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    Concepts 1. What is Inferential statistics? Inferential statistics uses observations of past occurrences or available data i.e. descriptive statistics to make decisions about future possibilities and/or the nature of the entire body of data. Inferential statistics draws conclusions or makes interpretations‚ predictions and inferences about a population based upon an analysis of a sample. 2. Give 2 different techniques which are used in descriptive statistics to represent the data. Tables or

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    Master of Business Administration – MBA Semester I Subject code – MB0040 Subject Name – Statistics For Management Assignment Set – 1 Q.1. Why it is necessary to summarise date? Explain the approaches available to summarize the data distributions? Q.2. Explain the purpose of tabular presentation of statistical data. Draft a form of tabulation t show the distribution of population according to i) Community by age‚ ii) Literacy‚ iii) Sex‚ and iv) Marital status. Q.3. Give a brief note of the

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    Statistical Analysis BU 510 601 2 Credit Hours Fall 2013 Instructor: Shrikant Panwalkar Office phone: (410) 234 9456 Office Hours: By appointment panwalkar@jhu.edu Required Text and Learning Materials Business Statistics in Practice; 6th Edition‚ McGraw-Hill Higher Education‚ ISBN-13 978-0-07-340183-6 (There are other ISBN numbers) Authors: Bowerman‚ Bruce; O’Connell‚ Richard. (the cover shows a third author – Murphree) Please note: 7th edition is available‚ however

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    Drug abuse statistics and drug abuse facts are widely available but are thought to understate the problems of drug abuse as drug behaviors have to be reported by the users themselves. Drug abuse statistics are collected in surveys taken in high school and door-to-door in some neighborhoods. While these provide useful estimates‚ they are not thought to be the complete numbers. Statistics on drug abuse show alcohol is the most widely-used and widely-abused drug with two thirds of adults regularly consuming

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    STATISTICS

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    universally. The scale is chosen depending on the information that the data is intending to represent. The four scales of measurement of data are nominal‚ ordinal‚ interval‚ and ratio. Each plays a different‚ yet very important role in the world of statistic a) Nominal scale Is the lowest level in scales of measurement? Is a way of grouping behavior‚ where actual numbers are simply labels or identifiers. -they do not put subjects in any particular order: no logical basis for the answers in each

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    GM 03 Business Statistics Assignment II Assignment Code: 2012 GM03 B2 Last Date of Submission: 15th November 2012 Maximum Marks: 100 Attempt all the questions. All questions are compulsory and carry equal marks. SECTION – A 1. a) Explain the need for different forecasting techniques. How can we evaluate as to how good is our forecast. b) Collect data on the amount of expenditure you do each day for the next 25 days and

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    Kamlesh‚ Mathur‚ Daniel Solow. Management Science - The Art of Decision Making. Prentice Hall‚ 1994. 4 Jon Curwin and Roger Slater. Quantitative Methods for Business Decisions. Thomson‚ fifth edition‚ 2002. 5 Steyn‚ Smit‚ Du Toit‚ Strasheim. Modern Statistics in Practice. Van Schaik Publishers‚ 1994. 295

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    Chapter 2 Charts and Graphs Statistics is the science of data. A first step in the study of statistics is the examination of data. Chapters 2 and 3 present several techniques for reducing data so that it is more manageable. In addition‚ graphic displays are essential to understand and interpret complex sets of data in order to be able to make business decisions easier. Chapter 2 discusses and displays several graphical tools including the histogram‚ frequency polygon‚ ogive‚ dot plot‚ bar

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    s |COLLEGE OF THE BAHAMAS | |BUSINESS STATISTICS | |FIRST INTERM EXAM | |COURSE: STAT201

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    distribution function for 100 normal random numbers. The K-S test is based on the maximum distance between these two curves. Characteristics and Limitations of the K-S TestAn attractive feature of this test is that the distribution of the K-S test statistic itself does not depend on the underlying cumulative distribution function being tested. Another advantage is that it is an exact test (the chi-square goodness-of-fit test depends on an adequate sample size for the approximations to be valid). Despite

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