Business Statistics‚ 9e (Groebner/Shannon/Fry) Chapter 10 Estimation and Hypothesis Testing for Two Population Parameters 1) The Cranston Hardware Company is interested in estimating the difference in the mean purchase for men customers versus women customers. It wishes to estimate this difference using a 95 percent confidence level. If the sample size is n = 10 from each population‚ the samples are independent‚ and sample standard deviations are used‚ and the variances are assumed equal‚ then
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BUS 173 Assignment 2 Prepared For: Md. Siddique Hossain (Sqh) Answer to the question no 01 Inference Regarding the population variance‚ σ 2 An important area of statistic is concern with making inference about the population variance. Knowledge of population variability is an important element of statistical analysis. Two possibilities arise For example. A) For a car rental agency . * Tires with low variability’s is preferred compared with durable lives with high variability
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David F. Groebner‚ Patrick C. Shannon‚ Phillip C. Fry‚ Kent D. Smith Prentice-Hall Publisher‚ 2011 ISBN: 9780136121015 COURSE DESCRIPTION: This course introduces the basic statistical concepts and methods in inferential statistics and quantitative decision making useful in analyzing problems in all areas of business and economics. |Topics include: application of descriptive statistics; probability and probability models; point
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elements of descriptive statistical problems are the population or sample of interest‚ one or more variables (characteristics of the populations or sample units) that are to be investigated‚ Tables‚ graphs‚ numerical summary tools‚ and the identification of patterns in the data. Also there are Inferential statistics that utilizes sample data to make estimates‚ decisions‚ predictions‚ or other generalizations about a larger set of data. There are 5 elements of inferential statistical problems: The population
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ETF2121/ETF5912 Data Analysis in Business Unit Information – Semester 1 2014 Coordinator and Lecturer - Weeks 7-12: Associate Professor Ann Maharaj Office: H5.86 Phone: (990)32236 Email: ann.maharaj@monash.edu Lecturer - Weeks 1-6: Mr Bruce Stephens Office: H5.64 Phone: (990)32062 Email: bruce.stephens@monash.edu Unit material: No prescribed textbook Unit Book: available on the Moodle site. Exercises: available on the Moodle site. Software: EXCEL. Recommended Reference Books Berenson
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Email: Sonia.iqbal@uogsialkot.edu.pk INTRODUCTION 1.1 Meaning of Statistics:- Statistics is a subject consisting of rules‚ methods and techniques of collecting data and presenting large amount of numerical information. It is also used to draw inference about the population on the basis of sample For example‚ to check the performance of a student is being studied. Data will be collected on different type of variables such that study hours‚ percentage of attendance and IQ level etc. Branches of Statistics:-
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Data Analysis • Describing data and datasets Introduction to Data Analysis and Decision Making • Making inferences from data and datasets • Searching for relationships in data and datasets Decision Making Uncertainty • Optimization • Measuring uncertainty • Decision analysis with uncertainty • Modeling and simulation • Sensitivity Analysis 1 What is Management Science? • Logical‚ systematic approach to decision making using quantitative methods. • Science
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organizing‚ analyzing‚ and interpreting numerical information. Statistics is more than just looking at numbers‚ there is a process involved in obtaining the numerical information. Statistical thinking is helpful as well. This involves applying rational thought and the science of statistics to critically assess data and inferences. It is important to keep in mind that variations exist in populations and processed data. There are two different types of statistics‚ descriptive statistics and inferential
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1 Some key points and concepts mentioned in class and solved by both online and face-to-face students Chapter 8: Statistical Inference: Estimation for Single Populations Confidence Intervals Notes * There will be no questions on the exam regarding the “proportion” of a population In optional Section 7.5 we concluded this chapter by comparing confidence intervals for μ with tolerance intervals. We emphasized that a tolerance interval is meant to contain a specified percentage of the
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Testing statistical significance is an excellent way to identify probably relevance between a total data set mean/sigma and a smaller sample data set mean/sigma‚ otherwise known as a population mean/sigma and sample data set mean/sigma. This classification of testing is also very useful in proving probable relevance between data samples. Although testing statistical significance is not a 100% fool proof‚ if testing to the 95% probability on two data sets the statistical probability is .25% chance
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