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CITATION

Kazmier, L.. Schaum's Easy Outline of Busines Statistics. US: McGraw-Hill, 2003.

Schaum's Easy Outline of Busines Statistics

Authors: L. Kazmier

Published:  February 2003

eISBN: 9780071425841 0071425845 | ISBN: 9780071398763
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  • Copyright
  • Contents
  • Chapter 1 Analyzing Business Data
  • Definition of Business Statistics
  • Descriptive and Inferential Statistics
  • Types of Applications in Business
  • Discrete and Continuous Variables
  • Obtaining Data through Direct Observation vs. Surveys
  • Methods of Random Sampling
  • Other Sampling Methods
  • Solved Problems
  • Chapter 2 Statistical Presentations and Graphical Displays
  • Frequency Distributions
  • Class Intervals
  • Histograms and Frequency Polygons
  • Frequency Curves
  • Cumulative Frequency Distributions
  • Relative Frequency Distributions
  • The “And-Under” Type of Frequency Distribution
  • Stem-and-Leaf Diagrams
  • Dotplots
  • Pareto Charts
  • Bar Charts and Line Graphs
  • Run Charts
  • Pie Charts
  • Solved Problems
  • Chapter 3 Describing Business Data: Measures of Location
  • Measures of Location in Data Sets
  • The Arithmetic Mean
  • The Weighted Mean
  • The Median
  • The Mode
  • Relationship between the Mean and Median
  • Mathematical Criteria Satisfied by the Median and the Mean
  • Use of the Mean, Median, and Mode
  • Use of the Mean in Statistical Process Control
  • Quartiles, Deciles, and Percentiles
  • Solved Problems
  • Chapter 4 Describing Business Data: Measures of Dispersion
  • Measures of Dispersion in Data Sets
  • The Range and Modified Ranges
  • The Mean Absolute Deviation
  • The Variance and Standard Deviation
  • Simplified Calculations for the Variance and Standard Deviation
  • Mathematical Criterion Associated with the Variance and Standard Deviation
  • Use of the Standard Deviation in Data Description
  • Use of the Range and Standard Deviation in Statistical Process Control
  • The Coefficient of Variation
  • Pearson’s Coefficient of Skewness
  • Solved Problems
  • Chapter 5 Probability
  • Basic Definitions of Probability
  • Expressing Probability
  • Mutually Exclusive and Nonexclusive Events
  • The Rules of Addition
  • Independent Events, Dependent Events, and Conditional Probability
  • The Rules of Multiplication
  • Bayes’ Theorem
  • Joint Probability Tables
  • Permutations
  • Combinations
  • Solved Problems
  • Chapter 6 Probability Distributions for Discrete Random Variables: Binomial, Hypergeometric, and Poisson
  • What Is a Random Variable?
  • Describing a Discrete Random Variable
  • The Binomial Distribution
  • The Binomial Variable Expressed by Proportions
  • The Hypergeometric Distribution
  • The Poisson Distribution
  • Poisson Approximation of Binomial Probabilities
  • Solved Problems
  • Chapter 7 Probability Distributions for Continuous Random Variables: Normal and Exponential
  • Continuous Random Variables
  • The Normal Probability Distribution
  • Normal Approximation of Binomial Probabilities
  • Normal Approximation of Poisson Probabilities
  • The Exponential Probability Distribution
  • Solved Problems
  • Chapter 8 Sampling Distributions and Confidence Intervals for the Mean
  • Point Estimation of a Population or Process Parameter
  • The Concept of a Sampling Distribution
  • Sampling Distribution of the Mean
  • The Central Limit Theorem
  • Determining Probability Values for the Sample Mean
  • Confidence Intervals for the Mean Using the Normal Distribution
  • Determining the Required Sample Size for Estimating the Mean
  • The t Distribution and Confidence Intervals for the Mean
  • Summary Table for Interval Estimation of the Population Mean
  • Solved Problems
  • Chapter 9 Other Confidence Intervals
  • Confidence Intervals for the Difference between Two Means Using the Normal Distribution
  • The t Distribution and Confidence Intervals for the Difference between Two Means
  • Confidence Intervals for the Population Proportion
  • Determining the Required Sample Size for Estimating the Proportion
  • Confidence Intervals for the Difference between Two Proportions
  • The Chi-Square Distribution and Confidence Intervals for the Variance and Standard Deviation
  • Solved Problems
  • Chapter 10 Testing Hypotheses Concerning the Value of the Population Mean
  • Introduction
  • Basic Steps in Hypothesis Testing by the Critical Value Approach
  • Testing a Hypothesis Concerning the Mean by Use of the Normal Distribution
  • Type I and Type II Errors in Hypothesis Testing
  • Determining the Required Sample Size for Testing the Mean
  • Testing a Hypothesis Concerning the Mean by Use of the t Distribution
  • The P-Value Approach to Testing Hypotheses Concerning the Population Mean
  • The Confidence Interval Approach to Testing Hypotheses Concerning the Mean
  • Testing with Respect to the Process Mean in Statistical Process Control
  • Summary Table for Testing a Hypothesized Value of the Mean
  • Solved Problems
  • Chapter 11 Testing Other Hypotheses
  • Testing the Difference between Two Means Using the Normal Distribution
  • Testing the Difference between Means Based on Paired Observations
  • Testing a Hypothesis Concerning the Value of the Population Proportion
  • Determining Required Sample Size for Testing the Proportion
  • Testing with Respect to the Process Proportion in Statistical Process Control
  • Testing the Difference between Two Population Proportions
  • Testing a Hypothesized Value of the Variance Using the Chi-Square Distribution
  • Testing with Respect to Process Variability in Statistical Process Control
  • The F Distribution and Testing the Equality of Two Population Variances
  • Alternative Approaches to Testing the Null Hypothesis
  • Solved Problems
  • Chapter 12 The Chi-Square Test for the Analysis of Qualitative Data
  • General Purpose of the Chi-Square Test
  • Goodness of Fit Tests
  • Tests for the Independence of Two Categorical Variables (Contingency Table Tests)
  • Testing Hypotheses Concerning Proportions
  • Testing a Hypothesized Value of the Proportion
  • Testing the Difference Between Two Population Proportions
  • Testing the Difference Among Several Population Proportions
  • Solved Problems
  • Chapter 13 Analysis of Variance
  • Basic Rationale Associated with Testing the Differences among Several Population Means
  • One-Factor Completely Randomized Design (One-Way ANOVA)
  • Two-Way Analysis of Variance (Two-Way ANOVA)
  • The Randomized Block Design (Two-Way ANOVA, One Observation per Cell)
  • Two-Factor Completely Randomized Design (Two-Way ANOVA, n Observations Per Cell)
  • Solved Problem
  • Chapter 14 Linear Regression and Correlation Analysis
  • Objectives and Assumptions of Regression Analysis
  • The Method of Least Squares for Fitting a Regression Line
  • Residuals and Residual Plots
  • The Standard Error of Estimate
  • Inferences Concerning the Slope
  • Confidence Intervals for the Conditional Mean
  • Prediction Intervals for Individual Values of the Dependent Variable
  • The Coefficient of Determination
  • The Coefficient of Correlation
  • Solved Problems
  • Chapter 15 Multiple Regression and Correlation
  • Objectives and Assumptions of Multiple Regression Analysis
  • Additional Concepts in Multiple Regression Analysis
  • Constant
  • Partial regression coefficient
  • Use of the F Test
  • Use of the t Tests
  • Confidence interval for the conditional mean
  • Prediction intervals
  • Stepwise regression analysis
  • The Use of Indicator (Dummy) Variables
  • Analysis of Variance in Linear Regression Analysis
  • Objectives and Assumptions of Multiple Correlation Analysis
  • Solved Problem
  • Chapter 16 Time Series Analysis and Business Forecasting
  • The Classical Time Series Model
  • Trend Analysis
  • Analysis of Cyclical Variations
  • Measurement of Seasonal Variations
  • Applying Seasonal Adjustments
  • Forecasting Based on Trend and Seasonal Factors
  • Cyclical Forecasting and Business Indicators
  • Forecasting Based on Moving Averages
  • Exponential Smoothing as a Forecasting Method
  • Other Forecasting Methods That Incorporate Smoothing
  • Solved Problems
  • Chapter 17 Decision Analysis: Payoff Tables and Decision Trees
  • The Structure of Payoff Tables
  • Decision Making Based upon Probabilities Alone
  • Decision Making Based upon Economic Consequences Alone
  • Decision Making Based upon Both Probabilities and Economic Consequences: The Expected Payoff Criterion
  • Expected Utility as the Decision Criterion
  • Solved Problems
  • Chapter 18 Statistical Process Control
  • Total Quality Management
  • Statistical Quality Control
  • Types of Variation in Processes
  • Control Charts
  • Solved Problems
  • Appendix A Proportions of Area for the Standard Normal Distribution
  • Appendix B Proportions of Area for the t Distribution
  • Appendix C Proportions of Area for the x2 Distribution
  • Appendix D Values of F Exceeded with Probabilities of 5 and 1%
  • Index