Statistics
16 courses·EN
Reason about variation, sampling, relationships, and uncertainty when working with data.
Select a focused concept or practice exercise. Data Science and Marketing Analytics apply these ideas to particular workflows; a statistic alone does not establish causation.
A route through the topic
Choose from these lessons according to the question or task you want to explore.
Courses in this topic
Distributions: Center, Spread, Outliers
This training helps learners explore key statistical concepts—center, spread, and outliers—to better understand data distributions.
12 slides·24 min
Sampling and Bias Essentials
A concise introduction to sampling and bias for beginners, covering key concepts and how to identify common sources of bias in data collection.
13 slides·26 min
Correlation, Causation, Confounding
Learn to distinguish correlation from causation and identify confounding variables in data analysis.
13 slides·26 min
Regression Analysis Fundamentals
This training introduces foundational regression concepts, including lines of best fit, residuals, and pattern analysis, for learners new to statistical modeling.
13 slides·26 min
P-Value Concepts and Applications
This training explains the concept of p-value in statistics, its purpose in hypothesis testing, and practical examples for learners seeking to interpret statistical significance.
14 slides·28 min
Statistical Power Fundamentals
Learn the core concepts of statistical power, its purpose in hypothesis testing, and practical examples for designing robust studies. Ideal for researchers and analysts.
14 slides·28 min
Statistics Practice Problems
Practice statistics with interactive problems designed to build analytical skills for learners seeking hands-on experience in data interpretation and statistical reasoning.
14 slides·28 min
Statistics Workflow for Data Science Projects
Learn a practical workflow for applying statistics in data science projects, from data exploration to model validation. Ideal for aspiring data scientists seeking to build reliable, data-driven insights.
14 slides·28 min
Categorical Data Analysis
This training teaches learners to analyze categorical data using counts, proportions, and comparative methods for data-driven decision-making.
15 slides·30 min
Data Transformations: Scale & Units
This training explains how transforming data scales and units can affect the interpretation of results, helping analysts and data professionals make accurate conclusions.
13 slides·26 min
Misleading Statistics
Learn to identify common statistical fallacies and misleading data presentations, equipping professionals to critically evaluate statistics in reports, media, and research.
14 slides·28 min
Missing Data: Absence, Codes, Limits
Learn to identify and interpret missing data, including absence, codes, and limits, for data professionals.
13 slides·26 min
Statistical Methods for Data Science
This training introduces essential statistical methods for data science, equipping beginners with foundational concepts and techniques to analyze data effectively in practical applications.
14 slides·28 min
Time Series: Trends, Seasonality, and Change
Learn to analyze time series data by identifying trends, seasonal patterns, and detecting changes for effective forecasting and decision-making.
15 slides·30 min
Statistics Software: Selection and Workflow
This training helps data analysts and researchers select statistical software, define requirements, and build efficient analysis workflows.
14 slides·28 min
Statistical Parameters: Concepts and Examples
This training explains statistical parameters, their purpose, and practical examples for learners seeking a clear foundation in statistical concepts.
15 slides·30 min