Business statistics

Description

Cover Business Statistics Copyright Brief Contents Contents About the Author Preface Reviewers Introduction to Statistics Introduction Why Statistics is Important for Managers Roadmap to Learning Statistics Statistical Analysis Using MS Excel, SPSS, and Minitab® Why We Need Data Scales of Measurement Nominal Scale Ordinal Scale Interval Scale Ratio Scale Four Levels of Data Measurement Basic Statistical Concepts Population and Sample Descriptive Statistics and Inferential Statistics Parameter and Statistic Introduction to MS Excel Introduction to Minitab® Introduction to SPSS Summary Key Terms Discussion Questions Case Stady Charts and Graphs Introduction Frequency Distribution Class Midpoint Relative Frequency Cumulative Frequency Graphical Presentation of Data Bar Chart Using MS Excel for Bar Chart Construction Using Minitab for Bar Chart Construction Using SPSS for Constructing a Bar Chart Pie Chart Using MS Excel for Pie Chart Construction Using Minitab for Pie Chart Construction Using SPSS for Constructing a Pie Chart Histogram Using MS Excel for Histogram Construction Using Minitab for Histogram Construction Frequency Polygon Using MS Excel for Constructing Frequency Polygon Using Minitab for the Construction of Frequency Polygon Using SPSS for Frequency Polygon Construction Ogive Using MS Excel for Ogive Construction Using Minitab for Ogive Construction Using SPSS for Ogive Construction Pareto Chart Using Minitab for the Construction of Pareto Charts Using SPSS for the Construction of Pareto Charts Stem-and-Leaf Plot Using Minitab for Stem-and-Leaf Plot Construction Using SPSS for Stem-and-Leaf Plot Construction Scatter Plot Using MS Excel for Constructing Scatter Plots Using Minitab for Scatter Plot Construction Using SPSS for Scatter Plot Construction Summary Key Terms Discussion Questions Numerical Problems Case Stady Measures of Central Tendency Introduction Central Tendency Measures of Central Tendency Prerequisites for an Ideal Measure of Central Tendency Mathematical Averages Arithmetic Mean Calculation of Simple Arithmetic Mean Using MS Excel for the Computation of Arithmetic Mean Using Minitab for the Computation of Arithmetic Mean Using SPSS for Arithmetic Mean Computation Mathematical Properties of Arithmetic Mean Merits and Demerits of Arithmetic Mean Merits Demerits Weighted Arithmetic Mean Computation of Weighted Mean Geometric Mean for Discrete and Continuous Series Geometric Mean Computation of Geometric Mean for Individual Series Geometric Mean for Discrete and Continuous Series Using MS Excel for the Computation of Geometric Mean Average Rate of Growth Importance of Geometric Mean Merits and Demerits of Geometric Mean Merits Demerits Harmonic Mean Computation of Harmonic Mean for Individual Series Computation of Harmonic Mean for Discrete Frequency Distribution and ContinuousFrequency Distribution Using MS Excel for Harmonic Mean Computation Weighted Harmonic Mean Importance of Harmonic Mean Relationship Between AM, GM, and HM Merits and Demerits of Harmonic Mean Merits Demerits Positional Averages Median Calculation of Median Computation of Median for the Individual Series Computation of Median for a Discrete Frequency Distribution Determination of Median for a Continuous Frequency Distribution Using MS Excel for Median Computation Merits and Demerits of Median Merits Demerits Mode Determination of Mode Computation of Mode for the Individual Series Computation of Mode for Discrete Frequency Distribution Computation of Mode for Continuous Frequency Distribution Using MS Excel for Mode Computation Merits and Demerits of Mode Merits Demerits An Empirical Relation between Mean, Median, and Mode Partition Values: Quartiles, Deciles, and Percentiles Quartiles First and Third Quartiles for Individual Series First and Third Quartiles for Discrete Series First and Third Quartiles for Continuous Series Using MS Excel for Quartiles Computation Using Minitab for Quartiles Computation Using SPSS for Quartiles Computation Merits and Demerits of Quartiles Merits Demerits Deciles Percentiles Summary Key Terms Discussion Questions Numerical Problems Formulas Case Study Measures of Dispersion Introduction Measures of Dispersion Properties of a Good Measure of Dispersion Methods of Measuring Dispersion Range Range for Individual Series Range for Discrete Frequency Distribution Range for Continuous Frequency Distribution Using MS Excel for Range Computation Using Minitab for Range Computation Using SPSS for Range Computation Merits and Demerits of Range Merits Demerits Interquartile Range and Quartile Deviation Interquartile Range for Individual Series, Discrete Frequency Distribution, andContinuous Frequency Distribution Using MS Excel, Minitab, and SPSS for Interquartile Range Merits and Demerits of Quartile Deviation Merits Demerits Mean Absolute Deviation (or Average Absolute Deviation) Mean Absolute Deviation for Individual Series Mean Absolute Deviation for Discrete and Continuous Frequency Distributions Using MS Excel, Minitab, and SPSS for Computing Mean Absolute Deviation Merits and Demerits of Mean Deviation Merits Demerits Standard Deviation, Variance, and Coefficient of Variation Standard Deviation Variance Coefficient of Variation Standard Deviation and Variance for an Individual Series Standard Deviation and Variance for Discrete and Continuous FrequencyDistributions Using MS Excel for Computing Standard Deviation Using Minitab for Computing Standard Deviation Using SPSS for Computing Standard Deviation Mathematical Properties of Standard Deviation Merits and Demerits of Standard Deviation Merits Demerits Empirical Rule Empirical Relationship Between Measures of Dispersion Chebyshev’s Theorem Measures of Shape Skewness Coefficient of Skewness Kurtosis The Five-Number Summary Box-and-Whisker Plots Using Minitab for Box-and-Whisker Plot Construction Using SPSS for Box-and-Whisker Plot Construction Measures of Association Correlation Karl Pearson’s Coefficient of Correlation Using MS Excel for Computing Correlation Coefficient Using Minitab for Computing Correlation Coefficient Using SPSS for Computing Correlation Coefficient Summary Key Terms Discussion Questions Numerical Problems Formulas Case Study Probability Introduction to Probability Concept of Probability Basic Concepts Venn Diagram, Unions, and Intersections Experiment Event Compound Event Independent and Dependent Events Mutually Exclusive Events Collective Exhaustive Events Equally Likely Events Complementary Events Sample Space Counting Rules, Combinations, and Permutations Multi-Step Experiment Counting Rules for Combinations Counting Rules for Permutations Probability Assigning Techniques Classical Technique Relative Frequency Technique Subjective Approach Types of Probability Marginal Probability Union Probability Joint Probability Conditional Probability Some Basic Probability Rules General Rule of Addition Probability Matrices Special Rule of Addition for Mutually Exclusive Events General Rule of Multiplication Special Rule of Multiplication Conditional Probability Independent Events Bayes’ Theorem Summary Key Terms Discussion Questions Numerical Problems Formulas Case Study Discrete Probability Distributions Introduction Difference between Discrete and Continuous Random Distributions Discrete Probability Distribution Mean, Variance, and Standard Deviation of Discrete Distribution Mean or Expected Value Variance Variance of a Discrete Distribution Binomial Distribution Solving the Problem Using Binomial Formula Using MS Excel for Binomial Probability Computation in Example Using Minitab for Binomial Probability Computation in Example Using MS Excel for Binomial Probability Computation in Example Using Minitab for Binomial Probability Computation in Example Mean and Variance of a Binomial Probability Distribution Graphical Presentation of the Binomial Probability Distribution Poisson Distribution Using MS Excel for Poisson distribution Using Minitab for Poisson Probability Computation Mean and Variance of a Poisson Probability Distribution Graphical Presentation of the Poisson Probability Distribution Poisson Probability Distribution as an Approximation of the Binomial Probability Distribution Hypergeometric Distribution Using MS Excel for Hyper geometric Distribution Using Minitab for Hyper geometric Distribution Summary Key Terms Discussion Questions Numerical Problems Formulas Case Study Continuous Probability Distributions Introduction Uniform Probability Distribution Mean, Variance, and Standard Deviation of Uniform Probability Calculation of Probabilities in Uniform Probability Distribution Using Minitab for Computing Uniform Probabilities Normal Probability Distribution Normal Curve Some Important Characteristics of Normal Probability Distribution Probability Density Function of a Normal Distribution Standard Normal Probability Distribution Using MS Excel for Calculating Normal Probabilities Using Minitab for Calculating Normal Probabilities Normal Approximation of Binomial Probabilities Exponential Probability Distribution Using MS Excel for Calculating Exponential Probabilities Using Minitab for Calculating Exponential Probabilities Summary Key Terms Discussion Questions Numerical Problems Formulas Case Study Sampling and Sampling Distributions Introduction Sampling Why is Sampling Essential? The Sampling Design Process Random Versus Non-Random Sampling Random Sampling Methods Simple Random Sampling Using MS Excel for Random Number Generation Using Minitab for Random Number Generation Stratified Random Sampling Cluster (or Area) Sampling Systematic (or Quasi-Random) Sampling Multi-Stage Sampling Non-Random Sampling Quota Sampling Convenience Sampling Judgment Sampling Snowball Sampling Sampling and Non-Sampling Errors Sampling Errors Non-Sampling Errors Faulty Designing and Planning of Survey Response Errors Non-Response Bias Errors in Coverage Compiling Error and Publication Error Sampling Distribution Central Limit Theorem Case of Sampling from a Finite Population Sample Distribution of Sample Proportion Summary Key Terms Discussion Questions Numerical Problems Case Studay Statistical Inference:Estimation for SinglePopulations Introduction Types of Estimates Using the z Statistic for Estimating Population Mean Using MS Excel for Confidence Interval Construction Using Minitab for Confidence Interval Construction Using Finite Correction Factor for Finite Populations Confidence Interval for Estimating Population Mean μ when σ is Unknown Using MS Excel and Minitab to construct z Confidence Intervals for the Mean Estimating Population Mean Using the t Statistic (Small-Sample Case) The t Distribution Degrees of Freedom Using Minitab to Construct t Confidence Intervals for the Mean Confidence Interval Estimation for Population Proportion Using Minitab to Construct Confidence Interval Estimates for Population Proportion Sample Size Estimation Sample Size for Estimating Population Mean μ Sample Size for Estimating Population Proportion p Summary Key Terms Discussion Questions Numerical Problems Formulas Case Stady Statistical Inference: Hypothesis Testing for Single Populations Introduction Introduction to Hypothesis Testing Hypothesis Testing Procedure Two-Tailed and One-Tailed Tests of Hypothesis Two-Tailed Test of Hypothesis One-Tailed Test of Hypothesis Type I and Type II Errors Hypothesis testing for a Single Population Mean Using the z Statistic p-Value Approach for Hypothesis Testing Critical Value Approach for Hypothesis Testing Using MS Excel for Hypothesis testing with the z Statistic Using Minitab for Hypothesis testing with the z Statistic Hypothesis Testing for a Single Population Mean Using the t Statistic (Case of a Small Random Sample When n < 30) Using Minitab for Hypothesis Testing for Single Population Mean Using the t Statistic (Case of a Small Random Sample, n < 30) Using SPSS for Hypothesis Testing for Single Population Mean Using the t Statistic (Case of a Small Random Sample, n Hypothesis Testing for a Single Population Mean Using Then t Statistic (Case of a Small Random Sample When n 15) Kruskal–Wallis Test Using Minitab for the Kruskal–Wallis Test Using SPSS for the Kruskal–Wallis Test Friedman Test Using Minitab for the Friedman Test Using SPSS for the Friedman Test Spearman’s Rank Correlation Using SPSS for Spearman’s Rank Correlation Summary Key Terms Discussion Questions Formulas Numerical Problems Case Study Statistical Decision Theory Introduction Elements of Decision Analysis Decision Making Under Uncertainty Laplace (Equally Likely Decision) Criterion Maximin or Minimax Criterion Maximax or Minimin Criterion Hurwicz Criterion Regret Criterion Decision Making Under Risk Expected Monetary Value Expected Opportunity Loss Expected Value of Perfect Information Bayesian Analysis: Posterior Analysis Decision Trees Summary Key Terms Discussion Questions Numerical problems Formulas Case Study Appendices Glossary Index