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    • Statistical Analysis

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    1392 results for "statistical analysis"

    • Imperial College London

      Imperial College London

      Statistical Analysis with R for Public Health

      Skills you'll gain: Analysis, Bayesian Statistics, Business Analysis, Correlation And Dependence, Data Analysis, Econometrics, General Statistics, Machine Learning, Machine Learning Algorithms, Mathematics, Probability & Statistics, Probability Distribution, R Programming, Regression, Statistical Analysis, Statistical Programming, Statistical Tests

      4.7

      (1.6k reviews)

      Beginner · Specialization

    • University of Michigan

      University of Michigan

      Inferential Statistical Analysis with Python

      Skills you'll gain: Data Analysis, Hypothesis, Python Programming, Statistical Programming, Computer Programming, Statistical Tests, Statistical Hypothesis Testing, Statistical Analysis, Analysis, Business Analysis, Confidence, Probability & Statistics, General Statistics, Hypothesis Testing, Inference, Experiment, Statistical Inference

      4.6

      (790 reviews)

      Intermediate · Course

    • SAS

      SAS

      Introduction to Statistical Analysis: Hypothesis Testing

      Skills you'll gain: Correlation And Dependence, Data Analysis, SAS (Software), General Statistics, Probability & Statistics, Regression, Statistical Programming, Analysis, Business Analysis, Statistical Tests, Statistical Analysis

      4.6

      (70 reviews)

      Intermediate · Course

    • Coursera Project Network

      Coursera Project Network

      Statistical Analysis using Python Numpy

      Skills you'll gain: Python Programming, Data Analysis, Probability & Statistics, Business Analysis, Computer Programming, Analysis, Statistical Programming, Numpy

      4.6

      (8 reviews)

      Intermediate · Guided Project

    • Coursera Project Network

      Coursera Project Network

      Visualization for Statistical Analysis

      Beginner · Guided Project

    • Google

      Google

      Google Data Analytics

      Skills you'll gain: Algorithms, Analysis, Application Development, Big Data, Budget Management, Business Analysis, Business Communication, Change Management, Cloud Computing, Communication, Computational Logic, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Model, Data Structures, Data Visualization, Data Visualization Software, Database Administration, Database Design, Databases, Decision Making, Design and Product, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, General Statistics, Interactive Data Visualization, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Metadata, Network Security, Other Programming Languages, Plot (Graphics), Probability & Statistics, Problem Solving, Product Design, Programming Principles, Project Management, R Programming, Research and Design, SQL, Security Engineering, Security Strategy, Small Data, Software Engineering, Software Security, Spreadsheet Software, Statistical Analysis, Statistical Programming, Storytelling, Strategy and Operations, Theoretical Computer Science, Visual Design

      4.8

      (63.7k reviews)

      Beginner · Professional Certificate

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      IBM

      IBM

      IBM Data Science

      Skills you'll gain: Algebra, Algorithms, Analysis, Business Analysis, Communication, Computational Logic, Computer Programming, Computer Programming Tools, Correlation And Dependence, Data Analysis, Data Clustering Algorithms, Data Management, Data Mining, Data Structures, Data Visualization, Database Administration, Database Application, Databases, Econometrics, Exploratory Data Analysis, Extract, Transform, Load, General Statistics, Geovisualization, Interactive Data Visualization, Machine Learning, Machine Learning Algorithms, Marketing, Mathematical Theory & Analysis, Mathematics, Plot (Graphics), Probability & Statistics, Python Programming, R Programming, Regression, SPSS, SQL, Spreadsheet Software, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Supply Chain Systems, Supply Chain and Logistics, Theoretical Computer Science

      4.6

      (93.7k reviews)

      Beginner · Professional Certificate

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      IBM

      IBM

      IBM Data Analyst

      Skills you'll gain: Algebra, Apache, Big Data, Business Analysis, Computational Logic, Computer Programming, Computer Programming Tools, Correlation And Dependence, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Structures, Data Visualization, Data Visualization Software, Data Warehousing, Database Administration, Database Application, Databases, Econometrics, Exploratory Data Analysis, Extract, Transform, Load, General Statistics, Geovisualization, Leadership and Management, Linear Regression, Machine Learning, Mathematical Theory & Analysis, Mathematics, Microsoft Excel, NoSQL, Operating Systems, Plot (Graphics), Probability & Statistics, Professional Development, Python Programming, Regression, Regression Analysis, SQL, Spreadsheet Software, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Statistical Visualization, System Programming, Theoretical Computer Science

      4.6

      (50.6k reviews)

      Beginner · Professional Certificate

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      IBM

      IBM

      Data Science Fundamentals with Python and SQL

      Skills you'll gain: Analysis, Basic Descriptive Statistics, Business Analysis, Computational Logic, Computer Programming, Data Analysis, Data Management, Data Visualization, Database Administration, Database Application, Databases, Extract, Transform, Load, General Statistics, Machine Learning, Mathematical Theory & Analysis, Mathematics, Plot (Graphics), Probability & Statistics, Probability Distribution, Python Programming, R Programming, Regression, SPSS, SQL, Statistical Analysis, Statistical Programming, Statistical Tests, Statistical Visualization, Theoretical Computer Science

      4.5

      (46.5k reviews)

      Beginner · Specialization

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      IBM

      IBM

      IBM Data Analytics with Excel and R

      Skills you'll gain: Advertising, Analysis, Apache, Big Data, Business Analysis, Communication, Computational Logic, Computer Programming, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Structures, Data Visualization, Data Visualization Software, Data Warehousing, Databases, Extract, Transform, Load, General Statistics, Leadership and Management, Marketing, Microsoft Excel, NoSQL, Operating Systems, Plot (Graphics), Probability & Statistics, Professional Development, Programming Principles, R Programming, Regression, SQL, Software, Spreadsheet Software, Statistical Analysis, Statistical Programming, Statistical Visualization, System Programming, Theoretical Computer Science

      4.7

      (9.8k reviews)

      Beginner · Professional Certificate

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      IBM

      IBM

      Applied Data Science

      Skills you'll gain: Algebra, Algorithms, Analysis, Business Analysis, Computational Logic, Computer Programming, Computer Programming Tools, Correlation And Dependence, Data Analysis, Data Management, Data Mining, Data Visualization, Databases, Econometrics, Exploratory Data Analysis, Extract, Transform, Load, General Statistics, Geovisualization, Interactive Data Visualization, Linear Regression, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Modeling, Plot (Graphics), Probability & Statistics, Python Programming, Regression, Regression Analysis, SQL, Spreadsheet Software, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Theoretical Computer Science

      4.6

      (38k reviews)

      Beginner · Specialization

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      Google

      Google

      Foundations: Data, Data, Everywhere

      Skills you'll gain: SQL, Decision Making, Data Visualization, Data Management, Analysis, Application Development, Design and Product, Data Analysis, Entrepreneurship, Software Engineering, Business Analysis, Leadership and Management, Spreadsheet Software, Data-Informed Decision-Making, Spreadsheet, Statistical Programming, Product Design, Databases, Analytics, Statistical Analysis

      4.8

      (46k reviews)

      Beginner · Course

    Searches related to statistical analysis

    statistical analysis with r for public health
    statistical analysis using python numpy
    inferential statistical analysis with python
    visualization for statistical analysis
    introduction to statistical analysis: hypothesis testing
    business statistics and analysis
    sas statistical business analyst
    business statistics and analysis capstone
    1234…84

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

    • Statistical Analysis with R for Public Health: Imperial College London
    • Inferential Statistical Analysis with Python: University of Michigan
    • Introduction to Statistical Analysis: Hypothesis Testing: SAS
    • Statistical Analysis using Python Numpy: Coursera Project Network
    • Visualization for Statistical Analysis: Coursera Project Network
    • Google Data Analytics: Google
    • IBM Data Science: IBM
    • IBM Data Analyst: IBM
    • Data Science Fundamentals with Python and SQL: IBM
    • IBM Data Analytics with Excel and R: IBM

    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 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.‎

    • 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.‎

    • 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.‎

    • 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.‎

    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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