What is statistical analysis?

Statistical analysis is the process of collecting and organizing data in order to observe patterns in that data. This discipline examines numerical data for trends, and it has practical applications across multiple industries and business sectors. Statistical analysts can examine large or small amounts of data to determine what the data shows—and what should be done with that information. The business world has relied on statistical analysis for years, but the advent of computer technology has made analyzing large amounts of data increasingly easy. Computers allow statisticians to analyze copious amounts of data and look for more specific patterns and trends than ever before.

Why is statistical analysis important?

Statistical analysis is important because it helps you make sense—and make use—of data. No matter what industry you work in, you see data every day. You may not know how to interpret the data, or there may just be too much data to understand on its own merits. Using statistical analysis can help you interpret key patterns in your data and sort out extraneous information to understand what the data means and what you should do about it. If you have a background in statistical analysis, you can also test or disprove any analysis that you receive from someone else as well.

What are typical careers that use statistical analysis?

A thorough knowledge of statistical analysis can help you find a career in the financial sector, information technology, or other areas of the business world. You can find jobs giving businesses advice on how to invest or how to manage their money more efficiently, or you can consult with companies on how to budget for large projects. Market research jobs rely on statistical analysis skills, while software engineers analyze data to develop and test new and updated applications. Data scientists work with various organizations to help them identify patterns and trends in their field of business.

How can online courses on Coursera help me learn statistical analysis?

From courses that introduce you to the basics of statistical analysis to more specific topics like hypothesis testing, data analysis in the health care industry, or risk management, you can gain a confident base of knowledge from online courses on Coursera. Specific topics you can discover include using logistic regression in R, survival analysis in R, bias and validity in epidemiology, statistics with Python, and data analytics.

What are the benefits of taking an online Statistical Analysis course?

Online Statistical Analysis courses offer a convenient and flexible way to enhance your knowledge or learn new Statistical Analysis skills. Choose from a wide range of Statistical Analysis courses offered by top universities and industry leaders tailored to various skill levels.

What Statistical Analysis courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in Statistical Analysis, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here .

Top Statistical Analysis Courses - Learn Statistical Analysis Online

Explore the Statistical Analysis Course Catalog

Status: Free
University of Cape Town
Doing Clinical Research: Biostatistics with the Wolfram Language
Skills you'll gain: Descriptive Statistics, Plot (Graphics), Statistical Analysis, Statistical Programming, Biostatistics, Statistical Hypothesis Testing, Data Analysis, Quantitative Research, Data Visualization Software, Probability & Statistics, Deep Learning, Machine Learning
4.7
Rating, 4.7 out of 5 stars
49 reviews
Beginner · Course · 1 - 4 Weeks
IBM
Statistics for Data Science with Python
Skills you'll gain: Descriptive Statistics, Statistical Analysis, Data Analysis, Probability Distribution, Statistics, Data Visualization, Statistical Hypothesis Testing, Regression Analysis, Data Science, Matplotlib, Exploratory Data Analysis, Statistical Inference, Probability, Correlation Analysis, Pandas (Python Package), Jupyter
4.5
Rating, 4.5 out of 5 stars
428 reviews
Mixed · Course · 1 - 3 Months
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
Coursera Project Network
Data Analysis Using Pyspark
Skills you'll gain: PySpark, Matplotlib, Apache Spark, Big Data, Data Processing, Distributed Computing, Data Management, Data Visualization, Data Analysis, Data Manipulation, Data Cleansing, Query Languages, Google Cloud Platform
4.5
Rating, 4.5 out of 5 stars
296 reviews
Intermediate · Guided Project · Less Than 2 Hours
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
SAS
SAS Statistical Business Analyst
Skills you'll gain: SAS (Software), Predictive Modeling, Predictive Analytics, Statistical Hypothesis Testing, Statistical Analysis, Correlation Analysis, Statistical Modeling, Regression Analysis, Statistical Methods, Probability & Statistics, Big Data, Plot (Graphics), Data Analysis, Data Analysis Software, Analysis, Feature Engineering, Performance Analysis, Performance Measurement, Data Cleansing
4.6
Rating, 4.6 out of 5 stars
215 reviews
Intermediate · Professional Certificate · 3 - 6 Months
Johns Hopkins University
Data – What It Is, What We Can Do With It
Skills you'll gain: Data Visualization, Data Analysis, Research Design, Data Presentation, Descriptive Statistics, Analytics, Statistical Analysis, Quantitative Research, Statistical Methods, Probability & Statistics
4.6
Rating, 4.6 out of 5 stars
172 reviews
Beginner · Course · 1 - 4 Weeks
University of Colorado Boulder
Statistics and Data Analysis with Excel, Part 2
Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Sampling (Statistics), Statistical Methods, Microsoft Excel, Probability & Statistics, Data Analysis, Regression Analysis, Statistical Inference, Statistical Modeling
5
Rating, 5 out of 5 stars
6 reviews
Intermediate · Course · 1 - 3 Months
Status: Free
Universiteit Leiden
Population Health: Responsible Data Analysis
Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Regression Analysis, R Programming, Data Analysis, Descriptive Statistics, Statistical Methods, Probability & Statistics, Data Ethics, Data Collection, Exploratory Data Analysis, Statistical Reporting, Data Management, Science and Research, Data Cleansing
4.6
Rating, 4.6 out of 5 stars
43 reviews
Beginner · Course · 1 - 3 Months
IBM
Introduction to Data Analytics
Skills you'll gain: Big Data, Data Analysis, Statistical Analysis, Apache Hadoop, Apache Hive, Data Collection, Data Mart, Data Warehousing, Data Storytelling, Apache Spark, Data Cleansing, Data Lakes, Data Visualization Software, SQL
4.8
Rating, 4.8 out of 5 stars
18K reviews
Beginner · Course · 1 - 3 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
University of Michigan
Introduction to Data Science in Python
Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles
4.5
Rating, 4.5 out of 5 stars
27K reviews
Intermediate · Course · 1 - 4 Weeks