is the firm's profit margin. Compute the difference in probability of bankruptcy when the average profit margin increases from 0.10 to 0.40. Show the calculation in detail.
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- What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?Suppose you trained your logistic regression classifier which takes an image as input and outputs either dog (class 0) or cat (class 1). Given the input image x, the hypothesis outputs 0.2. What is the probability that the input image corresponds to a dog?A multiple regression includes two regressors: Yi = b0 + b1X1i +b2X2i + ui. What is the expected change in Y if X1 increases by 8 unitsand X2 is unchanged? What is the expected change in Y if X2 decreasesby 3 units and X1 is unchanged? What is the expected change in Y if X1increases by 4 units and X2 decreases by 7 units?
- Suppose an appliance manufacturer is doing a regression analysis, using quarterly time-series data, of the factors affecting its sales of appliances. A regression equation was estimated between appliance sales (in dollars) as the dependent variable and disposable personal income and new housing starts as the independent variables. The statistical tests of the model showed large t-values for both independent variables, along with a high r2 value. However, analysis of the residuals indicated that substantial autocorrelation was present.a. What are some of the possible causes of this autocorrelation?b. How does this autocorrelation affect the conclusions concerning the significance of the individual explanatory variables and the overall explanatory power of the regression model?c. Given that a person uses the model for forecasting future appliance sales, how does this autocorrelation affect the accuracy of these forecasts?d. What techniques might be used to remove this autocorrelation…When using a regression line, the sum of the residuals should be equal to zero negative maximized positive In a sense, the standard error can be thought of as a standard deviation of the residuals. True FalseA group of scientists are interested in finding out whether the days of rainfall during the dry season could predict the magnitude of butterfly migration in the local area during wet season. Every year for twenty years, they count the total days of rainfall during the dry season preceding the migration and measure the number of butterflies migrating in the following wet season. Which type of statistical test should they use to analyze their data? (pearson's r correlation OR, simple regression equation)
- Remove the outlier and compute the least-square regression line for predicting the president's age from the first lady's age. Round the slope and y-intercept values to at least four decimal places.A 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking relate to the risk of strokes (Dataset "Stroke"). Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10-year period. For the smoker variable, 1 indicates a smoker and 0 indicates a nonsmoker. a. Develop an estimated regression equation that can be used to predict the risk of stroke given the age and blood-pressure level. b. Consider adding two independent variables to the model developed in part (a), one for the interaction between age and blood-pressure level and the other for whether the person is a smoker. Develop an estimated regression equation using these four independent variables. c. At a 0.05 level of significance, test to see whether the addition of the interaction term and the smoker variable contributes significantly to the estimated regression equation developed in part (a). d. Refer to the model developed in part…Compute the least-square regression line for predicting the president's age from the first lady's age. Round the slope and -intercept values to at least four decimal places.
- For the 23 space shuttle flights before the Challenger mission disaster in 1986, The following table shows the temperature (◦F) at the time of the flight and whether at least one primary O-ring suffered thermal distress. Use logistic regression to model the effect of temperature on the probability of thermal distress. Interpret the effect. Estimate the probability of thermal distress at 31◦F, the temperature at the time of the Challenger flight. At what temperature does the estimated probability equal 0.50? At that temperature, give a linear approximation for the change in the estimated probability per degree increase in temperature. Interpret the effect of temperature on the odds of thermal distress. Test the hypothesis that temperature has no effect, using (i) the Wald test, (ii) the likelihood-ratio test.Explain which characteristic of the STA leads to a consideration of a logistic model as opposed to a linear regression mode.The number of pounds of steam used per month by a chemical plant is thought to be related to the average ambient temperature (in F) for that month. The past year’s usage and temperatures are in the following table: Assuming that a simple linear regression model is appropriate, fit the regression model relating stem usage (y) to the average temperature (x). What is the estimate of Sigma2? What is the estimate of expected stem usage when the average temperature is 55 F? What change in mean stem usage is expected when the monthly average temperature changes by 1 F? Suppose that the monthly average temperature is 47 F. Calculate the fitted value of y and the corresponding residual. Test for significance of regression using α=0.01 (Use ANOVA). Calculate the r2 of the model. Find a 99% CI for B1 .