Basic Statistics courses can help you learn data collection methods, descriptive statistics, probability distributions, and hypothesis testing. You can build skills in interpreting data sets, conducting surveys, and performing regression analysis. Many courses introduce tools like Excel, R, and Python, that support analyzing data and visualizing results. By applying these skills and tools, you can effectively communicate findings and make informed decisions based on statistical evidence.

University of Amsterdam
★ 4.6 (4.7K) · Beginner · Course

Skills you'll gain: Bayesian Statistics, Descriptive Statistics, Statistical Hypothesis Testing, Statistical Inference, Statistical Software, Sampling (Statistics), Data Modeling, Statistics, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Marketing Analytics, Tableau Software, Data Analysis, Spreadsheet Software, Analytics, Descriptive Analytics, Time Series Analysis and Forecasting, Regression Analysis
★ 4.8 (413) · Beginner · Course · 1 - 3 Months

University of Colorado Boulder
Skills you'll gain: Probability, Statistical Inference, Estimation, Probability & Statistics, Statistical Methods, Probability Distribution, Statistics, Markov Model, Statistical Analysis, Sampling (Statistics), Applied Mathematics, Artificial Intelligence, Generative AI, Data Analysis, Correlation Analysis, Data Science, Data Collection
★ 4.4 (373) · Intermediate · Specialization · 3 - 6 Months

Stanford Online
Skills you'll gain: Statistics, Statistical Inference, Probability & Statistics, Regression Analysis, Statistical Methods, Descriptive Statistics, Statistical Hypothesis Testing, Exploratory Data Analysis, Statistical Modeling, Statistical Analysis, Data Analysis, Sampling (Statistics), Probability Distribution, Probability, Statistical Visualization
★ 4.6 (4.3K) · Beginner · Course · 1 - 3 Months

Birla Institute of Technology & Science, Pilani
Skills you'll gain: Data Analysis, Statistical Analysis, Statistics, Statistical Methods, Data Visualization, Predictive Modeling, Applied Mathematics
★ 4.3 (13) · Beginner · Course · 1 - 3 Months

Skills you'll gain: Data Visualization, Descriptive Statistics, Statistical Hypothesis Testing, Regression Analysis, Forecasting, Probability Distribution, Data Analysis, Statistical Analysis, Statistical Methods, Analytics, Probability & Statistics, Microsoft Excel, Statistics, Spreadsheet Software, Probability, Model Evaluation
★ 4.6 (155) · Intermediate · Course · 1 - 3 Months

University of Michigan
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Modeling, Statistical Methods, Statistical Inference, Statistics, Bayesian Statistics, Data Visualization, Matplotlib, Statistical Visualization, Model Evaluation, Statistical Programming, Data-Driven Decision-Making, Probability & Statistics, Statistical Analysis, Regression Analysis, Predictive Modeling, Data Analysis, Exploratory Data Analysis, Python Programming
★ 4.6 (3.4K) · Beginner · Specialization · 1 - 3 Months

University of Colorado Boulder
Skills you'll gain: Probability Distribution, Exploratory Data Analysis, Probability, Descriptive Statistics, Statistical Modeling, Data Literacy, Statistics, Probability & Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Statistical Inference, Data Analysis, Diagnostic Tests, Histogram, Box Plots, Bayesian Statistics, Combinatorics, Statistical Hypothesis Testing, Quality Control
Beginner · Specialization · 3 - 6 Months

Arizona State University
Skills you'll gain: Statistical Methods, Bayesian Statistics, Statistics, Probability & Statistics, Analytics, Data Storage Technologies, Data Storage, Data Access, Estimation, Data-Driven Decision-Making, Applied Machine Learning, Logistic Regression, Simulations, Simulation and Simulation Software, Sampling (Statistics), Data Science, Data Visualization, Regression Testing
★ 4.3 (6) · Intermediate · Specialization · 3 - 6 Months

University of Michigan
Skills you'll gain: Statistics, Data Analysis, Statistical Programming, Descriptive Statistics, Python Programming
★ 4.8 (6) · Intermediate · Course · 1 - 4 Weeks

Real Madrid Graduate School Universidad Europea
Skills you'll gain: Data Presentation, Data Literacy, Matplotlib, Analytics, Probability Distribution, Data Processing, Probability & Statistics, Statistical Methods, Statistical Analysis, Probability, Data Cleansing, Computer Programming Tools, Data Collection, Performance Measurement, Python Programming, Technical Analysis
Beginner · Course · 1 - 4 Weeks

University of Colorado Boulder
Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Sample Size Determination, A/B Testing, Statistical Methods, Correlation Analysis, Statistical Inference, Statistical Modeling, Probability & Statistics, Predictive Modeling, Sampling (Statistics), Statistics, Analysis, Statistical Analysis, Business Analytics, Scatter Plots, Model Evaluation, Estimation, Data-Driven Decision-Making, Regression Testing
Beginner · Specialization · 3 - 6 Months
Top-rated Basic Statistics courses offered by University of Colorado Boulder on Coursera.
Earn a certificate in Basic Statistics from top universities and companies.
Top-rated beginner-friendly Basic Statistics courses with no prerequisites.
Basic statistics is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. It is essential because it provides the tools needed to make informed decisions based on data, which is increasingly important in various fields such as business, healthcare, social sciences, and more. Understanding basic statistics helps individuals interpret data accurately, recognize trends, and make predictions, which can significantly impact decision-making processes.‎
A background in basic statistics opens up various job opportunities across multiple sectors. Positions such as data analyst, market researcher, business analyst, and quality control analyst often require a solid understanding of statistical principles. Additionally, roles in healthcare, education, and social research also value statistical skills, as they rely on data analysis to inform practices and policies.‎
To learn basic statistics, you should focus on several key skills. These include understanding descriptive statistics (mean, median, mode), probability concepts, data visualization techniques, and basic inferential statistics (hypothesis testing, confidence intervals). Familiarity with statistical software or tools, such as Excel or R, can also enhance your ability to analyze data effectively.‎
There are several excellent online courses available for learning basic statistics. For instance, the Basic Statistics course provides a comprehensive introduction to the subject. Additionally, the Basic Inferential Statistics for Psychology Specialization offers a focused approach for those interested in psychology-related applications of statistics.‎
Yes. You can start learning basic statistics on Coursera for free in two ways:
If you want to keep learning, earn a certificate in basic statistics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎
Learning basic statistics can be approached through various methods. Start by enrolling in online courses that cover the fundamentals. Engage with interactive exercises and quizzes to reinforce your understanding. Additionally, practicing with real-world data sets can help solidify your skills. Joining study groups or forums can also provide support and enhance your learning experience.‎
Typical topics covered in basic statistics courses include descriptive statistics, probability theory, sampling methods, hypothesis testing, and regression analysis. These subjects provide a solid foundation for understanding how to analyze and interpret data effectively.‎
For training and upskilling employees, courses like the Business Statistics and Analysis Specialization are particularly beneficial. They focus on applying statistical methods to business contexts, making them ideal for workforce development in data-driven environments.‎