MFE MATLAB Function Reference Financial Econometrics Kevin Sheppard October 30‚ 2009 2 c 2001-2009 Kevin Sheppard Contents Notes v 1 Included but not documented functions 1 2 Cross Sectional Analysis 5 2.1 Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 3 Regression: ols Stationary Time Series 3.1 ARMA Simulation . . . . . . . . . . .
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concerning variances for test concerning frequency distributions to test the independence of two variables The chi-square variable cannot be negative and the distributions are positively skewed. At about 100 d.f.‚ the distribution becomes symmetrical. The area under each chi-square distribution is equal to 1 or 100%. BUSSTAT prepared by CSANDIEGO A portion of 2 distribution BUSSTAT prepared by CSANDIEGO Test for a Single Variance Used to test a claim about a single variance‚ should
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Accounting Winter 2013 Practice Problems Chapter 8 Problem 1: Different management levels in Bates‚ Inc.‚ require varying degrees of managerial accounting information. Because of the need to comply with the managers’ requests‚ four different variances for manufacturing overhead are computed each month. The information for the September overhead expenditures is as follows: Budgeted output units 3‚200 units Budgeted fixed manufacturing overhead $20‚000 Budgeted variable manufacturing
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Katie Ebert JET2 Task 2 #000276281 There are a few areas of concern when looking over Competition Bike’s budget for the upcoming year (Year 9). This budget estimates that 3‚510 units will be sold. CB has just experienced a 15 % decline in sales‚ due to the economic situation. In year 8‚ CB sold 3‚400 units. This flexible budget is allowing 110 more units be added into the mix. Although sales trends have remained consistent‚ despite the decline in sales from professional riders‚ it might
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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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do not remain static. With the change in circumstances‚ if the standards are not revised the same become impracticable. The fixing of responsibility is not an easy task. The variances are to be classified into controllable and uncontrollable variances. Standard costing is applicable only for controllable variances. For instance‚ if the industry changed the technology then the system will not be suitable. In that case‚ we will have to change or revise the standards. A frequent revision of
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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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20 Diameter‚ xk 14.5 20.3 26.2 30.5 23.4 21.6 17.8 27.2 23.6 20.8 Age‚ yk 61 80 114 147 122 106 82 88 97 99 ¯ (a) Treating the trees as a simple random sample‚ estimate the mean age of trees in the stand Y ‚ with a variance estimate‚ 95% confidence interval‚ and RSE. Comment on the quality of the estimate. (b) Draw a scatterplot of these data (make sure the x and y axes both start at zero). Fit a regression line y = α +βx+ε to the data‚ and draw it on to the plot
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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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