ECONOMETRICS 1 SUMMATIVE PROJECT Introduction. “There ’s nothing in the world so demoralizing as money.” Sophocles‚ Antigone Nowadays‚ a lot of people have invested in a mutual fund. Because it became more popular. They think that there are low risks and also it is sample type of investment. But probably‚ mutual funds are not so in a real. In a recent study‚ Craig MacKinley (1993: p4) argued that One of the important problems of modern financial economics is the quantification of the trade-off
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Standard Deviation in the Business World QRB/501 Abstract On Standard Deviations in Job Performance The purpose of this study was to compare the expected payoffs from personnel programs based on standard deviation of job performances in dollars‚ the Global Estimation model‚ and the CREPID procedure. The study was done for route salesmen of a large soft drink bottling company. The Global Estimation model and the CREPID procedure were behaviorally based‚ where the standard deviation of job performance
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CENTRAL LIMIT THEOREM There are many situations in business where populations are distributed normally; however‚ this is not always the case. Some examples of distributions that aren’t normal are incomes in a region that are skewed to one side and if you need to are looking at people’s ages but need to break them down to for men and women. We need a way to look at the frequency distributions of these examples. We can find them by using the Central Limit Theorem. The Central Limit Theorem states
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bloomberg beta interpretation Beta definition A measure of an asset’s risk in relation to the market (for example‚ the S&P500) or to an alternative benchmark or factors. Roughly speaking‚ a security with a beta of 1.5‚ say‚ will move 50% more than the market. So if the market goes up by 20% the security’s price will go up by 30%. According to asset pricing theory‚ beta represents that part of the risk of the security called systematic risk that cannot be diversified away. When using beta‚ there
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Chi-Square Test Chi-square is a statistical test commonly used to compare observed data with data we would expect to obtain according to a specific hypothesis. For example‚ if‚ according to Mendel’s laws‚ you expected 10 of 20 offspring from a cross to be male and the actual observed number was 8 males‚ then you might want to know about the "goodness to fit" between the observed and expected. Were the deviations (differences between observed and expected) the result of chance‚ or were they due to
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Chapter 5 1. Discuss when you would use discriminant analysis instead of multiple regression analysis. Explain the difference between metric and nonmetric variables. (This is also discussed in Chapter 1.) Chapter 5 100 word minimum In choosing an appropriate analytical technique‚ we sometimes encounter a problem that involves a categorical dependent variable and several metric independent variables. Recall that the single dependent variables in regression are the appropriate statistical techniques
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ROP based on Normal Distribution of LT demand -Example No. 1 Example : Suppose that the manager of a construction supply house determined from historical records that demand for sand during leadtime averages 50 tons. In addition‚ suppose the manager determined that the demand during leadtime could be described by a normal distribution that has a mean of 50 tons and a standard deviation of 5 tons. Answer the following questions‚ assuming that the manager is willing to accept a stockout risk of no
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Collinearity The final test is testing for collinearity. This tests for variables that can be linearly predicted with high accuracy. In order for the independent variables to pass this test they may not be correlated more than +/- 0.90. If they happened to be correlated this much or great the standard error would be greatly inflated. Table 2: Collinearity of Variables After evaluating the table‚ one issue arises. There is a collinearity issue between TV and Internet. The correlation is .91 which
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SD Statistical Calculations REG Population Standard Deviation (σn) = 1.316956719 Arithmetic Mean (o) = 53.375 Number of Data (n) = 8 SD Standard Deviation Sum of Values (Σx) = 427 Sum of Squares of Values (Σx 2 ) = 22805 Use the F key to enter the SD Mode when you want to perform statistical calculations using standard deviation. SD .................................... F 2 (fx-95MS) F F 1 (Other Models) • Always start data input with A B 1 (Scl) = to clear statistical
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Blackboard Problem Set #6a 1. Consider the joint probability distribution of X and Y: x = 2 x = 4 y = 1 0.3 0.2 y = 2 0.1 0.4 What is E(X|y = 1) (rounded to four decimal places)? 2. Consider the joint probability distribution of X and Y: x = 2 x = 4 y = 1 0.3 0.2 y = 2 0.1 0.4 What is E(Y|x = 4) (rounded to four decimal places)? 3. Undergraduates are asked to write a 300-word essay. The
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