Statistics for Business
( 24 Modules )

Module #1
Introduction to Statistics in Business
Overview of statistics in business, importance of data-driven decision making, and course objectives

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

Module #3
Data Types and Levels of Measurement
Qualitative, quantitative, nominal, ordinal, interval, and ratio data types

Module #4
Data Collection Methods
Surveys, experiments, observational studies, and data sources

Module #5
Data Visualization
Using plots, charts, and graphs to visualize and communicate data insights

Module #6
Probability Fundamentals
Basic concepts of probability, events, and conditional probability

Module #7
Discrete Random Variables
Probability distributions for discrete random variables, including binomial and Poisson distributions

Module #8
Continuous Random Variables
Probability distributions for continuous random variables, including uniform and normal distributions

Module #9
Sampling Distributions
Sampling distributions, central limit theorem, and confidence intervals

Module #10
Confidence Intervals
Constructing and interpreting confidence intervals for population means and proportions

Module #11
Hypothesis Testing
Formulating hypotheses, test statistics, p-values, and Type I and Type II errors

Module #12
One-Sample Hypothesis Testing
Testing hypotheses about a population mean or proportion using a single sample

Module #13
Two-Sample Hypothesis Testing
Testing hypotheses about the difference between two population means or proportions

Module #14
ANOVA and Regression Analysis
Analysis of variance (ANOVA) and simple linear regression

Module #15
Multiple Regression Analysis
Multiple linear regression, coefficient interpretation, and model evaluation

Module #16
Time Series Analysis
Trend analysis, seasonal decomposition, and forecasting using ARIMA models

Module #17
Statistical Quality Control
Process control, control charts, and process capability analysis

Module #18
Business Applications of Statistics
Applying statistical concepts to business problems, including forecasting and decision-making

Module #19
Data Mining and Big Data Analytics
Overview of data mining and big data analytics, including data preprocessing and visualization

Module #20
Machine Learning for Business
Introduction to machine learning, including supervised and unsupervised learning

Module #21
Case Studies in Business Statistics
Real-world applications of statistical concepts to business problems and case studies

Module #22
Statistical Software for Business
Using statistical software packages, including R, Python, and Excel

Module #23
Communicating Statistical Results
Effectively communicating statistical results to business stakeholders

Module #24
Course Wrap-Up & Conclusion
Planning next steps in Statistics for Business career

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