Business statistics in practice

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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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 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 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 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 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 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 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 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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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 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 16 - Times series forecasting and index numbers. This chapter includes contents: Time series components and models, time series regression, multiplicative decomposition, simple exponential smoothing, Holt-Winter’s Models, the Box Jenkins methodology (optional advanced section), forecast error comparisons, index numbers.

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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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Chapter 15 - Multiple regression and model building. After mastering the material in this chapter, you will be able to: Explain the multiple regression model and the related least squares point estimates, explain the assumptions behind multiple regression and calculate the standard error, calculate and interpret the multiple and adjusted multiple coefficients of determination,...

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Chapter 18 - Nonparametric methods. After mastering the material in this chapter, you will be able to: Use the sign test to test a hypothesis about a population median, compare the locations of two distributions using a rank sum test for independent samples, compare the locations of two distributions using a signed ranks test for paired samples,...

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Chapter 17 - Process improvement using control charts. After mastering the material in this chapter, you will be able to: Discuss the principles and importance of quality improvement, distinguish between common causes and assignable causes of process variation, sample a process by using rational subgrouping.

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Chapter 19 - Decision theory. After studying this chapter you will be able to: Make decisions under uncertainty and under risk and assess the value of perfect information, make decisions using posterior analysis and assess the value of sample information, make decisions using utility theory.

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Lectures "Applied statistics for business - Chapter 1: Data and statistics" provides students with the knowledge: Applications in business and economics, data, data sources, descriptive Statistics, statistical Inference, computer and statistical analysis, data mining, ethical guidelines for statistical practice. Invite you to refer to the disclosures.

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