40%)2(0.1) = 712.44 standard deviation = square root of 712.44 = 26.69% coefficient of variation= CV= σ/ = 26.69%/11.40% = 2.34 expected return = = P1r1+P2r2+P3r3 expected return market= .3*15%+.4*9%+.3*18%= 13.5% expected return stock j= .3*20%+.4*5%+.3*12%=11.6% standard deviation =( r1- )2*P1+( r2- )2*P2+( r3- )2*P3 then square rooted standard deviation of market = ((15% - 13.5%)2*.3 + (9% - 13.5%)2*.4 + (18% -13.5%)2*.3) then square rooted = 3.85% standard deviation of stock j = ((20%
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/ N * Population standard deviation = σ = sqrt [ Σ ( Xi - μ )2 / N ] * Population variance = σ2 = Σ ( Xi - μ )2 / N * Variance of population proportion = σP2 = PQ / n * Standardized score = Z = (X - μ) / σ * Population correlation coefficient = ρ = [ 1 / N ] * Σ { [ (Xi - μX) / σx ] * [ (Yi - μY) / σy ] } Statistics Unless otherwise noted‚ these formulas assume simple random sampling. * Sample mean = x = ( Σ xi ) / n * Sample standard deviation = s = sqrt [ Σ ( xi - x )2 /
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the manager receives a daily salary of $200 plus $85 per car sold. What is the expected value and standard deviation of her salary? (Hint: Use the ‘Summary of the Laws of Expected Value and Variance’ slide in the lecture notes.) Exercise 5.4. Now assume the company managing the network gets penalised $900 for each interruption. Calculate the expected daily penalty. Calculate the standard deviation of the daily penalty. (Hint: Use the ‘Summary of the Laws of Expected Value and Variance’ slide in
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EXECUTIVE SUMMARY It is difficult for business leaders to open a newspaper or read a journal without seeing the warning that their only competitive advantage in the world economy is the knowledge embodied in the people they employ. Invest in your people‚ the gurus say‚ and your business will survive and profit. Yet when these leaders ask their Human Resource (HR) specialists to present them with proposals to increase the firm’s human capital wealth‚ these proposals are generally filled with vague
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Inferential Statistics Drawing Conclusions based on Samples Introduction This chapter introduces how you can use data from a sample to draw conclusions about the larger population from which the sample was taken. Data often arises from the results of a survey of individuals. For example‚ the management of a fast food chain might be interested in determining the total number of dollars that Baylor students spend each year eating in Waco fast food restaurants. The fast food chain would
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Average real return E. Financial reward Answer: A 4(12). The fact that higher returns are associated with higher standard deviation is known as the: A. Real return factor B. Geometric relationship C. Risk-return tradeoff D. Market variance E. Market capitalization Answer: C 5(17). The frequency distribution that is completely defined by its average and standard deviation is referred to as a(n): A. Normal distribution B. Variance distribution C. Expected rate of return D.
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January 2012 intake and March 2012 intake of the SAM students of Taylor’s College Subang Jaya campus who are taking Mathematical subject. The size of the population is 722 people. Based on the data‚ the parameters that can be measured include standard deviation‚ mean‚ and percentage. There are several problems such as some students might answer the survey more than once‚ possibly resulting in repeating data. There are also cases where not all students answer the survey as told‚ resulting in inaccuracy
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one on the left is positively skewed. The one on the right is negatively skewed. Measure of Skewness: 1. Karl Pearson coefficient of Skewness Sk = 3(mean - median) / Standard Deviation. = 3(X –Me) / S 2. The skewness of a random variable X is denoted or skew(X). It is defined as: where and are the mean and standard deviation of X. Interpretation: 1. If Sk = 0‚ then the frequency distribution is normal and symmetrical. 2. If Sk 0‚ then the frequency distribution is positively skewed. 3. If Sk
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question incorrectly. 3. Unless otherwise specified‚ each question is independent of the others and assumptions from one question do not carry over to the others. 4. Use of a calculator is allowed. 5. Some useful equations are printed below. (a) Standard deviation: n (ri − r¯)2 i=1 σ(r) = n−1 (b) Variance of a portfolio: σ 2 = w12 σ12 + w22 σ22 + 2w1 w2 σ1 σ2 cov(R1 ‚ R2 ) = w12 σ12 + w22 σ22 + 2w1 w2 σ1 σ2 ρ1‚2 (c) Weighted average cost of capital: W ACC = ke × D E + kd (1 − t) × V V GOOD LUCK
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Lecture Notes: Statistics A note on basic statistics Statistics is the practice or science of collecting and analyzing numerical data in large quantities. So there are two parts1. Collection of Data 2. Analysis of Data- understanding what the data says. Steps in Statistics To carry out any statistical operation‚ the following steps need to be followed‚ in the given order: 1. 2. 3. 4. 5. 6. Sampling Estimation Hypothesis Generation Testing Regression Prediction Collection of Data: Sampling
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