Statistical Tools for Business Decision Making
( 25 Modules )

Module #1
Introduction to Statistical Tools for Business Decision Making
Overview of the role of statistics in business decision making, importance of data-driven decisions, and course objectives.

Module #2
Descriptive Statistics
Measures of central tendency, variability, and data visualization techniques.

Module #3
Data Collection and Sampling
Types of data, data collection methods, and sampling techniques.

Module #4
Probability and Risk Analysis
Basic concepts of probability, probability distributions, and risk analysis in business.

Module #5
Confidence Intervals
Construction and interpretation of confidence intervals for means and proportions.

Module #6
Hypothesis Testing
Introduction to hypothesis testing, types of errors, and test statistics.

Module #7
One-Sample Tests
Hypothesis testing for means and proportions, including z-tests and t-tests.

Module #8
Two-Sample Tests
Hypothesis testing for differences between means and proportions, including t-tests and ANOVA.

Module #9
Regression Analysis
Simple and multiple linear regression, coefficient interpretation, and model assumptions.

Module #10
Time Series Analysis
Introduction to time series components, trend analysis, and forecasting techniques.

Module #11
Forecasting Methods
Moving average, exponential smoothing, and ARIMA models for forecasting.

Module #12
Chi-Square Tests and Non-Parametric Tests
Goodness-of-fit tests, tests for independence, and non-parametric tests.

Module #13
ANOVA and Experimental Design
One-way and two-way ANOVA, randomized block designs, and factorial designs.

Module #14
Correlation Analysis
Measures of correlation, correlation coefficients, and interpretation.

Module #15
Data Visualization
Effective visualization techniques for business data, including charts, graphs, and plots.

Module #16
Statistical Software for Business
Overview of popular statistical software packages, including R, Excel, and Python.

Module #17
Big Data and Statistical Analysis
Challenges and opportunities of big data, and statistical techniques for big data analysis.

Module #18
Machine Learning for Business
Introduction to machine learning, supervised and unsupervised learning, and model evaluation.

Module #19
Decision Trees and Random Forests
Decision tree models, random forests, and feature importance.

Module #20
Clustering and Segmentation
K-means clustering, hierarchical clustering, and market segmentation.

Module #21
Case Studies in Business Analytics
Real-world examples of statistical tools and machine learning techniques in business.

Module #22
Effective Communication of Statistical Results
Best practices for presenting statistical results to non-technical stakeholders.

Module #23
Ethics in Statistical Analysis
Ethical considerations in data collection, analysis, and interpretation.

Module #24
Statistical Tools for Financial Analysis
Statistical techniques for financial analysis, including time series analysis and risk modeling.

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Statistical Tools for Business Decision Making career

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Statistical Tools for Business Decision Making ( 25 Modules )

Statistical Tools for Business Decision Making
( 25 Modules )