Business Statistics for Data-Informed Decisions
( 24 Modules )

Module #1
Introduction to Business Statistics
Overview of the importance of statistics in business decisions, course objectives, and expectations

Module #2
Descriptive Statistics
Measures of central tendency, variability, and graphical representations of data

Module #3
Data Visualization
Effective use of charts, graphs, and tables to communicate insights

Module #4
Probability Fundamentals
Basic concepts of probability, events, and conditional probability

Module #5
Discrete Probability Distributions
Bernoulli, binomial, and Poisson distributions, their applications and calculations

Module #6
Continuous Probability Distributions
Uniform, exponential, and normal distributions, their applications and calculations

Module #7
Sampling and Sampling Distributions
Random sampling, sampling distributions, and the central limit theorem

Module #8
Confidence Intervals
Construction and interpretation of confidence intervals for population means and proportions

Module #9
Hypothesis Testing
Formulation of hypotheses, test statistics, p-values, and test decisions

Module #10
One-Sample Hypothesis Testing
Testing hypotheses about population means and proportions with a single sample

Module #11
Two-Sample Hypothesis Testing
Comparing population means and proportions with two independent samples

Module #12
Analysis of Variance (ANOVA)
Comparing means of three or more populations using ANOVA

Module #13
Regression Analysis
Simple and multiple linear regression, coefficient interpretation, and model evaluation

Module #14
Model Building and Validation
Building and validating regression models, including model selection and diagnostics

Module #15
Time Series Analysis
Introduction to time series components, trend analysis, and forecasting

Module #16
Chi-Square Tests and Non-Parametric Tests
Tests for independence, goodness of fit, and non-parametric alternatives

Module #17
Data Mining and Machine Learning
Introduction to data mining, supervised and unsupervised learning, and model evaluation

Module #18
Big Data and Business Analytics
Overview of big data, business analytics, and the role of statistics in decision-making

Module #19
Case Studies in Business Statistics
Real-world applications of statistical techniques in business decision-making

Module #20
Communicating Statistical Results
Effective communication of statistical insights and results to stakeholders

Module #21
Statistical Software and Tools
Introduction to popular statistical software and tools, such as R, Excel, and Python

Module #22
Data Quality and Management
Importance of data quality, data cleaning, and data management best practices

Module #23
Ethics in Business Statistics
Ethical considerations in data analysis and decision-making, including bias and fairness

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

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Business Statistics for Data-Informed Decisions ( 24 Modules )

Business Statistics for Data-Informed Decisions
( 24 Modules )