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  • Statistical Analysis

Statistical Analysis Courses

Statistical analysis courses can help you learn data collection methods, hypothesis testing, regression analysis, and data visualization techniques. You can build skills in interpreting results, making predictions, and drawing conclusions from data sets. Many courses introduce tools such as R, Python, and Excel, that support performing statistical computations and creating visual representations of data.


Popular Statistical Analysis Courses and Certifications


  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Statistics

    Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.3K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Data Analysis with Python

    Skills you'll gain: Exploratory Data Analysis, Model Evaluation, Data Transformation, Data Analysis, Data Cleansing, Data Manipulation, Data Import/Export, Predictive Modeling, Data Preprocessing, Regression Analysis, Data Science, Statistical Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Matplotlib, Data Visualization, NumPy, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    20K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Statistical Analysis Fundamentals using Excel

    Skills you'll gain: Data Visualization, Descriptive Statistics, Regression Analysis, Forecasting, Business Analytics, Data Analysis, Statistical Analysis, Statistical Methods, Microsoft Excel, Statistics, Spreadsheet Software, Predictive Analytics, Probability

    4.6
    Rating, 4.6 out of 5 stars
    ·
    130 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Statistical Analysis with R for Public Health

    Skills you'll gain: Logistic Regression, Analytical Skills, Correlation Analysis, Regression Analysis, Sampling (Statistics), Statistical Hypothesis Testing, Data Literacy, Data Analysis, R Programming, Descriptive Statistics, Statistical Modeling, Biostatistics, Model Evaluation, Exploratory Data Analysis, Statistical Analysis, R (Software), Statistics, Statistical Methods, Data Wrangling, Public Health

    4.7
    Rating, 4.7 out of 5 stars
    ·
    2.1K reviews

    Beginner · Specialization · 3 - 6 Months

  • C

    Coursera

    Introduction to Data Analysis using Microsoft Excel

    Skills you'll gain: Microsoft Excel, Excel Formulas, Spreadsheet Software, Pivot Tables And Charts, Data Analysis, Data Manipulation, Microsoft Office, Data Mining

    4.7
    Rating, 4.7 out of 5 stars
    ·
    4.5K reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Statistics with Python

    Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Modeling, Statistical Methods, Statistical Inference, Bayesian Statistics, Data Visualization, Statistics, Matplotlib, Statistical Visualization, Statistical Software, Probability & Statistics, Model Evaluation, Statistical Analysis, Jupyter, Statistical Programming, Statistical Machine Learning, Regression Analysis, Data Visualization Software, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.3K reviews

    Beginner · Specialization · 1 - 3 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    R

    Rice University

    Business Statistics and Analysis

    Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Statistical Methods, Pivot Tables And Charts, Regression Analysis, Statistics, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Modeling, Statistical Analysis, Statistical Inference, Excel Formulas, Data Analysis, Data Presentation, Model Evaluation, Sample Size Determination

    4.7
    Rating, 4.7 out of 5 stars
    ·
    13K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    The Power of Statistics

    Skills you'll gain: Sampling (Statistics), Descriptive Statistics, Statistical Hypothesis Testing, Data Analysis, Probability Distribution, Statistics, Data Science, Statistical Analysis, A/B Testing, Statistical Methods, Probability, Statistical Inference, Statistical Programming, Python Programming, Technical Communication

    4.8
    Rating, 4.8 out of 5 stars
    ·
    860 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Data Analysis with R

    Skills you'll gain: Bayesian Statistics, Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Peer Review, Regression Analysis, R (Software), Statistical Reporting, Probability Distribution, Statistical Analysis, Statistics, Data Analysis Software, Data Analysis, Probability & Statistics, Probability, R Programming, Statistical Modeling, Statistical Methods, Data Visualization

    4.7
    Rating, 4.7 out of 5 stars
    ·
    7.6K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Statistics and Calculus Methods for Data Analysis

    Skills you'll gain: Statistical Analysis, Statistical Modeling, Predictive Modeling, Data Analysis, Statistics, Integral Calculus, Probability & Statistics, Data Science, Probability Distribution, Calculus, Mathematics and Mathematical Modeling, Applied Mathematics, Derivatives, Mathematical Modeling, Machine Learning, Algorithms

    Build toward a degree

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Statistics for Data Science

    Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, Probability Distribution, R Programming, Biostatistics, Data Science, Statistics, Mathematical Modeling, Data Analysis, Data Modeling, Applied Mathematics

    4.4
    Rating, 4.4 out of 5 stars
    ·
    783 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    S

    SkillUp

    Advanced Statistical Analysis and Tools

    Skills you'll gain: Statistical Process Controls, Statistical Hypothesis Testing, Process Improvement, Lean Methodologies, Kaizen Methodology, Process Capability, Six Sigma Methodology, Risk Analysis, Quality Improvement, Process Analysis, Statistical Analysis, Statistical Methods, Risk Management, Business Process, Sample Size Determination, Data Collection, Graphing

    5
    Rating, 5 out of 5 stars
    ·
    7 reviews

    Intermediate · Course · 1 - 4 Weeks

Searches related to statistical analysis

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In summary, here are 10 of our most popular statistical analysis courses

  • Introduction to Statistics: Stanford University
  • Data Analysis with Python: IBM
  • Statistical Analysis Fundamentals using Excel: IBM
  • Statistical Analysis with R for Public Health: Imperial College London
  • Introduction to Data Analysis using Microsoft Excel: Coursera
  • Statistics with Python: University of Michigan
  • Business Statistics and Analysis: Rice University
  • The Power of Statistics: Google
  • Data Analysis with R: Duke University
  • Statistics and Calculus Methods for Data Analysis: University of Pittsburgh

Skills you can learn in Business Essentials

Analytics (37)
Presentation (33)
Modeling (29)
Business Analytics (27)
Language (26)
Microsoft Excel (26)
Writing (26)
Speech (18)
Plan (17)
Business Communication (16)
Decision-making (16)
Leadership (15)

Frequently Asked Questions about Statistical Analysis

Statistical analysis is the process of collecting, examining, interpreting, and presenting data to uncover patterns and insights. It plays a crucial role in various fields, including business, healthcare, and social sciences, as it helps organizations make informed decisions based on empirical evidence. By applying statistical methods, individuals can identify trends, test hypotheses, and predict future outcomes, making statistical analysis an essential skill in today's data-driven world.‎

A background in statistical analysis can open doors to various career opportunities. Some common job titles include data analyst, statistician, market researcher, and biostatistician. These roles often involve analyzing data to inform business strategies, conducting surveys, or evaluating clinical trials. Additionally, positions in academia and research institutions are also available for those interested in furthering their expertise in statistical analysis.‎

To excel in statistical analysis, you should develop a range of skills. Key competencies include proficiency in statistical software (such as R, Python, or SAS), a solid understanding of statistical concepts (like hypothesis testing and regression analysis), and the ability to interpret and communicate data findings effectively. Familiarity with data visualization tools and techniques is also beneficial, as it helps present complex information in an accessible manner.‎

There are several excellent online courses available for those interested in statistical analysis. For instance, the Statistical Analysis with R for Public Health Specialization offers a comprehensive introduction to statistical methods using R. Another option is the Inferential Statistical Analysis with Python, which focuses on applying statistical techniques in Python. These courses provide valuable knowledge and practical skills for aspiring analysts.‎

Yes. You can start learning statistical analysis on Coursera for free in two ways:

  1. Preview the first module of many statistical analysis courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in statistical analysis, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn statistical analysis effectively, start by identifying your goals and the specific areas you wish to explore. Enroll in online courses that match your interests and skill level, and practice regularly with real datasets to reinforce your learning. Engaging with online communities or study groups can also provide support and motivation. As you progress, consider applying your skills to projects or case studies to gain practical experience.‎

Statistical analysis courses typically cover a variety of topics, including descriptive statistics, inferential statistics, regression analysis, hypothesis testing, and data visualization. Additionally, many courses may introduce statistical software tools and programming languages, such as R or Python, to help learners apply statistical techniques in real-world scenarios. Understanding these topics is essential for anyone looking to build a strong foundation in statistical analysis.‎

For training and upskilling employees in statistical analysis, courses like the SAS Statistical Business Analyst Professional Certificate can be particularly beneficial. This program equips learners with essential skills in data analysis and statistical methods, making it suitable for professionals looking to enhance their analytical capabilities in the workplace.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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