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    • Statistics

    Statistics Courses

    Statistics courses can help you learn how to collect, analyze, and interpret data to make informed decisions in fields like science, business, and healthcare.

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    Find the Best Statistics Course for Your Goals

    • University of Michigan

      Applied Machine Learning in Python

      Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Dimensionality Reduction, Random Forest Algorithm

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8.6K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free

      The State University of New York

      Practical Time Series Analysis

      Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, R Programming, Statistical Analysis, Data Analysis, Data Visualization, Mathematical Modeling, Statistical Modeling, Predictive Modeling, Correlation Analysis, Regression Analysis, Descriptive Statistics, Statistical Inference, Software Installation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.7K reviews

      Intermediate · Course · 1 - 3 Months

    • Johns Hopkins University

      Multiple Regression Analysis in Public Health

      Skills you'll gain: Biostatistics, Regression Analysis, Statistical Methods, Public Health, Probability & Statistics, Statistical Analysis, Statistical Inference, Advanced Analytics, Statistical Modeling, Predictive Modeling, Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      308 reviews

      Beginner · Course · 1 - 4 Weeks

    • University of Colorado Boulder

      Data Science Foundations: Statistical Inference

      Skills you'll gain: Statistical Hypothesis Testing, Probability, Probability & Statistics, Statistical Inference, Statistical Methods, Probability Distribution, Statistics, Bayesian Statistics, Statistical Modeling, Data Science, Sampling (Statistics), Statistical Analysis, Data Ethics, Quantitative Research

      Build toward a degree

      4.4
      Rating, 4.4 out of 5 stars
      ·
      322 reviews

      Intermediate · Specialization · 3 - 6 Months

    • University of Colorado Boulder

      Statistical Inference and Hypothesis Testing in Data Science Applications

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Data Ethics, Probability & Statistics, Statistical Inference, Statistical Analysis, Quantitative Research, Statistics, Probability Distribution

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      50 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free

      University of Washington

      Computational Neuroscience

      Skills you'll gain: Supervised Learning, Network Model, Matlab, Machine Learning Algorithms, Artificial Neural Networks, Neurology, Computer Science, Reinforcement Learning, Computational Thinking, Mathematical Modeling, Biology, Linear Algebra, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 3 Months

    • University of London

      International Business Essentials

      Skills you'll gain: Financial Statements, Business Planning, Sampling (Statistics), Leadership and Management, Descriptive Statistics, Team Management, Team Building, Organizational Structure, Data Presentation, Professional Networking, Communication, Organizational Change, Business Mathematics, Business Strategy, Professionalism, Resource Allocation, Competitive Analysis, Linear Algebra, Mathematical Modeling, Business Strategies

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Johns Hopkins University

      Getting and Cleaning Data

      Skills you'll gain: Data Manipulation, Data Cleansing, Data Wrangling, Data Integration, Data Quality, Data Transformation, Data Import/Export, Data Collection, Data Management, Web Scraping, Data Access, R Programming, Exploratory Data Analysis, MySQL, File Management, SQL, Application Programming Interface (API)

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • Packt

      R Programming for Statistics and Data Science

      Skills you'll gain: R Programming, Exploratory Data Analysis, Statistical Hypothesis Testing, Ggplot2, Data Manipulation, Data Science, Tidyverse (R Package), Data Structures, Data Analysis, Statistical Analysis, Regression Analysis, Statistical Inference, Probability & Statistics, Data Transformation, Integrated Development Environments

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      Status: AI skills
      AI skills

      DeepLearning.AI

      DeepLearning.AI Data Analytics

      Skills you'll gain: Data Storytelling, Web Scraping, Google Sheets, Data Visualization, Data Presentation, Spreadsheet Software, Large Language Modeling, Dashboard, Pandas (Python Package), Interactive Data Visualization, Time Series Analysis and Forecasting, Probability & Statistics, Extract, Transform, Load, Statistical Analysis, Statistics, Statistical Modeling, Matplotlib, Data Manipulation, Data Visualization Software, Data Validation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      62 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Multiple educators

      Machine Learning for Trading

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Machine Learning, Google Cloud Platform, Applied Machine Learning, Financial Trading, Reinforcement Learning, Supervised Learning, Data Pipelines, Time Series Analysis and Forecasting, Statistical Machine Learning, Technical Analysis, Deep Learning, Portfolio Management, Machine Learning Methods, Artificial Neural Networks, Market Trend, Securities Trading, Artificial Intelligence and Machine Learning (AI/ML), Financial Market

      3.9
      Rating, 3.9 out of 5 stars
      ·
      1.1K reviews

      Intermediate · Specialization · 1 - 3 Months

    • IBM

      Exploratory Data Analysis for Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Statistical Inference, Data Processing, Data Access, Anomaly Detection, Statistical Analysis, Data Analysis, Data Cleansing, Data Manipulation, Machine Learning, Probability & Statistics, Data Transformation, Workflow Management, Scalability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.2K reviews

      Intermediate · Course · 1 - 3 Months

    Searches related to statistics

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    1…141516…105

    In summary, here are 10 of our most popular statistics courses

    • Applied Machine Learning in Python: University of Michigan
    • Practical Time Series Analysis: The State University of New York
    • Multiple Regression Analysis in Public Health : Johns Hopkins University
    • Data Science Foundations: Statistical Inference: University of Colorado Boulder
    • Statistical Inference and Hypothesis Testing in Data Science Applications: University of Colorado Boulder
    • Computational Neuroscience: University of Washington
    • International Business Essentials: University of London
    • Getting and Cleaning Data: Johns Hopkins University
    • R Programming for Statistics and Data Science: Packt
    • DeepLearning.AI Data Analytics: DeepLearning.AI

    Why Learn Statistics?

    Statistics is the science of collecting, analyzing, and interpreting data to uncover patterns and inform decisions. It’s essential in fields like business, healthcare, social science, and data analytics. Learning statistics can help you make sense of data, support evidence-based thinking, and contribute to smarter outcomes in any field.

    Frequently Asked Questions about Statistics

    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.‎

    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. ‎

    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.‎

    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.‎

    Yes, Coursera offers a variety of free courses across many topics, including statistics. While you can access most course materials for free by auditing the courses, this does not include graded assignments or a completion certificate. For those looking to obtain a certificate to showcase their learning or enhance their professional profile, Coursera provides the option to purchase the course. Additionally, Coursera offers free trials or financial aid to learners who qualify, making certifications more accessible to everyone.‎

    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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