be able to: • • • • • • • understand the complexity of today’s managerial decisions know the meaning of quantitative techniques know the need of using quantitative approach to managerial decisions appreciate the role of statistical methods in data analysis know the various models frequently used in operations research and the basis of their classification have a brief idea of various statistical methods know the areas of applications of’ quantitative approach in business and management. Quantitative
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account for 3% of the course grade. 2. It requires the Apple.jmp dataset which is available on the course website alongside this homework. Please note that you may not need all of the data available in the file. 3. Please perform the required data analysis using JMP and turn in a brief report of no more than 3 pages (sides). No separate JMP files or appendices should be provided. Please copy and paste any relevant JMP output into the document itself. 4. Please remember to include your name‚ section
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types of data which econometricians might use for analysis: 1. Time series data 2. Cross-sectional data 3. Panel data‚ a combination of 1. & 2. Regression Returns in Financial Modelling It is preferable not to work directly with asset prices‚ so we usually convert the raw prices into a series of returns. There are two ways to do this: Simple returns or log returns Regression is probably the single most important tool What is regression analysis? It is concerned with describing and evaluating
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aimed at analyzing the impact of dividend policy of shareholders’ wealth in Organic and Inorganic Chemical Companies in India during 1996 – 1997 to 2005-2006. To measure the impact of dividend policy on shareholders’ wealth multiple regression method and stepwise regression models are used by taking DPSit (Dividend per Share)‚ RE it (Retained Earnings per Share)‚ Pet-1 (Lagged Price Earning Ratio) and MPSit-1 (Lagged Market Price) (MVit-1) as independent variable‚ and MPSit (Market Price Per Share) as
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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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Also‚ a prediction of the years 1984 and futuristic year 2016 will be made according to the function created manually. Furthermore‚ the range of data will be extended to evaluate the effectiveness of the created function for extrapolated points. Analysis of the extrapolated points will be discussed with special reference of significant fluctuations. Lastly‚ the self created function that was modelled for the first set of data will be discussed for
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POOR ACADEMIC PERFORMANCE IN SCHOOL Guidelines for Parents and Teachers The initial step in intervention for children not doing well in school is to determine the cause. The school psychologist may be the best source of information‚ and the either the school or the parents can request an evaluation to determine the causes of a child’s learning problems. The following general causes and suggested interventions are based on the gross distinctions suggested by Rabinovitch: 1. deficits in specific
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which of various plausible determinants are significantly related to an index of “perceived corruption” compiled from business risk surveys for the mid-1990s. Using 2SLS to reduce problems of endogeneity and a variation of Leamer’s “extreme bounds analysis” to test for robustness‚ it finds three factors robustly significant. Countries that were more economically developed and those which are former British colonies were rated “less corrupt”. Those which have a federal structure were “more corrupt”
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PART TWO Solutions to Empirical Exercises Chapter 3 Review of Statistics Solutions to Empirical Exercises 1. (a) Average Hourly Earnings‚ Nominal $’s Mean AHE1992 AHE2004 AHE2004 − AHE1992 (b) Average Hourly Earnings‚ Real $2004 Mean AHE1992 AHE2004 AHE2004 − AHE1992 15.66 16.77 Difference 1.11 SE(Mean) 0.086 0.098 SE(Difference) 0.130 95% Confidence Interval 15.49−15.82 16.58−16.96 95% Confidence Interval 0.85−1.37 11.63 16.77 Difference 5.14 SE(Mean) 0.064 0.098 SE(Difference) 0.117 95%
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1. This problem is in reference to students who may or may not take advantage of the opportunities provided in QMB such as homework. Some of the students pass the course‚ and some of them do not pass. Research indicates that 40% of the students do the assigned homework. Of the students who do homework‚ there is an 80% chance they will pass the course. The probability of not passing if the student does not do the home work is 90%. What is the probability of a student not doing homework or
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