Revision Questions for This Week Suppose you see the following regression table: earnings Coef. Std. Err. married 7737.006 265.0139 _cons 9058.677 210.3906 1. What are the 95 confidence intervals for (i) the intercept, (ii). the slope, rounded to the second decimal place? 2. Are any of the coefficients statistically significant at the 5% level of significance? Explain. 3. Return to the t-statistic example from earlier (below). Do either of the 95% confidence intervals contain zero? Should they? log(wage) = .284.092 educ· (.104) (.007)

Revision Questions for This Week Suppose you see the following regression table: earnings Coef. Std. Err. married 7737.006 265.0139 _cons 9058.677 210.3906 1. What are the 95 confidence intervals for (i) the intercept, (ii). the slope, rounded to the second decimal place? 2. Are any of the coefficients statistically significant at the 5% level of significance? Explain. 3. Return to the t-statistic example from earlier (below). Do either of the 95% confidence intervals contain zero? Should they? log(wage) = .284.092 educ· (.104) (.007)

Essentials of Business Analytics (MindTap Course List)

2nd Edition

ISBN:9781305627734

Author:Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson

Publisher:Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson

Chapter8: Time Series Analysis And_forecasting

Section: Chapter Questions

Problem 23P: Consider the following time series data: Construct a time series plot. What type of pattern exists...

See similar textbooks

Similar questions

Consider the following time series: a. Construct a time series plot. What type of pattern exists in the data? Is there an indication of a seasonal pattern? b. Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. c. Compute the quarterly forecasts for next year.
Show your work (use of formula, etc.) in solving the problem. Provide your answer/solution in the answer space provided below. Answer the question: Given the following historical returns, calculate the average return and the standard deviation: Year Return 1 14% 2 10% 3 15% 4 11%
calculate the following Sharpe Ratio (SP) Treynor Measure Jensen Measure M2 measure T2 measure Information Ratio (appraisal ratio) Fund Average return Standard Deviation Beta coefficient Unsystematic Risk A 0.240 0.220 0.800 0.017 B 0.200 0.170 0.900 0.450 C 0.290 0.380 1.200 0.074 D 0.260 0.290 1.100 0.026 E 0.180 0.400 0.900 0.121 F 0.320 0.460 1.100 0.153 G 0.250 0.190 0.700 0.120 Market 0.220 0.180 1.000 0.000 Risk free return 0.050 0.000
A linear regression model is Units = 4,004 – 0.659×Week. For week 46, what is the forecast for the number of units? Round your answer to the nearest whole number. units
Consider the following POPULATION of returns: 5%, -4%, -3%, and 12%. What is the standard deviation of this population of returns? O A. 0.42% O B. 0.56% OC. 6.50% O D. 7.51%
a. Using the data in the table below alculate the following performance measures.i. Sharpe ratioii. Treynor measureiii. Jensen’s alphaiv. M-squared measurev. T-squared measure, andvi. Appraisal ratio (information ratio) Fund Average return Standard Deviation Beta coefficient Unsystematic Risk A 0.240 0.220 0.800 0.017 B 0.200 0.170 0.900 0.450 C 0.290 0.380 1.200 0.074 D 0.260 0.290 1.100 0.026 E 0.180 0.400 0.900 0.121 F 0.320 0.460 1.100 0.153 G 0.250 0.190 0.700 0.120 Market 0.220 0.180 1.000 0.000 Risk free return 0.050 0.000 b. Out of the performance measures you calculated in part a., which one would you use undereach of the following circumstances:i. You want to select one of the funds as your risky portfolio.ii. You want to select one of the funds to be mixed with the rest of your portfolio,currently composed solely of holdings in the market-index fund.iii. You want to select one of the funds to form an actively managed stock portfolio
The following table illustrates the regression results from regressing monthly IBM excess returns on monthly S&P 500 excess returns. Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations Intercept Excess Market 0.517 0.268 ANOVA O 0.264 Regression Residual Total O 0.422 0.517 0.268 0.264 0.080 180.000 df 1.000 178.000 179.000 Coefficients 0.001 1.120 SS MS 0.422 0.422 1.153 0.006 1.575 What is the estimated correlation between excess IBM and market returns? F 65.085 Standard Error t Stat P-value 0.006 0.237 0.813 0.139 8.068 0.000 Significance F 0.000
A regression line has an intercept value of 174.71 and slope value of 25.22. What is the predicted value (the y-value) in the 100th period (the x-value is 100)? Round to two decimal places.
Please help!
can someone help me find b?
To 4-digit accuracy, what is the Mean of IWM return and the Mean of EEM return?
Use the following returns for X and Y. Returns Year X Y 1. 21.8% 26.4% 2. -16.8 -3.8 3. 9.8 28.4 4. 19.8 -14.6 5. 4.8. 32.4 a. Calculate the average returns for X and Y. (Do not round intermediate calculations and enter your answers as a percent rounded to 2 decimal places, e.g., 32.16.) b. Calculate the variances for X and Y. (Do not round intermediate calculations and round your answers to 6 decimal places, e.g., 32.161616.) c. Calculate the standard deviations for X and Y. (Do not round intermediate calculations and enter your answers as a percent rounded to 2 decimal places, e.g., 32.16.)