What knowledge and skills can you gain from statistics courses on Coursera?

Statistics courses on Coursera can help equip you with analytical skills and mathematical knowledge to effectively interpret data: Understanding of statistical theory, including probability, distributions, and hypothesis testing. Skills in applying statistical methods to real-world problems across various industries. Proficiency in using statistical software tools like R, Python, or SPSS to analyze and visualize data. Techniques for designing experiments and surveys to collect data efficiently. Knowledge of regression analysis, ANOVA, and other statistical models. Insights into big data analytics, including machine learning algorithms driven by statistical principles. Application of statistics in specialized fields such as biostatistics, econometrics, or psychological statistics.

Do I need prior knowledge in statistics to enroll in these courses?

Statistics courses on Coursera are designed to accommodate learners at different stages of their educational or professional journey: Introductory courses are suitable for those new to statistics, offering foundational knowledge and basic application skills. Intermediate courses build upon basic statistics knowledge, introducing more complex analyses and applications. Advanced courses cater to individuals with a solid background in statistics, focusing on specialized topics or advanced analytical techniques.

What types of certifications and credentials can you pursue through statistics courses on Coursera?

Coursera provides various educational pathways to help validate your skills in statistics: Professional certificates that can help you demonstrate your competence in statistical analysis. Specialized course certificates that focus on particular aspects of statistics, such as data science or predictive analytics. Degree programs and professional qualifications that prepare you for roles involving extensive use of statistics. These credentials are intended to enhance your professional qualifications and assist you in advancing your career in fields reliant on statistical analysis.

What career opportunities can knowledge in statistics lead to?

Studying statistics on Coursera can prepare you for a variety of roles in data-intensive sectors: Data Analyst : Utilize statistical tools and methods to interpret data and inform business decisions. Statistical Consultant: Provide expertise to organizations on statistical methods, data collection, and analysis. Biostatistician : Apply statistics to biological sciences and public health. Econometrician: Use statistical techniques to study economic data and trends. Quality Control Analyst: Implement statistical methods to assess product quality and maintain standards.

Top Statistics Courses - Learn Statistics Online

Explore the Statistics Course Catalog

University of Colorado Boulder
Data Science Foundations: Statistical Inference
Skills you'll gain: Statistical Hypothesis Testing, Probability, Statistical Inference, Statistical Methods, Probability Distribution, Probability & Statistics, Statistics, Bayesian Statistics, Data Science, Sampling (Statistics), Statistical Analysis, Data Ethics, Quantitative Research, Sample Size Determination, Descriptive Statistics
Build toward a degree
4.4
Rating, 4.4 out of 5 stars
315 reviews
Intermediate · Specialization · 3 - 6 Months
Duke University
Data Analysis with R
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Statistical Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Modeling, Probability & Statistics, Probability, Statistics, Data Science, Descriptive Statistics, Predictive Modeling
4.7
Rating, 4.7 out of 5 stars
7.5K reviews
Beginner · Specialization · 3 - 6 Months
Status: [object Object]
IBM
IBM Data Science
Skills you'll gain: Dashboard, Data Visualization Software, Data Wrangling, Data Visualization, SQL, Supervised Learning, Feature Engineering, Plotly, Interactive Data Visualization, Jupyter, Exploratory Data Analysis, Data Mining, Data Cleansing, Matplotlib, Data Analysis, Unsupervised Learning, Generative AI, Pandas (Python Package), Data Manipulation, Professional Networking
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
140K reviews
Beginner · Professional Certificate · 3 - 6 Months
DeepLearning.AI
Mathematics for Machine Learning and Data Science
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Linear Algebra, Statistical Inference, A/B Testing, Applied Mathematics, NumPy, Calculus, Dimensionality Reduction, Machine Learning, Jupyter, Python Programming, Data Transformation, Data Manipulation, Data Science
4.6
Rating, 4.6 out of 5 stars
2.6K reviews
Intermediate · Specialization · 1 - 3 Months
Coursera Project Network
Statistics For Data Science
Skills you'll gain: Correlation Analysis, Probability & Statistics, Statistics, Statistical Analysis, Data Analysis, Sampling (Statistics), Data Science, Probability Distribution, Descriptive Statistics, Statistical Inference, Exploratory Data Analysis
3.9
Rating, 3.9 out of 5 stars
31 reviews
Beginner · Guided Project · Less Than 2 Hours
Imperial College London
Introduction to Statistics & Data Analysis in Public Health
Skills you'll gain: Analytical Skills, Sampling (Statistics), Statistical Hypothesis Testing, Statistical Analysis, Data Analysis, Exploratory Data Analysis, Quantitative Research, Probability & Statistics, R Programming, Statistics, Descriptive Statistics, Probability Distribution, Data Import/Export
4.7
Rating, 4.7 out of 5 stars
1.5K reviews
Beginner · Course · 1 - 4 Weeks
Johns Hopkins University
Data Science
Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Leaflet (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Visualization, Plotly, Machine Learning Algorithms, Interactive Data Visualization, Probability & Statistics, Knitr
4.5
Rating, 4.5 out of 5 stars
51K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free
University of Zurich
An Intuitive Introduction to Probability
Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Descriptive Statistics, Applied Mathematics, Statistical Methods, Risk Analysis, Financial Modeling
4.8
Rating, 4.8 out of 5 stars
1.8K reviews
Beginner · Course · 1 - 3 Months
Imperial College London
Statistical Analysis with R for Public Health
Skills you'll gain: Analytical Skills, Correlation Analysis, Regression Analysis, Sampling (Statistics), Statistical Hypothesis Testing, Statistical Analysis, Data Analysis, R Programming, Descriptive Statistics, Statistical Modeling, Quantitative Research, Exploratory Data Analysis, Probability & Statistics, Statistics, Statistical Methods, Data Wrangling, Biostatistics, Time Series Analysis and Forecasting, Probability Distribution, Predictive Modeling
4.7
Rating, 4.7 out of 5 stars
2K reviews
Beginner · Specialization · 3 - 6 Months
Coursera Project Network
Basic Statistics in Python (Correlations and T-tests)
Skills you'll gain: Exploratory Data Analysis, Box Plots, Correlation Analysis, Data Visualization, Scatter Plots, Data Cleansing, Statistical Visualization, Data Manipulation, Pandas (Python Package), Statistical Hypothesis Testing, Descriptive Statistics, Statistical Analysis, Data Analysis, Probability & Statistics, Python Programming
4.3
Rating, 4.3 out of 5 stars
32 reviews
Beginner · Guided Project · Less Than 2 Hours
Imperial College London
Mathematics for Machine Learning
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Data Transformation, Jupyter, Data Science, Advanced Mathematics, Statistics, Numerical Analysis, Geometry, Statistical Analysis, Machine Learning Methods, Artificial Neural Networks, Algorithms, Data Manipulation, Machine Learning
4.6
Rating, 4.6 out of 5 stars
15K reviews
Beginner · Specialization · 3 - 6 Months
University of Colorado Boulder
Statistical Modeling for Data Science Applications
Skills you'll gain: Statistical Inference, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, R Programming, Data Ethics, Experimentation, Research Design, Statistical Methods, Data Science, Data Analysis, Statistical Analysis, Data Modeling, Predictive Modeling, Predictive Analytics, Probability & Statistics, Mathematical Modeling, Forecasting, A/B Testing, Quantitative Research
Build toward a degree
4.1
Rating, 4.1 out of 5 stars
52 reviews
Intermediate · Specialization · 3 - 6 Months