distribution of predictions for the population of financial analysts is normal. a) The probability is 0.10 that the sample variance is more than what percentage of the population variance? b) Determine any pair of numbers a and b to complete the following sentence: The probability is 0.95 that the sample variance is between a% and b% of the population variance. 2. A random sample of 202 vice presidents of marketing in corporations from the manufacturing sector were given a list
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the time series are stationary with respect to the variance and with respect to the mean. First‚ we will assume statistical stationarity of all time series (later on‚ this restriction will be relaxed). Statistical stationarity of a time series implies that the marginal probability distribution is time-independent which means that: bullet the expected values and variances are constant stationary time series - expected values and variances are constant (V.I.1-2) where T is the number
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The Mean and Median: Measures of Central Tendency The Mean and the Median The difference between the mean and median can be illustrated with an example. Suppose we draw a sample of five women and measure their weights. They weigh 100 pounds‚ 100 pounds‚ 130 pounds‚ 140 pounds‚ and 150 pounds. To find the median‚ we arrange the observations in order from smallest to largest value. If there is an odd number of observations‚ the median is the middle value. If there is an even number of observations
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Prompt 1 Perform an Internet search using the phrase “reducing overhead costs”. Select and read a case study or article from the results of your search. (Make sure that you do not select an instructor ’s lecture notes or a class assignment from the results of your search.) Summarize the case study or article‚ and relate the ideas of the article to what you have learned this week in this course. Overhead Costs are “An accounting term that refers to all ongoing business expenses not including or
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assumptions about them: * Independent. The error for one observation is independent of the error for any other observation. * Equal variance. All errors have the same variance‚ Var(ε) = σε2. * Normal. The errors are normally distributed. If these assumptions hold‚ then the collection of all possible errors forms a normal population with mean 0 and variance σε2‚ abbreviated ε ̴̴ N (0‚ σε2). Simple Regression Model (SRM) observed values of the response Y are linearly related to values of the
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information. We define σt to be the time t 2 conditional variance of ηt+1 or the conditional expectation of ηt+1 . We assume the conditional on time t information‚ the innovation is normally distributed: 2 ηt+1 ∼ N (0‚ σt ) (1) The unconditional variance of the innovation‚ σ 2 ‚ is just the unconditional 2 expectation of σt . 2 2 σ 2 ≡ E[ηt+1 ] = E[σt ] (2) 2 The variability of σt around its mean does not change the unconditional 2 2 variance σ . The variability of σt does affect higher moments
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5) What are assumptions about the expected real return on TIPS‚ its volatility‚ and its correlation with the real return on the other asset classes? What is the correlation of TIPS with the proposed Policy Portfolio excluding TIPS? HMC has assumed that the current real yield of 4% on TIPS is a good estimate of the real expected return for the future. This relies on the expectation that the current investment in TIPS will provide returns in the future that will be similar to its current earning
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the word Statistics? [ 5 marks] 2. a. In a bivariate data on ‘x’ and ‘y’‚ variance of ‘x’ = 49‚ variance of ‘y’ = 9 and covariance (x‚y) = -17.5. Find coefficient of correlation between ‘x’ and ‘y’. [ 5 marks] b. Enumerate the factors which should be kept in mind for proper planning. [ 5 marks] 3. The percentage sugar content of Tobacco in two samples was represented in table 11.11. Test whether their population variances are same. [ 10 marks] Table 1. Percentage sugar content of Tobacco in two
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volume shifts to the right; (see the graph below) it may not be at the equilibrium but it’s getting closer to the equilibrium. (Period 2 production lies between period 1 and equilibrium production level) In the second half of the year‚ the labor variance looks worse than the first term. This is the result of an increase in production during second term. In the first half of the year‚ the company did not meet its production quota (therefore less materials and labor were used for production). So Carlo
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this tool to compute the global minimum variance portfolio and the tangency portfolio for the three-firm example (see the spreadsheet 3firm.xls). The spreadsheet for this tutorial is called solverex.xls. The data for this example are given in the following table Stock 1 2 3 E[R] 0.229 0.138 0.052 VAR(R) 0.924 0.862 0.528 COV(I‚J) 0.063 -0.582 -0.359 PAIR(I‚J) (1‚2) (1‚3) (2‚3) For convenience‚ I have named the cells containing the expected returns‚ variances and covariances. See the 483solverex
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