What is statistical inference?

Statistical inference is the process whereby you can draw conclusions about a population based on random samples of that population and the statistics that you draw from those samples. When you rely on statistical inference, you take what you've observed about your samples of that population and apply them to the group as a whole. Applying statistical inference allows you to take what you know about the population as well as what's uncertain to make statements about the entire population based on your analysis.

Why is it important to learn about statistical inference?

If you want to learn about a certain population—whether they're customers or fellow employees—you can use statistical inference to draw conclusions about that population based on your analysis of data about them. You can't always survey or test an entire population to gain insight, but you can sample the population and make educated assumptions based on the data. Understanding statistical inference allows you to take that data and use it to draw conclusions that make sense and prove true.

How can I apply statistical inference in my career?

Statistical inference has plenty of benefits for different business sectors. Statisticians and data analysts use this method often to draw conclusions based on samples of populations. If you're in sales or product development, you can use statistical inference to determine which brands or products are popular with your customers or clients. Scientists use statistical inference to test hypotheses and draw conclusions when it's impossible for them to test or sample an entire population. You can apply statistical inference to analyze the data from surveys of any population that you sample.

How can online courses on Coursera help me learn about statistical inference?

Online courses on Coursera give you both a grasp of the concepts of statistical inference and practical applications. You'll learn from the best instructors in the academic world, and you can learn at a pace and schedule that best suits your schedule and lifestyle. When you finish our courses, you'll know how to use statistical inference in your career, which will give you an advantage whether you're trying to get better at your current job or whether you're looking to make a career change.

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Statistical Inference

필터링 기준

"statistical inference"에 대한 215개의 결과

University of California, Santa Cruz
Bayesian Statistics: Techniques and Models
획득할 기술: Statistical Analysis, Statistical Machine Learning, Data Analysis, Econometrics, General Statistics, Markov Model, Business Analysis, Probability Distribution, Statistical Programming, Bayesian Statistics, Bayesian, Graph Theory, R Programming, Mathematics, Probability & Statistics, Regression, Machine Learning
4.8
(442개의 검토)
Intermediate · Course · 1-3 Months
무료
Eindhoven University of Technology
Improving your statistical inferences
획득할 기술: Statistical Tests, Data Analysis, Business Analysis, Euler'S Totient Function, Analysis, Statistical Analysis, General Statistics, Hypothesis, Bayesian Statistics, Statistical Hypothesis Testing, Machine Learning, Statistical Inference, Bayesian, Bayesian Network, Experiment, Inference, Probability & Statistics, Hypothesis Testing
4.9
(725개의 검토)
Intermediate · Course · 1-3 Months
무료
Stanford University
Introduction to Statistics
획득할 기술: Statistical Tests, Statistical Analysis, Correlation And Dependence, Plot (Graphics), Econometrics, Data Analysis, Probability Distribution, Data Visualization, General Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Machine Learning, Probability & Statistics, Statistical Inference, Markov Model, Regression, Experiment, Basic Descriptive Statistics, Probability
4.5
(1.3k개의 검토)
Beginner · Course · 1-3 Months
University of Michigan
Inferential Statistical Analysis with Python
획득할 기술: Statistical Analysis, Python Programming, Data Analysis, Confidence, Statistical Tests, Analysis, Statistical Programming, Business Analysis, General Statistics, Hypothesis, Experiment, Inference, Hypothesis Testing, Statistical Inference, Computer Programming, Statistical Hypothesis Testing, Probability & Statistics
4.6
(798개의 검토)
Intermediate · Course · 1-4 Weeks
University of Illinois at Urbana-Champaign
Inferential and Predictive Statistics for Business
획득할 기술: Analysis, Statistical Analysis, Business Analysis, Econometrics, Data Analysis, General Statistics, Predictive Analytics, Statistical Inference, Hypothesis, Hypothesis Testing, Probability & Statistics, Statistical Hypothesis Testing, Regression, Inference, Experiment
4.8
(819개의 검토)
Mixed · Course · 1-3 Months

statistical inference과(와) 관련된 검색

statistical inference and hypothesis testing in data science applications

statistical inference for estimation in data science

improving your statistical inferences

data science foundations: statistical inference

inferential statistical analysis with python

inferential statistics

descriptive and inferential statistics in r

inferential and predictive statistics for business

요약하자면, 여기에 가장 인기 있는 statistical inference 강좌 10개가 있습니다.

Statistical Inference: Johns Hopkins University
Data Science Foundations: Statistical Inference: University of Colorado Boulder
Bayesian Statistics: Techniques and Models: University of California, Santa Cruz
Improving your statistical inferences: Eindhoven University of Technology
Introduction to Statistics: Stanford University
Statistical Inference and Hypothesis Testing in Data Science Applications: University of Colorado Boulder
Inferential Statistical Analysis with Python: University of Michigan
Inferential Statistics: University of Amsterdam
Statistical Inference for Estimation in Data Science: University of Colorado Boulder
Modern Regression Analysis in R: University of Colorado Boulder

Probability And Statistics에서 학습할 수 있는 스킬

Statistical Inference에 대한 자주 묻는 질문

Statistical inference is the process whereby you can draw conclusions about a population based on random samples of that population and the statistics that you draw from those samples. When you rely on statistical inference, you take what you've observed about your samples of that population and apply them to the group as a whole. Applying statistical inference allows you to take what you know about the population as well as what's uncertain to make statements about the entire population based on your analysis.‎
If you want to learn about a certain population—whether they're customers or fellow employees—you can use statistical inference to draw conclusions about that population based on your analysis of data about them. You can't always survey or test an entire population to gain insight, but you can sample the population and make educated assumptions based on the data. Understanding statistical inference allows you to take that data and use it to draw conclusions that make sense and prove true.‎
Statistical inference has plenty of benefits for different business sectors. Statisticians and data analysts use this method often to draw conclusions based on samples of populations. If you're in sales or product development, you can use statistical inference to determine which brands or products are popular with your customers or clients. Scientists use statistical inference to test hypotheses and draw conclusions when it's impossible for them to test or sample an entire population. You can apply statistical inference to analyze the data from surveys of any population that you sample.‎
Online courses on Coursera give you both a grasp of the concepts of statistical inference and practical applications. You'll learn from the best instructors in the academic world, and you can learn at a pace and schedule that best suits your schedule and lifestyle. When you finish our courses, you'll know how to use statistical inference in your career, which will give you an advantage whether you're trying to get better at your current job or whether you're looking to make a career change.‎