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

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
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
SAS
Statistics with SAS
Skills you'll gain: SAS (Software), Statistical Hypothesis Testing, Statistical Software, Statistical Analysis, Predictive Modeling, Statistical Programming, Statistical Modeling, Statistical Methods, Regression Analysis, Probability & Statistics, Data Analysis
4.7
Rating, 4.7 out of 5 stars
296 reviews
Intermediate · Course · 1 - 3 Months
University of California, Santa Cruz
Bayesian Statistics: From Concept to Data Analysis
Skills you'll gain: Bayesian Statistics, Statistical Inference, Data Analysis, Probability, Statistical Modeling, Statistical Analysis, Microsoft Excel, Probability Distribution, R Programming, Regression Analysis
4.6
Rating, 4.6 out of 5 stars
3.2K reviews
Intermediate · 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
University of Illinois Urbana-Champaign
Inferential and Predictive Statistics for Business
Skills you'll gain: Statistical Inference, Business Analytics, Statistical Analysis, Statistical Hypothesis Testing, Regression Analysis, Data-Driven Decision-Making, Statistical Methods, Probability & Statistics, Predictive Analytics, Microsoft Excel, Sampling (Statistics)
4.8
Rating, 4.8 out of 5 stars
859 reviews
Intermediate · Course · 1 - 3 Months
Johns Hopkins University
Statistical Inference
Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Probability & Statistics, Probability, Statistics, Bayesian Statistics, Statistical Methods, Statistical Modeling, Statistical Analysis, Probability Distribution, Sampling (Statistics)
4.2
Rating, 4.2 out of 5 stars
4.4K reviews
Mixed · Course · 1 - 4 Weeks
University of Amsterdam
Inferential Statistics
Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Statistical Software, Statistical Analysis, Statistical Methods, Quantitative Research, Sampling (Statistics), Probability & Statistics, Regression Analysis, Probability Distribution
4.3
Rating, 4.3 out of 5 stars
595 reviews
Mixed · Course · 1 - 3 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
Johns Hopkins University
Summary Statistics in Public Health
Skills you'll gain: Biostatistics, Histogram, Box Plots, Statistical Visualization, Epidemiology, Medical Science and Research, Quantitative Research, Descriptive Statistics, Probability & Statistics, Statistical Methods, Probability Distribution, Sample Size Determination
4.8
Rating, 4.8 out of 5 stars
2K reviews
Beginner · Course · 1 - 3 Months
Status: Free
Eindhoven University of Technology
Improving your statistical inferences
Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Quantitative Research, Bayesian Statistics, Statistical Analysis, Statistical Methods, Sample Size Determination, Data Analysis, Research, Research Design, General Science and Research, Research Methodologies, Data Sharing, Probability
4.9
Rating, 4.9 out of 5 stars
791 reviews
Intermediate · Course · 1 - 3 Months
Databricks
Introduction to Computational Statistics for Data Scientists
Skills you'll gain: Bayesian Statistics, Databricks, Sampling (Statistics), Statistical Modeling, Probability, Classification And Regression Tree (CART), Jupyter, Regression Analysis, Statistical Programming, Statistical Analysis, Statistical Machine Learning, Probability Distribution, Data Science, Markov Model, Simulations, Data Visualization, Probability & Statistics, Development Environment, Statistical Inference, Algorithms
4
Rating, 4 out of 5 stars
109 reviews
Beginner · Specialization · 1 - 3 Months