In a sample of 103 bags of dog food, the average weight was found to be 21.5lb with a standard deviation of 0.5. Give a point estimate for the population variance of the weight of the bags of dog food. Round your answer to two decimal places, if necessary.
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In a sample of 103 bags of dog food, the average weight was found to be 21.5lb with a standard deviation of 0.5.
Give a point estimate for the population variance of the weight of the bags of dog food. Round your answer to two decimal places, if necessary.
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- Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?The state of California has a mean annual rainfall of 22 inches, whereas the states of New York has a mean annual rainfall of 42 inches. Assume that the standard deviation for both states is 8 inches. A sample of 30 years of rainfall for California and a sample of 45 years of rainfall for New York has been taken. If required, round your answer to three decimal places.
- The weights of a random sample of cereal boxes that are supposed to weigh 1 pound are given below. Estimate the standard deviation of the entire population with 92.8% confidence. 0.95 1.01 0.97 0.95 1.04 0.98 1.02 1.03 LCL = UCL =An agriculture publication claims that the population mean of the birth weights for all Suffolk sheep is 4.29 kg. A veterinary service has hired you to test that claim. To do so, you select a random sample of 35 Suffolk sheep and record the birth weights. Assume it is known that the population standard deviation of the birth weights of Suffolk sheep is 2.15 kg. Based on your sample, follow the steps below to construct a 99% confidence interval for the population mean of the birth weights for all Suffolk sheep. Then state whether the confidence interval you construct contradicts the publication's claim. (If necessary, consult a list of formulas.) (a) Click on "Take Sample" to see the results from your random sample of 35 Suffolk sheep. Take Sample Number of sheep 35 Sample mean 5.52 deviation Sample standard Population standard deviation 1.78 2.15 Enter the values of the sample size, the point estimate for the population mean, the population standard deviation, and the critical value…What is the meaning of x ~ N (50, 20)? 1. Sampling distribution of x is distributed with a mean of 20 and a standard deviation of 50 2. x-bar is normally distributed with a mean of 20 and a standard deviation of 50 3. x is normally distributed with a mean of 50 and a standard deviation of 20 4. Sampling distribution of x is distributed with a mean of 50 and a standard deviation of 20
- You may need to use the appropriate appendix table or technology to answer this question. The following results come from two independent random samples taken of two populations. Sample 1 Sample 2 n1 = 60 n2 = 25 x1 = 13.6 x2 = 11.6 σ1 = 2.5 σ2 = 3 (a) What is the point estimate of the difference between the two population means? (Use x1 − x2.) (b) Provide a 90% confidence interval for the difference between the two population means. (Use x1 − x2. Round your answers to two decimal places.) to (c) Provide a 95% confidence interval for the difference between the two population means. (Use x1 − x2. Round your answers to two decimal places.) tobex Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 3.136512 0.964065 0.985521 0.971252 0971252 Given the above regression statistics, what is the value of the coefficient of determination? 0.964065 3.136512What is the meaning of x ̅ ~ N (50, 2)? 1. The Sampling distribution is distributed normally with a mean of 50 and a standard deviation of 2 2. Sampling distribution of x is distributed normally with a mean of 2 and a standard deviation of 50 3. x is normally distributed with a mean of 50 and a standard deviation of 2 4. x-bar is normally distributed with a mean of 2 and a standard deviation of 50
- 8. assignment variable at which the treatment status does NOT change In Regression Discontinuity framework, the cutoff is defined as the level of the True False 9. What regression equation do we use for regression discontinuity framework? a) Y = Bo + B1 T + B2Xu+ Ei b) Y = Bo + B,T+ B2C + ei c) Y, = Bo + B, T+ B2 (Xi-C) + ei d) Y, = Bo + B1T + B2 (Xu + C) + € 10. Regression Discontinuity Design accomplices apples-to-apples comparison by comparing individuals as far from the cutoff as possible. True FalseBo Using data from 50 workers, a researcher estimates Wage = ẞe + B₁Education + B2Experience + B3Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. A portion of the regression results is shown in the following table. Intercept Education Experience Age Coefficients Standard Error t Stat p-Value 7.17 4.26 1.68 0.0991 1.81 0.35 5.17 0.0000 0.45 0.10 4.50 0.0000 -0.01 0.06 -0.17 0.8684 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.81/hour. As Education increases by 1 year, Wage is predicted to increase by 0.45/hour. As Education increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Experience constant. a-2. Interpret the point estimate for $2. As Experience…A simple random sample is a sample drawn in such a way that each member of the population has: some chance of being selected in the sample. an equal chance of being included in the sample. a 1% chance of being included in the sample.