What is 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.

Why is statistical analysis important?

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.

What are typical careers that use statistical analysis?

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.

How can online courses on Coursera help me learn statistical analysis?

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.

Parcourir
Statistical Analysis

Filtrer par

1810 résultats pour ''statistical analysis'

Imperial College London
Statistical Analysis with R for Public Health
Compétences que vous acquerrez : Probability & Statistics, General Statistics, Regression, Business Analysis, Statistical Analysis, Machine Learning, Machine Learning Algorithms, Data Analysis, Statistical Programming, Mathematics, Statistical Tests, R Programming, Probability Distribution, Basic Descriptive Statistics, Correlation And Dependence, Econometrics, Estimation, Bayesian Statistics, Exploratory Data Analysis, Critical Thinking, Data Analysis Software, Forecasting
4.7
(1.7k avis)
Beginner · Specialization · 3-6 Months
University of Michigan
Inferential Statistical Analysis with Python
Compétences que vous acquerrez : Probability & Statistics, Business Analysis, Computer Programming, General Statistics, Statistical Programming, Python Programming, Statistical Tests, Data Analysis, Experiment, Statistical Analysis, Basic Descriptive Statistics, Data Analysis Software, Mathematics
4.6
(827 avis)
Intermediate · Course · 1-4 Weeks
SAS
Introduction to Statistical Analysis: Hypothesis Testing
Compétences que vous acquerrez : Business Analysis, Data Analysis, General Statistics, Probability & Statistics, SAS (Software), Statistical Analysis, Statistical Programming, Statistical Tests, Regression, Correlation And Dependence, Advertising, Algebra, Communication, Journalism, Marketing
4.6
(79 avis)
Intermediate · Course · 1-4 Weeks
Google
Google Data Analytics
Compétences que vous acquerrez : Data Analysis, Statistical Programming, Data Science, Business Analysis, SQL, Spreadsheet Software, Data Visualization, Business, Data Management, Data Visualization Software, R Programming, Leadership and Management, Exploratory Data Analysis, Statistical Visualization, Change Management, Strategy and Operations, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Tableau Software, Big Data, Cloud Computing, Critical Thinking, Customer Analysis, General Statistics, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget Management, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Mining, Data Model, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, Full-Stack Web Development, Interactive Data Visualization, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Problem Solving, Product Design, Programming Principles, Project Management, Research and Design, Security Engineering, Security Strategy, Software Engineering, Software Security, Storytelling, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development
4.8
(93.7k avis)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Science
Compétences que vous acquerrez : Python Programming, Data Science, Data Analysis, Data Structures, Statistical Programming, Machine Learning, Data Mining, Regression, Machine Learning Algorithms, Data Visualization, General Statistics, Basic Descriptive Statistics, SQL, Applied Machine Learning, Statistical Analysis, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Databases, Programming Principles, Exploratory Data Analysis, Algebra, Data Management, Database Theory, Data Visualization Software, R Programming, Statistical Machine Learning, Statistical Tests, Deep Learning, Probability & Statistics, Statistical Visualization, Database Application, Extract, Transform, Load, Devops Tools, SPSS, Estimation, Interactive Data Visualization, Algorithms, Computer Programming, Database Administration, Geovisualization, Plot (Graphics), Reinforcement Learning, Theoretical Computer Science, Big Data, Business Analysis, Computational Logic, Correlation And Dependence, Econometrics, Entrepreneurship, Marketing, Mathematical Theory & Analysis, Mathematics, Spreadsheet Software, Storytelling, Supply Chain Systems, Supply Chain and Logistics, Writing
4.6
(103.7k avis)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Analyst
Compétences que vous acquerrez : Data Analysis, Python Programming, Data Visualization, Exploratory Data Analysis, Business Analysis, Basic Descriptive Statistics, Data Structures, Data Science, Statistical Programming, Microsoft Excel, Spreadsheet Software, Data Management, General Statistics, Plot (Graphics), SQL, Statistical Visualization, Databases, Data Mining, Statistical Analysis, Programming Principles, Probability & Statistics, Regression, Machine Learning, Algebra, Data Analysis Software, Data Visualization Software, Database Theory, Probability Distribution, Applied Machine Learning, Statistical Tests, Big Data, Correlation And Dependence, Database Application, Estimation, NoSQL, Geovisualization, ArcGIS, Cloud Computing, Computer Programming, Data Warehousing, Database Administration, Extract, Transform, Load, HTML and CSS, Knitr, Mathematics, Minitab, PostgreSQL, R Programming, SAS (Software), SPSS, Apache, Computational Logic, Computer Programming Tools, Econometrics, Leadership and Management, Mathematical Theory & Analysis, Operating Systems, Professional Development, Statistical Machine Learning, System Programming, Theoretical Computer Science
4.6
(58.8k avis)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
Data Science Fundamentals with Python and SQL
Compétences que vous acquerrez : Data Structures, Python Programming, Data Analysis, SQL, Statistical Programming, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Databases, General Statistics, Probability & Statistics, Programming Principles, Algebra, Database Theory, Data Visualization Software, R Programming, Statistical Tests, Data Management, Data Science, Basic Descriptive Statistics, Business Analysis, Probability Distribution, Statistical Analysis, Database Application, Devops Tools, Machine Learning Algorithms, SPSS, Correlation And Dependence, Data Visualization, Exploratory Data Analysis, Plot (Graphics), Regression, Statistical Visualization, Computer Programming, Database Administration, Extract, Transform, Load, Computational Logic, Machine Learning, Mathematical Theory & Analysis, Mathematics, Theoretical Computer Science
4.5
(51.5k avis)
Beginner · Specialization · 3-6 Months
IBM Skills Network
IBM Data Engineering
Compétences que vous acquerrez : Data Management, Databases, SQL, Data Architecture, Big Data, Data Structures, Database Administration, Database Theory, Statistical Programming, Apache, Extract, Transform, Load, Python Programming, Data Warehousing, Database Application, Data Model, Data Analysis, NoSQL, Data Engineering, Distributed Computing Architecture, Computer Architecture, Database Design, Operating Systems, System Programming, System Software, Programming Principles, PostgreSQL, Algebra, Business Analysis, Computer Programming, Machine Learning, Applied Machine Learning, Correlation And Dependence, Feature Engineering, General Statistics, Graph Theory, Machine Learning Algorithms, Machine Learning Software, Regression, Statistical Analysis, Statistical Machine Learning, Data Visualization, Data Visualization Software, Cloud Computing, DevOps, Leadership and Management, Cloud Engineering, Interactive Data Visualization, Basic Descriptive Statistics, Exploratory Data Analysis, Cloud Applications, Data Science, Hardware Design, Kubernetes, Network Architecture, Network Security, Other Programming Languages, Professional Development, Security Engineering, Algorithms, Computational Logic, Computational Thinking, Computer Networking, Computer Programming Tools, IBM Cloud, Linux, Mathematical Theory & Analysis, Mathematics, Microarchitecture, Project Management, Security Strategy, Software Architecture, Software Engineering, Strategy and Operations, Theoretical Computer Science
4.6
(39.4k avis)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
Applied Data Science
Compétences que vous acquerrez : Python Programming, Data Analysis, Data Science, Data Structures, Data Visualization, Statistical Programming, Basic Descriptive Statistics, Programming Principles, Exploratory Data Analysis, Algebra, Machine Learning, Applied Machine Learning, Data Mining, General Statistics, Regression, Statistical Analysis, Statistical Tests, Statistical Visualization, Data Management, Extract, Transform, Load, Interactive Data Visualization, Machine Learning Algorithms, SQL, Computer Programming, Geovisualization, Plot (Graphics), Algorithms, Business Analysis, Computational Logic, Computer Programming Tools, Correlation And Dependence, Data Analysis Software, Databases, Econometrics, Mathematical Theory & Analysis, Mathematics, Probability & Statistics, Spreadsheet Software, Statistical Machine Learning, Theoretical Computer Science
4.6
(42.2k avis)
Beginner · Specialization · 3-6 Months
IBM Skills Network
IBM Data Analytics with Excel and R
Compétences que vous acquerrez : Data Analysis, R Programming, Data Visualization, Plot (Graphics), Data Management, Business Analysis, Exploratory Data Analysis, Data Mining, Data Visualization Software, SQL, Basic Descriptive Statistics, Statistical Visualization, General Statistics, Databases, Data Analysis Software, Interactive Data Visualization, Microsoft Excel, Spreadsheet Software, Statistical Programming, Big Data, Statistical Analysis, Probability & Statistics, Database Theory, Regression, Statistical Tests, Data Science, Data Structures, Software Visualization, Machine Learning, User Experience, Probability Distribution, NoSQL, Python Programming, Applied Machine Learning, Deep Learning, Estimation, Geovisualization, Linear Algebra, Machine Learning Algorithms, Machine Learning Software, SAS (Software), Spatial Data Analysis, Statistical Machine Learning, Cloud Computing, Data Architecture, Data Model, Data Warehousing, Database Administration, Database Application, Database Design, Mathematics, Visualization (Computer Graphics), Advertising, Apache, Communication, Computational Logic, Computer Programming, Extract, Transform, Load, Leadership and Management, Marketing, Operating Systems, Professional Development, Programming Principles, System Programming, Theoretical Computer Science
4.7
(13.8k avis)
Beginner · Professional Certificate · 3-6 Months

Recherches liées à statistical analysis

statistical analysis with r for public health

statistical analysis using python numpy

inferential statistical analysis with python

introduction to statistical analysis: hypothesis testing

visualization for statistical analysis

sas statistical business analyst

business statistics and analysis

business statistics and analysis capstone

En résumé, voici 10 de nos cours statistical analysis les plus populaires

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
Visualization for Statistical Analysis: Coursera Project Network
Statistical Analysis using Python Numpy: Coursera Project Network
Google Data Analytics: Google
IBM Data Science: IBM Skills Network
IBM Data Analyst: IBM Skills Network
Data Science Fundamentals with Python and SQL: IBM Skills Network
IBM Data Engineering: IBM Skills Network

Compétences que vous avez acquises en Business Essentials

Analytique (37)

Présentation (33)

Modélisation (29)

Business Analytics (27)

Communication Commerciale (16)

Prise De Décision (16)

Direction (15)

Questions fréquentes sur Analyse statistique

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.‎

Le contenu de cette FAQ a été mis à disposition à des fins d'information uniquement. Il est conseillé aux étudiants d'effectuer des recherches supplémentaires afin de s'assurer que les cours et autres qualifications suivis correspondent à leurs objectifs personnels, professionnels et financiers.