• MS 10 MBA
    Coverage : All Blocks Note: Attempt all the questions and submit this assignment on or before 31st October, 2013 to the coordinator of your study centre. “Statistical unit is necessary not only for the collection of data, but also for the interpretation and presentation”. Explain the statement...
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  • Human Resource Planning (Hrp)
    UNITY UNIVERSITY SCHOOL OF GRADUATE STUDIES Faculty of Business and Economics MBA Program BUSINESS RESEARCH METHODS (MBA 631) Central Limit Theorem and Sample Size Prepared by: Dereje Mesfin ...
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  • Management Science
    SP JAIN INSTITUTE OF MANAGEMENT AND RESEARCH Management Science Summer 2012 Course Objectives To study advanced management-science (MS) techniques and topics related to business administration. At the beginning, this course organizes in a hierarchy (i.e., it paints a “big picture” of) the various...
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  • Marketing Research Tutorial Answers
    “when”, “where”, “what”… It's a precise statement of what the research project will achieve. RQ4 Why is determining the decision problem a critical step in any research endeavor? It’s an important step because it allows the researcher to determine whether it is really necessary to employ the research...
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  • Sampling Distribution of the Sample Mean
    PROBABILITY AND STATISTICS Lab, Seminar, Lecture 4. Behavior of the sample average X-bar  The topic of 4th seminar&lab is the average of the population that has a certain characteristic.  This average is the population parameter of interest, denoted by the greek letter mu.  We estimate...
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  • Mess
    4% The Central Limit Theorem The Central Limit Theorem (CLT) is what our parametric inferential statistics are based upon. The question is, if you draw samples from a population and calculate the means of those samples, how close can you expect them to be to the population mean? The CLT addresses...
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  • Brownian Motion
    Copyright c 2010 by Karl Sigman 1 IEOR 4106: Notes on Brownian Motion We present an introduction to Brownian motion, an important continuous-time stochastic process that serves as a continuous-time analog to the simple symmetric random walk on the one hand, and shares fundamental properties...
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  • Statistics for Dummies
    topics in quick, focused lessons Deborah Rumsey, PhD Auxiliary Professor and Statistics Education Specialist, The Ohio State University Statistics Essentials FOR DUMmIES ‰ by Deborah Rumsey, PhD Statistics Essentials For Dummies® Published by Wiley Publishing, Inc. 111 River St. Hoboken...
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  • Omis 41 Statistics Study Guide
    Synthesis/Potential Test Questions (PTQs) • What is statistics? Making an inference about a population from a sample. • What is the logic that allows you to be 95% confident that the confidence interval contains the population parameter? We know from the CLT that sample means are normally distributed around...
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  • Data Notes
    labels (e.g. Amazon Standard Item Number) Data values are useless without their context The W’s: WHO WHAT (essential) (AND IN WHAT UNITS) WHEN WHERE WHY HOW -> context for data values Who The rows of a data table correspond to individual cases about Whom (or which) we record some characteristics Respondents...
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  • Reearch
    must first understand two important concepts: 1) sampling distributions of statistics, and 2) the central limit theorem. Sampling Distributions Imagine drawing (with replacement) all possible samples of size n from a population, and for each sample, calculating a statistic--e.g., the sample mean. The...
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  • Stat 330 Dr. Hoffman
    . . . . . . . 2.4.3 Erlang density . . . . . . . . . . . . . . . . . . . 2.4.4 Gaussian or Normal density . . . . . . . . . . . . 2.5 Central Limit Theorem (CLT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
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  • Statistics101
    variable Normal distribution Standard error Sampling distribution Control chart 2 1 2 Outline Background Expectations Prior exposure to Statistics Undergraduate or prior graduate course Work experience Preparations here at ISB Concepts you probably already know Data and samples Numerical summaries...
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  • Commitment Level
    ……………………………………………………………… 4, 5, 6 Conclusion and Summary ……………….………………………………………… 6, 7 Appendix: Group Statistics …………………………………………………………………….… 8 Independent Sample Tests ………………………………………………………….. 9 Descriptive Statistics ……………………………………………………………….…. 9 Test of Normality ……………………………………………………………………. 10 Histogram...
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  • Res 341 Week 5 E-Text
    014) Equation: (b) Why is the normality assumption not a problem, despite the very small value of p? (Data are from Flying 120, no. 11 [November 1993], p. 31.) Because the sample size is very large, p is normally distributed by the Central Limit Theorem (CLT). The larger the sample the...
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  • Course Note
    representative of the population. Business Statistics is the science of ‘good' decision making in the face of uncertainty and is used in many disciplines, such as financial analysis, econometrics, auditing, production and operations, and marketing research. Statistics is a science of making decisions with...
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  • Research Project
    RAJSHAHI FACULTY OF SCIENCE DEPARTMENT OF STATISTICS B.Sc. Honours Syllabus in Statistics Session: 2011 – 2012 Part I Examination – 2012 Part II Examination - 2013 Part III Examination - 2014 Part IV Examination - 2015 The B.Sc. (Honours) courses in Statistics consist of total 160 credits of 4000 marks...
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  • Soft Skills
    . . . . . . . . . . . 4.9 Summary . . . . . . . . . . . . 4.10 Solved Problems . . . . . . . . 5 Random Variables 5.1 Examples . . . . 5.2 Joint Statistics . 5.3 Independence . . 5.4 Summary . . . . 5.5 Solved Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....
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  • Data Types, Data Display and Summary Statistics
    Part I Chapter 2 Data Types, Data Display and Summary Statistics 1 Introduction • Descriptive Statistics vs. Inferential Statistics • Descriptive Statistics - Data summarization • Inferential Statistics - Use of sample data to make inferences about a population parameter. • ...
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  • Course Notes
    time. | Time-series - data collected over different time periods | * Data can be obtained via existing sources & experimental/observational studies Experimental - when values of factors can be set or manipulated | Observational - when factors of interest cannot be controlled | * Population...
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