m Problem1: The demand for roses was estimated using quarterly figures for the period 1971 (3rd quarter) to 1975 (2nd quarter). Two models were estimated and the following results were obtained: Y = Quantity of roses sold (dozens) X2 = Average wholesale price of roses ($ per dozen) X3 = Average wholesale price of carnations ($ per dozen) X4 = Average weekly family disposable income ($ per week) X5 = Time (1971.3 = 1 and 1975.2 = 16) ln = natural logarithm The standard errors
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Programming Exercise 2: Logistic Regression Machine Learning October 30‚ 2011 Introduction In this exercise‚ you will implement logistic regression and apply it to two different datasets. Before starting on the programming exercise‚ we strongly recommend watching the video lectures and completing the review questions for the associated topics. To get started with the exercise‚ you will need to download the starter code and unzip its contents to the directory where you wish to complete the exercise
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ECMT1010 BUSINESS AND ECONOMIC STATISTICS A ASSIGNMENT Semester 1‚ 2011 This assignment is worth 10% of your total mark. It must be handed in by 4:30pm on Friday‚ 3 June in the marked drop-off boxes in the Merewether building (Level 2‚ reception area). Late assignments will not be accepted and will result in a zero mark. The assignment must be done individually and plagiarism will result in severe penalty and possibly a zero mark. The assignment will be marked out of 50. Marks
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SALES REPRESENTATIVE | NUMBER OF UNITS SOLD | NUMBER OF SALES CALLS | A | 28 | 14 | B | 66 | 35 | C | 38 | 22 | D | 70 | 29 | E | 22 | 6 | F | 27 | 15 | G | 28 | 17 | H | 47 | 20 | I | 14 | 12 | J | 68 | 29 | | | | | | | a) draw a scatter diagram of number of sales calls and number of units sold b) Estimate a simple linear regression model to explain the relationship between number of sales calls and number of units sold y=2.139x-1.760 Number of units
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The “value of time” according to transport economics refers to the opportunity cost of the time that voyager spend on their journey. In other words‚ it is the amount that a traveler would be willing to pay in order to save time‚ or the amount they would accept as compensation for lost time. It’s a known fact that one of the main reasons behind the transport improvements is the amount of time that travelers can save. Using a set of values of time‚ the economic benefits of a transport project can be
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CASE STUDY: 1 The bulbs manufactured by a company gave a mean life of 3000 hours with standard deviation of 400 hours. If a bulb is selected at random‚ what is the probability it will have a mean life less than 2000 hours? Question: 1) Calculate the probability. 2) In what situation does one need probability theory? 3) Define the concept of sample space‚ sample points and events in context of probability theory. 4) What is the difference between objective and subjective probability
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Regression Analysis Exercises 1- A farmer wanted to find the relationship between the amount of fertilizer used and the yield of corn. He selected seven acres of his land on which he used different amounts of fertilizer to grow corn. The following table gives the amount (in pounds) of fertilizer used and the yield (in bushels) of corn for each of the seven acres. |Fertilizer Used |Yield of Corn | |120
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------------------------------------------------- Tzu Han Hung (Vivian) CASE 2 1. Estimated profit by random selection Expected spending per catalog mailed = 0.053 * $103 = $5.46 Expected Gross Profit by random select= (5.46-2)*180‚000 = $622‚800 2. a) We applied partition to “All_data” sheet‚ and partition output is shown in “Data_Partition1” b) Logistic regression output can be seen in “LR_Output1”. Target variable is “purchase”. We select every variable except sequence_number(meaningless
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Structural Equation Modeling * A Conceptual Overview * The Basic Idea Behind Structural Modeling * Structural Equation Modeling and the Path Diagram A Conceptual Overview Structural Equation Modeling is a very general‚ very powerful multivariate analysis technique that includes specialized versions of a number of other analysis methods as special cases. We will assume that you are familiar with the basic logic of statistical reasoning as described in Elementary Concepts. Moreover‚ we will
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Tutorial 11 A11.1 Data on manatee deaths due to powerboats was used to construct a linear regression model relating these deaths to the number of registered powerboats. Year 1977 1978 1979 1980 1981 1982 1983 Power boats (thousands) 447 460 481 498 513 512 526 Manatee Deaths 13 21 24 16 24 20 15 Year 1984 1985 1986 1987 1988 1989 1990 Power boats (thousands) 559 585 614 645 675 711 719 Manatee Deaths 34 33 33 39 43 50 47 The
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