Business Statistics

1. The Where, Why, and How of Data Collection.


What Is Business Statistics? Tools for Collecting Data. Populations, Samples, and Sampling Techniques. Data Types and Data Measurement Levels.



2. Graphs, Charts, and Tables–Describing Your Data.


Frequency Distributions and Histograms. Bar Charts, Pie Charts and Stem and Leaf Diagrams. Line Charts and Scatter Diagrams.



3. Describing Data Using Numerical Measures.


Measures of Center and Location. Measures of Variation. Using the Mean and Standard Deviation Together.



Chapter 1-3 Special Review Section.


4. Using Probability and Probability Distributions.


The Basics of Probability. The Rules of Probability. Introduction to Probability Distributions.



5. Discrete and Continuous Probability Distributions.


The Binomial Probability Distribution. Other Discrete Probability Distributions. The Normal Probability Distribution. Other Continuous Probability Distributions.



6. Introduction to Sampling Distributions.


Sampling Error: What It Is and Why It Happens. Sampling Distribution of the Mean. Sampling Distribution of a Proportion.



7. Estimating Population Values.


Point and Confidence Interval Estimates for a Population Mean. Determining the Required Sample Size for Estimating the Population Mean. Estimating the Population Proportion.



8. Introduction Hypothesis Testing.


Hypothesis Tests for Means. Hypotheses Tests for Proportions. Type II Errors.



9. Hypothesis Testing and Estimation for Two Population Parameters.


Estimation for Two Population Means. Hypothesis Tests for the Difference between Two Population Means. Estimation and Hypothesis Tests for Two Population Proportions.



10. Hypothesis Tests for One and Two Population Variances.


Hypothesis Tests for a Single Population Variance. Hypothesis Tests for Two Population Variances.



11. Analysis of Variance.


One-Way Analysis of Variance. Randomized Complete Block Analysis of Variance. Two-Factor Analysis of Variance with Replication.



Chapter 7-11 Special Review Section.


12. Goodness-of-Fit Tests and Contingency Analysis.


Introduction to Goodness-of-Fit Tests. Introduction to Contingency Analysis.



13. Introduction to Linear Regression and Correlation Analysis.


Scatter Plots and Correlation. Simple Linear Regression Analysis. Uses for Regression Analysis.



14. Multiple Regression and Model Building.


Introduction to Multiple Regression Analysis. Using Qualitative Independent Variables. Working with Nonlinear Relationships. Stepwise Regression. Determining the Aptness of the Model.



15. Analyzing and Forecasting Time-Series Data.


Introduction to Forecasting, Time-Series Data, and Index Numbers. Trend-Based Forecasting Techniques. Forecasting Using Smoothing Methods.



16. Introduction to Nonparametric Statistics.


The Wilcoxon Signed Rank Test for One Population Center. Nonparametric Tests for Two Population Centers. Kruskal-Wallis One-Way Analysis of Variance.



17. Introduction to Quality and Statistical Process Control.


Quality Management and Tools for Process Improvement. Introduction to Statistical Process Control Charts.



18. Introduction to Decision Analysis (CD Chapter).