is the variance of this particular dimension. Firstly‚ the distance on each dimension between the host country j and the home country (in this case Germany). Secondly‚ this number is squared. After squaring minus each variable is divided by the variance of that variable. And finally‚ all these four variances are added together and divided by 4. 2. What is the difference between mean and variance? Can you explain the example given in the lecture in your own words? Mean and variance are both
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would it affect the graph if the broker were to charge the full amount of the fee? 4. Derive the optimum portfolio weights for a portfolio with two uncorrelated assets. 5. Suppose there n mutually uncorrelated assets. The return on asset i has variance i2 ‚ i 1‚2‚...‚ n but the expected rates of return are unspecified at this point. The weight of asset i in the market portfolio is xi ‚ i 1‚2‚...‚ n . Assume there is a risk-free asset with rate of return
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Week 5 Problems and questions ACC 349 a. Chapter 8 – Exercise E8-11 E8-11 Allied Company’s Small Motor Division manufactures a number of small motors used in household and office appliances. The Household Division of Allied then assembles and packages such items as blenders and juicers. Both divisions are free to buy and sell any of their components internally or externally. The following costs relate to small motor LN233 on a per unit basis.
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standards are set too high. When the products are run at a lower cost than the standard‚ then this produces a favorable variance. The cost of goods sold and variance should net to the correct cost though and this is the reason the system creates the variance. Lansing set a loose standard which the standard quantities and standard price are high‚ flowing this situation favorable variances will ordinarily result from operations. When the standard cost set artificially high‚ the standard cost of goods sold
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ANALYZING A PORTFOLIO a 58. You want your portfolio beta to be 1.20. Currently‚ your portfolio consists of $100 invested in stock A with a beta of 1.4 and $300 in stock B with a beta of .6. You have another $400 to invest and want to divide it between an asset with a beta of 1.6 and a risk-free asset. How much should you invest in the risk-free asset? a. $0 b. $140 c. $200 d. $320 e. $400 ANALYZING A PORTFOLIO d 59. You have a $1‚000 portfolio which is invested in stocks A
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A NOTE ON HYPOTHESIS TESTING |Significance Level |One-Sided Test |Two-Sided Test | |0.10 |1.285 |1.645 | |0.05 |1.645 |1.960 | |0.01 |2.33 |2.575 | Part A. Single-Sample
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After real estate is added to the portfolio‚ there are four asset classes in the portfolio: stocks‚ bonds‚ cash and real estate. Portfolio variance now includes a variance term for real estate returns and a covariance term for real estate returns with returns for each of the other three asset classes. Therefore‚ portfolio risk is affected by the variance (or standard deviation) of real estate returns and the correlation between real estate returns and returns for each of the other asset classes
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Introduction to Management Science‚ 10e (Taylor) Chapter 11 Probability and Statistics 1) Deterministic techniques assume that no uncertainty exists in model parameters. Answer: TRUE Diff: 1 Page Ref: 489 Main Heading: Types of Probability Key words: deterministic techniques 2) Probabilistic techniques assume that no uncertainty exists in model parameters. Answer: FALSE Diff: 1 Page Ref: 489 Main Heading: Types of Probability Key words: probabilistic techniques 3) Objective
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SAMPLE Population – the group of ALL people or objects that are under study Sample – a sub-set of the population Parameter – a numerical characteristic of a population 1. Population & Sample Means 2. Expected Values 3. Population & Sample Variances 4. Population & Sample Covariances 5. Population & Sample Correlation Coefficients 6. Estimators Statistic – a numerical characteristic of a sample Statistical inference – drawing conclusion about a population based on information contained
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are well defined but some of the possible factors can cause to the deviations and variances. Those possible factors can be eradicated through extra efforts into the process. However the small chances of variance will remain the same because the real business scenarios may vary sometimes than the forecasted one. This report is an attempt to investigate the operational standards and the possible causes of variance in standards and how does it affect customer satisfaction.
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