NAME: SHU ZHAOHUI ID: 17329164 Q5. Descriptive Statistics | | N | Minimum | Maximum | Mean | Std. Deviation | Skewness | | Statistic | Statistic | Statistic | Statistic | Statistic | Statistic | Std. Error | Gasolinescore | 1000 | 3.00 | 21.00 | 14.9090 | 4.83654 | -.493 | .077 | Globalscore | 1000 | 3.00 | 21.00 | 17.0490 | 3.78774 | -1.073 | .077 | Valid N (listwise) | 1000 | | | | | | | The mean in the gaslinescore and globalscore stand for the average the respondents choose is
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for a sample of 10 trading days is shown below. Day Stock Price 1 84 2 87 3 84 4 88 5 85 6 90 7 91 8 83 9 82 10 86 For the above sample‚ compute the following measures. a. b. c. The mean = ∑X/n = 860/10 = 86 The median = (85+86)/2 = 85.5 The variance = ∑ X - X 2/ n-1 = {(84-86)2 + (87-86)2 + (84-86)2 + (88-86)2 + (85-86)2 + (90-86)2 + (91-86)2 + (83The standard deviation = √8.89 = 2.98 The coefficient of variation = 2.98/86 * 100% = 3.47% 86)2 + (82-86)2 + (86-86)2 } / (10 -1) = 8.89 d. f
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COMPUTER ASSIGNMENT FINS2624 Session 1‚ 2012 Instructions Please read these instructions carefully before you start. Groups You may cooperate on this assignment in groups consisting of up to three students. If you prefer to work alone or with only one other student that is fine‚ too. Either way‚ make sure to enter the student IDs (including the letter) and names of all students in your group in the appropriate cells (B1:B6) on the Answers sheet. There will be draconian punishments for
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These wetland systems has experienced drought in 1950‚ 2005 and 2008. Each event occurred for the duration of nine‚ eighteen and ten months respectively refer to figure 1.1 “ Invertebrate richness”. The mean‚ standard deviation‚ standard error and variance of the available data given were calculated using the formulas shown in figure 1.0. The data available was also plotted into a line graph (refer to figure 1.2 “The number of invertebrate present in each wetland with year”) to easily determine the
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Chapter 1 1(4). The risk premium is defined as the rate of return on A. A risky asset minus the inflation rate B. The overall market C. A Treasury bill D. A risky asset minus the risk-free rate E. A risk-less investment Answer: D 2(5). The variance measure the: Non-graded A. Total difference between the actual returns and the average returns B. Average difference between the actual squared returns and the risk-free returns C. Average squared difference between the actual returns
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is high The formulas for standard deviation are given below but you should look at the examples first Population mean Population variance method 1 ‚ Population variance method 2 ‚ (it does not matter what method you use both give the same answer‚ the only thing you need to know about variance is that it is population standard deviation squared so if variance is high then standard deviation is high Population standard deviation σ = Example 1 find the population mean μ and population standard
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than 10 minutes for a bus. 3. A recent study indicates that the annual cost of maintaining and repairing a car in a town in Ontario averages 200 with a variance of 260. If a tax of 20% is introduced on all items associated with the maintenance and repair of cars (i.e.‚ everything is made 20% more expensive)‚ what will be the variance of the annual cost of maintaining and repairing a car? (Ans: 374) 4. The time to failure of a component in an electronic device has an exponential distribution
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0.0749 + 0.0749 = 0.1498. 2. [§8-53] Let X1 ‚ . . . ‚ Xn be i.i.d. uniform on [0‚ θ]. (a) Find the method of moments estimate of θ‚ and the mean‚ variance‚ bias‚ and MSE of the MME. (b) The mle of θ is θˆ = max Xi . The pdf of max1≤i≤n Xi (How do we 1≤i≤n find this? ) is n−1 nx f (x|θ) = θn 0 0<x<θ . otherwise Calculate the mean and variance of the mle.
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A statistical theory that states that given a sufficiently large sample size from a population with a finite level of variance‚ the mean of all samples from the same population will be approximately equal to the mean of the population. Furthermore‚ all of the samples will follow an approximate normal distribution pattern‚ with all variances being approximately equal to the variance of the population divided by each sample’s size. Using the central limit theorem allows you to find probabilities for
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Skewness‚ Kurtosis‚ and the Normal Curve Skewness In everyday language‚ the terms “skewed” and “askew” are used to refer to something that is out of line or distorted on one side. When referring to the shape of frequency or probability distributions‚ “skewness” refers to asymmetry of the distribution. A distribution with an asymmetric tail extending out to the right is referred to as “positively skewed” or “skewed to the right‚” while a distribution with an asymmetric tail extending out to
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