Business Statistics

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  • Many people find statistics challenging, but most statistics professors do not. As a result, it is sometimes hard for our professors and the authors of statistics textbooks to make statistics clear and practical for business students, managers, and executives. Business Statistics Demystified fills that gap. We begin slowly, introducing statistical concepts without mathematics.

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  • In Business Statistics, we try to narrow the gap between theory and practice by presentingstatistical methods so they are both relevant and interesting.The data that inform a business decision have a story to tell, and the role ofStatistics is to help us hear that story clearly and communicate it to others.

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  • Chapter 1 - An introduction to business statistics. After mastering the material in this chapter, you will be able to: Define a variable, describe the difference between a quantitative variable and a qualitative variable, describe the difference between crosssectional data and time series data, construct and interpret a time series (runs) plot,...

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  • A: Basically, statistics is the “science of data.” There are three main tasks in statistics: (A) collection and organization, (B) analysis, and (C) interpretation of data. (A) Collection and organization of data: We will see several methods of organizing data: graphically (through the use of charts and graphs) and numerically (through the use of tables of data). The type of organization we do depends on the type of analysis we wish to perform.

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  • Chapter 2 - Descriptive statistics: Tabular and graphical methods. After mastering the material in this chapter, you will be able to: Summarize qualitative data by using frequency distributions, bar charts, and pie charts; construct and interpret Pareto charts (Optional); summarize quantitative data by using frequency distributions, histograms, frequency polygons, and ogives;...

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  • Chapter 3 - Descriptive statistics: Numerical methods. After mastering the material in this chapter, you will be able to: Compute and interpret the mean, median, and mode; compute and interpret the range, variance, and standard deviation; use the Empirical Rule and Chebyshev's Theorem to describe variation;...

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  • Chapter 11 - Statistical inferences for population variances. After mastering the material in this chapter, you will be able to: Explain the basic terminology and concepts of experimental design, compare several different population means by using a one-way analysis of variance, compare treatment effects and block effects by using a randomized block design,...

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  • This compendium aims at providing a comprehensive overview of the main topics that appear in any well-structured course sequence in statistics for business and economics at the undergraduate and MBA levels. The idea is to supplement either formal or informal statistic textbooks such as, e.g., “Basic Statistical Ideas for Managers” by D.K. Hildebrand and R.L. Ott and “The Practice of Business Statistics: Using Data for Decisions” by D.S. Moore, G.P. McCabe, W.M. Duckworth and S.L. Sclove, with a summary of theory as well as with a couple of extra examples.

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  • Chapter 1 - What is statistics? When you have completed this chapter, you will be able to: Explain what is meant by statistics, identify the role of statistics in the development of knowledge and everyday life, explain what is meant by descriptive statistics and inferential statistics, distinguish between a qualitative variable and a quantitative variable,...

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  • When you have completed this chapter, you will be able to: Conduct the sign test for single and dependent samples using the binomial and standard normal distributions as the test statistics, conduct a test of hypothesis for dependent samples using the Wilcoxon signed-rank test, conduct and interpret the Wilcoxon rank-sum test for independent samples,...

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  • Chapter 4 - Probability. After completing this unit, you should be able to: Define a probability and a sample space, list the outcomes in a sample space and use the list to compute probabilities, use elementary probability rules to compute probabilities, compute conditional probabilities and assess independence,...

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  • Chapter 5 - Discrete random variables. After mastering the material in this chapter, you will be able to: Explain the difference between a discrete random variable and a continuous random variable, find a discrete probability distribution and compute its mean and standard deviation, use the binomial distribution to compute probabilities,...

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  • Chapter 6 - Continuous random variables. After mastering the material in this chapter, you will be able to: Define a continuous probability distribution and explain how it is used, use the uniform distribution to compute probabilities, describe the properties of the normal distribution and use a cumulative normal table, use the normal distribution to compute probabilities,...

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  • Chapter 7 - Sampling and sampling distributions. This chapter includes contents: Random sampling; the sampling distribution of the sample mean; the sampling distribution of the sample proportion; stratified random, cluster, and systematic sampling (optional); more about surveys and errors in survey sampling (optional); deviation of the mean and variance of the sample mean (optional).

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  • Chapter 8 - Confidence intervals. After mastering the material in this chapter, you will be able to: Calculate and interpret a z-based confidence interval for a population mean when σ is known, describe the properties of the t distribution and use a t table, calculate and interpret a t-based confidence interval for a population mean when σ is unknown,...

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  • Chapter 9 - Hypothesis testing. After mastering the material in this chapter, you will be able to: Set Up appropriate null and alternative hypotheses, describe Type I and Type II errors and their probabilities, use critical values and p-values to perform a z test about a population mean when s is known,...

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  • Chapter 10 - Comparing two means and two proportions. After mastering the material in this chapter, you will be able to: Compare two population means when the samples are independent, recognize when data come from independent samples and when they are paired, compare two population means when the data are paired, compare two population proportions using large independent samples.

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  • Chapter 12 - Experimental design and analysis of variance. After mastering the material in this chapter, you will be able to: Explain the basic terminology and concepts of experimental design, compare several different population means by using a one-way analysis of variance, compare treatment effects and block effects by using a randomized block design.

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  • Chapter 13 - Chi-square tests. After mastering the material in this chapter, you will be able to: Test hypotheses about multinomial probabilities by using a chi-square goodness-of-fit test, perform a goodness-of-fit test for normality, decide whether two qualitative variables are independent by using a chi-square test for independence.

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  • Chapter 14 - Simple linear regression analysis. After mastering the material in this chapter, you will be able to: Explain the simple linear regression model, find the least squares point estimates of the slope and y-intercept, describe the assumptions behind simple linear regression and calculate the standard error,...

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