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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NATIONAL UNIVERSITY OF SINGAPORE NUS BUSINESS SCHOOL FIN 3102 Investment Analysis and Portfolio Management Luis Goncalves-Pinto / Sem 1‚ AY 14/15 Practice Problems #1 1. You sell short 100 shares of Loser Co. at a market price of $45 per share. What is your maximum possible loss? Explain. 2. The investment bank you work for is writing its annual investments newsletter and you are in charge of the international markets outlook for next year. To prepare your section‚ you collect data on yearly
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Problem Sheet - I 1. Researcher conducted by a tobacco company indicates that the relative frequency distribution of tar content of its newly developed low-tar cigarette has a mean equal to 3.9 milligrams of tar per cigarette and a standard deviation equal to 1.0 milligram. Suppose a sample of 100 low-tar cigarettes is randomly selected from a day’s production and the tar content is measured in each. Assuming that the tobacco company’s claim is true‚ what is the probability that the mean
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Practical 16: estimating Population Size Using Mark and Recapture Method Raw and Processed Data Table 1: Uncertainties of apparatus used in the experiment. Apparatus | Uncertainties | Stopwatch | ±0.01s | Table 2: Formulae and sample calculations involved in processing data in the experiment. Calculations | Formula | Sample Calculation | Mean ( x ) | x = 1n i=1naiWhere‚ 1. n refers to the total number of values. 2. ∑ refers to the addition of all values starting with the first value
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Name __________________________________ Date _________ Algebra 2 Unit 5: Logarithmic Functions Logarithmic Functions Review Sheet #2 1. If the graph of is reflected across the line then the resulting curve has an Equation of (1) (3) (2) (4) 2. The domain of in the real number is (1) (3) (2) (4) 3. Which of the following values of x is not in the domain of (1) -3 (3) 5 (2) 0 (4) 4 4. The can be written as (1) (3) (2) (4) 5
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