University of Southern California Department of Economics ECON 317 Introduction to Statistics for Economists Prof. Safarzadeh Assignment # 2 Student Name: ________________ Answer all the questions on the spaces provided. Underline your answers and show your calculations and work on the tables. Item |Speed |Mileage | | |X - X |(X- X)2 |(Y-Y) |(Y-Y)2 |(X-X)(Y-Y) | | | |1 | 30 | 25 | | | | | | | | | | |2 | 50 | 20 | | | | | | | | | | |3 | 35 | 23 | | | | | | | | | | |4 | 45 | 21 | |
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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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been 10% of the number of employees in a given year. 2) The number of workplace injuries‚ X‚ typically follows a Poisson distribution with a parameter λ‚ where E(X) = λ and Variance(X) = λ. 3) We can reasonably approximate the Poisson distribution via a Normal distribution‚ with the same expected value and variance (according to Central Limit Theorem‚ for which you don’t need to know the details). 4) You will also need to use the critical value for the standard Normal distribution (i.e
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tools (EI) products for customers to perform the same basic function. So their alternatives‚ so it needs to calculate a sales combined variances template‚ template B did not provide this data. Part B Answer: According to the relationship between the BCG matrix‚ analysis of market share and market growth. First‚ for the EM 499 286 According to Table‚ the variance of the size of the market is unfavorable‚ the size of the market because their budget is 800000‚ but the actual market size of 650000
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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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and (C) The range of the data that would contain 68% of the results. (5 points). Raw data: sales/month (Millions of $) 23 45 34 34 56 67 54 34 45 56 23 19 Descriptive Statistics: Sales | Variable | Total Count | Mean | StDev | Variance | Minimum | Maximum | Range | Sales | 12 | 40.83 | 15.39 | 236.88 | 19.00 | 67.00 | 48.00 | Stem-and-Leaf Display: Sales Stem-and-leaf of Sales N = 12 Leaf Unit = 1.0 | 1 | 1 | 9 | 3 | 2 | 33 | 3 | 2 | | 6 |
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Mean and Variance of the Binomial Distribution The probability distribution of the Bernoulli trial with random variable X is given by Table 1 X=x P(X=x) 0 1-p 1 p The expectation and variance can be calculated as follow E X 01 p 1 p p Mean and Variance of the Binomial Distribution The expectation and variance can be calculated as follow Var X 0 1 p 1 p p 2 2 p p2 p1 p pq 2 Mean and Variance of the Binomial
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hypotheses tested concerning the value of βj or its estimated values? Question 3: Techniques Consider the moving average process: Yt = εt + θ1 εt−1 + θ12 εt−12 with {εt }T a mean zero white noise process with variance σ 2 > 0. t=0 a. Calculate the mean of Yt . b. Calculate the variance of Yt . c. Calculate the autocovariance function of {Yt }T . t=a T =120 d. Assume that {yt }t=1 represents the monthly tons of ice cream sold in the UK between Oct. 2001 and Oct. 2012. What type of
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CONFIDENTIAL CS/JAN 2012/QMT500 UNIVERSITI TEKNOLOGI MARA FINAL EXAMINATION COURSE COURSE CODE EXAMINATION TIME STATISTICS FOR ENGINEERING QMT500 JANUARY 2012 3 HOURS INSTRUCTIONS TO CANDIDATES 1. This question paper consists of five (5) questions. 2. Answer ALL questions in the Answer Booklet. Start each answer on a new page. Do not bring any material into the examination room unless permission is given by the invigilator. Please check to make sure that this examination pack
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Observation = estimated relationship + residual: yi =+ ei => yi = b1 + b2 x + ei Assumptions underlying model: 1. Linear Model ui = yi - 1- 2xi 2. Error terms have mean = 0 E(ui|x)=0 => E(y|x) = 1 + 2xi 3. Error terms have constant variance (independent of x) Var(ui|x) = 2=Var(yi|x) (homoscedastic errors) 4. Cov(ui‚ uj )= Cov(yi‚ yj )= 0. (no autocorrelation) 5. X is not a constant and is fixed in repeated samples. Additional assumption: 6. ui~N(0‚ 2) => yi~N(1- 2xi‚ 2)
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