EP BUSINESS STATISTICS:FIRST COURSE-ACC
8th Edition
ISBN: 9780135179802
Author: Levine
Publisher: PEARSON CO
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4. To investigate whether accounting quality affects the firm value, the following regression
is considered:
FirmValue, = a + B,AQt + B2FirmSize, + Ht
Required:
(a). How would you modify the above model to be able to test the hypothesis that the firm
value is higher after the adoption of the International Financial Reporting Standards (IFRS)?
Explain the modified model, the expected results and the implication of the results.
(b). How would you modify the above model to test the hypothesis that the average impact of
the accounting quality on the firm value is higher after the adoption of IFRS? Explain the
modified model, the expected results and the implication of the results.
An
Explain the Two stage Least Square estimator in the general IV regression model?
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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?arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardSuppose you a manager for a local car dealership, and you want to use a linear regression model to predict the price of a used car. You decide to use four predictor variables - "Age' (how long the car has been in use since it was produced), "Dents" (the number of visible dents on the outside of the car), "Accidents" (the number of accidents the car has been in), and "mpg" (the fuel efficiency of the car, measured in miles per gallon). Your dataset contains this information for the past 120 cars sold at your dealership. Using this model, your analysis finds an R² of 37%. What is the F statistic of your analysis? Note: 1- Only round your final answer. Round your final answer to two decimal places.arrow_forward
- What is the difference between an interaction term and a main effect in multiple linear regression?arrow_forwardThe marketing manager wants to test if the effect of the MBA program on salary depends on the work experience while controlling for the other factors. Which regression model is the MOST appropriate? O a. Salary = B_0+B_1 MBA+B_2 Work +B_3 Age +3_4 Gender + 8 Ob. Salary = B_0+ B_1 MBAx Work + B_2 Age + B 3 Gender & Oc. Salary = B_0+ B_1 MBA + B_2 MBA x Work + B_3 Age + B_4 Gender + e Od. Salary = B_0+ B_1 MBA+B_2 Work + B_3 MBA x Work + 3_4 Age + B_5 Gender + &arrow_forwardThe issue of multicollinearity impacted the 'vadity and trustworthiness' of a regression model. demonstrate how this issue can be a problem by using an appropriate hypothetical and mathematical example.arrow_forward
- To properly examine the effect of a categorical independent variable in a multiple linear regression model we use an interaction term. True O Falsearrow_forwardIf the error term in a linear regression model is normally distributed, then the distribution of the OLS estimator, conditional on explanatory variables, is also normal. True or False, why?arrow_forwardShow that an interaction term of a dummy variable and a regressor changes the slope of a regression line..arrow_forward
- when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?arrow_forwardYou are analyzing a dataset with 932 datapoints. You decide to create a linear regression model with this dataset, using 18 predictor variables. Using this information, what is the degrees of freedom associated with the sum of squares total (total sum of squares) of your analysis?arrow_forward1arrow_forward
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