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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

    • I

      IBM

      IBM Data Management

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Data Governance, Data Security, Data Migration, Database Design, Data Literacy, Descriptive Statistics, Extract, Transform, Load, Data Mining, Cloud Storage, Data Visualization Software, Data Store, IBM DB2, Data Management, Relational Databases, MySQL, Excel Formulas

      4.7
      Rating, 4.7 out of 5 stars
      ·
      16K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • M

      Meta

      Meta Marketing Science Certification Prep

      Skills you'll gain: Marketing Analytics, Bayesian Statistics, Descriptive Statistics, Marketing Effectiveness, Statistical Hypothesis Testing, A/B Testing, Target Audience, Marketing Strategies, Marketing Planning, Statistical Inference, Sampling (Statistics), Data Collection, Data Modeling, Statistics, Advertising Campaigns, Campaign Management, Marketing, Analytics, Google Analytics, Data Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.7K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Natural Language Processing

      Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Algorithms, Keras (Neural Network Library), Linear Algebra, Data Cleansing, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      BI Foundations with SQL, ETL and Data Warehousing

      Skills you'll gain: Data Warehousing, SQL, Extract, Transform, Load, Apache Airflow, Linux Commands, IBM Cognos Analytics, Data Pipelines, Apache Kafka, Bash (Scripting Language), Shell Script, Dashboard, File Management, Star Schema, Unix Shell, IBM DB2, Business Intelligence, Interactive Data Visualization, Databases, Stored Procedure, Relational Databases

      4.6
      Rating, 4.6 out of 5 stars
      ·
      24K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google

      Data Analysis with R Programming

      Skills you'll gain: Rmarkdown, Ggplot2, R Programming, Data Analysis, Tidyverse (R Package), Statistical Programming, Data Visualization Software, Data Cleansing, Data Manipulation, Exploratory Data Analysis, Data Import/Export, Package and Software Management, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      11K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      IBM Business Intelligence (BI) Analyst

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Database Design, MySQL, Presentations, Descriptive Statistics, Extract, Transform, Load, Business Intelligence, IBM DB2, Tableau Software, Relational Databases, Star Schema, Data Visualization Software, Interactive Data Visualization, Regression Analysis, Data-Driven Decision-Making, Excel Formulas, Microsoft Excel

      4.7
      Rating, 4.7 out of 5 stars
      ·
      14K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • J

      Johns Hopkins University

      R Programming

      Skills you'll gain: Statistical Analysis, R Programming, Statistical Programming, Data Analysis, Debugging, Simulations, Computer Programming Tools, Program Development, Data Structures, Performance Tuning, Data Import/Export

      4.5
      Rating, 4.5 out of 5 stars
      ·
      22K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Introduction to Data Science in Python

      Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Structures, 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

    • U

      University of Maryland, College Park

      Survey Data Collection and Analytics

      Skills you'll gain: Sampling (Statistics), Sample Size Determination, Surveys, Survey Creation, Research Methodologies, Data Collection, Statistical Analysis, Statistical Software, Interviewing Skills, Data Integration, Data Ethics, Research Design, Stata, R Programming, Data Quality, Statistical Modeling, Qualitative Research, Descriptive Statistics, Statistical Programming, Data Cleansing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.4K reviews

      Beginner · Specialization · 3 - 6 Months

    • R

      Rice University

      Business Statistics and Analysis Capstone

      Skills you'll gain: Statistical Analysis, Data Analysis, Data Presentation, Statistics, Business Analysis, Statistical Reporting, Analytical Skills, Technical Communication, Exploratory Data Analysis, Data Manipulation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      437 reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of London

      Statistics and Clustering in Python

      Skills you'll gain: Pandas (Python Package), NumPy, Probability & Statistics, Unsupervised Learning, Data Science, Statistics, Data Analysis, Statistical Analysis, Jupyter, Machine Learning Algorithms, Data Manipulation, Descriptive Statistics, Matplotlib, Data Visualization Software, Python Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      11 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      RStudio for Six Sigma - Basic Descriptive Statistics

      Skills you'll gain: Sampling (Statistics), Statistical Methods, Descriptive Statistics, Data Visualization, Data Import/Export, Pareto Chart, Histogram, Statistical Analysis, Six Sigma Methodology, Box Plots, R Programming, Probability Distribution, Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      64 reviews

      Beginner · Guided Project · Less Than 2 Hours

    Searches related to statistics

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    statistics and data analysis with excel, part 1
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    1…91011…105

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

    • IBM Data Management: IBM
    • Meta Marketing Science Certification Prep: Meta
    • Natural Language Processing: DeepLearning.AI
    • BI Foundations with SQL, ETL and Data Warehousing: IBM
    • Data Analysis with R Programming: Google
    • IBM Business Intelligence (BI) Analyst: IBM
    • R Programming: Johns Hopkins University
    • Introduction to Data Science in Python: University of Michigan
    • Survey Data Collection and Analytics: University of Maryland, College Park
    • Business Statistics and Analysis Capstone: Rice University

    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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