What is statistical modeling?

Statistical modeling is the process of using statistics to analyze data and make it usable for decision-making and analysis. It involves using computer programs to pull out numbers from data sets, identify trends, make predictions, and understand different situations. Most statistical modeling results in charts, graphs, or other types of reports to explain the data.

Why is it important to learn statistical modeling?

It's important to learn statistical modeling for many reasons to comprehend related material as a student and fulfill work-related requirements. Students often need to learn it because it's used in many different academic fields to understand the material. Many occupations either involve doing statistical analysis or being able to use the output in order to make decisions. Because of the way that data is reported in the media, it's helpful for members of the general public to have some understanding of how statistical modeling works.

What are typical careers that use statistical modeling?

Typical careers that use statistical modeling are medical research, scientific research, and financial analysis, but it is a component of many different fields. People working in marketing and sales use statistical modeling to build forecasts and generate prospects. Business managers use it to make decisions and to share information. Academics use it to understand trends and patterns in their fields. Journalists use statistical modeling to present information in their stories. By turning data into usable information, including charts and graphs, statistical modeling can add value to many different fields. People who understand the fundamentals of quantitative modeling and statistical model can expect the skill to enhance their careers.

How can taking online courses on Coursera help me learn statistical modeling?

Taking online courses on Coursera can help you learn statistical modeling in different ways, depending on your interests and needs. Some courses cover the fundamentals of statistics, which may be helpful if you have little background in the area. Others look at how statistical modeling is done with different software packages, such as Python, Excel, or SAS. Many classes focus on the uses of statistical modeling in specific fields, such as artificial intelligence, finance, or history. All classes include projects that help you apply what you learn.

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

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

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

When looking to enhance your workforce's skills in Statistical Modeling, 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 Modeling Courses - Learn Statistical Modeling Online

Explore the Statistical Modeling Course Catalog

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
Johns Hopkins University
R Programming
Skills you'll gain: Statistical Analysis, R Programming, Statistical Programming, Data Analysis, Debugging, Simulations, Program Development, Software Installation, Computer Programming, Data Structures, Performance Tuning, Data Import/Export
4.5
Rating, 4.5 out of 5 stars
22K reviews
Intermediate · Course · 1 - 4 Weeks
University of Colorado Boulder
Statistical Inference for Estimation in Data Science
Skills you'll gain: Statistical Inference, Statistical Methods, Probability & Statistics, Sampling (Statistics), Statistical Analysis, Data Science, Probability Distribution
4.1
Rating, 4.1 out of 5 stars
86 reviews
Intermediate · Course · 1 - 3 Months
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
Johns Hopkins University
Regression Models
Skills you'll gain: Regression Analysis, Statistical Analysis, Statistical Modeling, Correlation Analysis, Data Analysis, Statistical Methods, Predictive Modeling, Probability & Statistics, Statistical Inference, Statistical Hypothesis Testing
4.4
Rating, 4.4 out of 5 stars
3.4K reviews
Mixed · Course · 1 - 4 Weeks
Johns Hopkins University
Infectious Disease Modeling in Practice
Skills you'll gain: Epidemiology, Mathematical Modeling, Infectious Diseases, Risk Modeling, Biostatistics, Statistical Modeling, Predictive Modeling, Forecasting, Data Analysis, Statistics
4.8
Rating, 4.8 out of 5 stars
9 reviews
Intermediate · Course · 1 - 4 Weeks
University of Minnesota
Introduction to Predictive Modeling
Skills you'll gain: Time Series Analysis and Forecasting, Predictive Modeling, Regression Analysis, Microsoft Excel, Forecasting, Pivot Tables And Charts, Data Transformation, Data Cleansing, Statistical Methods, Business Analytics
4.8
Rating, 4.8 out of 5 stars
127 reviews
Mixed · Course · 1 - 4 Weeks
Multiple educators
Data Science Foundations
Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Mining, Pandas (Python Package), Data Visualization Software, Correlation Analysis, Web Scraping, NumPy, R Programming, Probability & Statistics, Predictive Modeling, Big Data, Automation, Computer Programming Tools, GitHub, Data Analysis Software, Machine Learning Algorithms, Unsupervised Learning
4.6
Rating, 4.6 out of 5 stars
111K reviews
Beginner · Specialization · 3 - 6 Months
University of Amsterdam
Methods and Statistics in Social Sciences
Skills you'll gain: Qualitative Research, Statistical Hypothesis Testing, Scientific Methods, Descriptive Statistics, Statistical Inference, Statistical Analysis, Statistical Software, Probability Distribution, Research, Correlation Analysis, Research Design, Sampling (Statistics), Research Reports, Science and Research, Probability, Interviewing Skills, Data Analysis, Sample Size Determination, Statistical Methods, Social Sciences
4.6
Rating, 4.6 out of 5 stars
7.6K reviews
Beginner · Specialization · 3 - 6 Months
University of Colorado Boulder
Modeling Climate Anomalies with Statistical Analysis
Skills you'll gain: Matplotlib, Pandas (Python Package), Statistical Analysis, Data Science, Data Analysis, Python Programming, Data Visualization Software, NumPy, Statistical Modeling, Time Series Analysis and Forecasting, Regression Analysis, Data Integration, Data Manipulation, Application Programming Interface (API)
Build toward a degree
Intermediate · Course · 1 - 4 Weeks
SAS
Statistical Thinking for Industrial Problem Solving, presented by JMP
Skills you'll gain: Exploratory Data Analysis, Data Compilation, Correlation Analysis, Data Collection, Statistical Inference, Statistical Process Controls, Statistical Methods, Predictive Modeling, Data Analysis, Statistical Hypothesis Testing, Data-Driven Decision-Making, Regression Analysis, Statistical Analysis, Experimentation, Probability & Statistics, Descriptive Statistics, Interactive Data Visualization
4.9
Rating, 4.9 out of 5 stars
90 reviews
Beginner · Course · 1 - 3 Months
Johns Hopkins University
Data Science: Foundations using R
Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Visualization, Statistical Programming, Ggplot2, Dimensionality Reduction, Data Visualization Software, Data Integration, Knitr, Data Analysis, Data Import/Export, General Science and Research, Data Sharing, Statistical Reporting
4.6
Rating, 4.6 out of 5 stars
48K reviews
Beginner · Specialization · 3 - 6 Months