What skills or experience do I need to already have, before starting to learn econometrics?

Before starting to learn econometrics, you typically need to already have an understanding of advanced mathematics and the different statistical methods used in economic models. Probability theory is another topic you typically need to understand before proceeding into econometrics. It can help to have experience with research techniques like data collection. R programming language, linear regression, regression analysis, and time series are three other topics that can typically support your econometrics studies. Additionally, you could benefit from studying causal inference, machine learning, social sciences, or qualitative modeling in coordination with your econometrics studies to support your learning efforts.

What kind of people are best suited for roles in econometrics?

People who have a highly analytical nature and who also have the patience to solve complex problems are typically the best suited to roles in econometrics. It can also be important to be a person who enjoys advanced mathematics, such as statistics and calculus when pursuing an econometrics role. People who work in fields like finance, computer science, auditing, or teaching courses like economics can also be well suited to econometrics roles that complement existing jobs in those fields.

What are common career paths for someone in econometrics?

Consumer scientists and computer programmers are two common career paths for people in econometrics because computer technology helps with processing large amounts of data. Another common career path for people in econometrics is in the educational field as an economics professor teaching others about this field. Auditors, such as IRS agents, and government jobs in regulatory affairs are also potential career paths for those who learn econometrics. Businesses may also hire compliance specialists and those with knowledge of regulatory affairs who are strong in the area of econometrics.

What topics can I study that are related to econometrics?

Data science, including statistics, linear regression and modeling, and machine learning like AI is a broad topic you can study that is related to and encompasses econometrics. Finance, quantitative modeling, and R programming language are some more numbers-based topics that are related to econometrics. Those interested in econometrics may also enjoy the econometrics-related topics of causal inference, social science, regression analysis, and regression modeling. Additionally, cliometrics, which uses numbers pulled from historic documents like parish registries and population census records to interpret economic history is another topic that is closely related to econometrics.

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Econometrics

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''econometrics'的 170 個結果

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Stanford University
Introduction to Statistics
您將獲得的技能： Data Science, General Statistics, Probability & Statistics, Statistical Tests, Estimation, Basic Descriptive Statistics, Correlation And Dependence, Probability Distribution, Regression, Bayesian Statistics, Data Analysis, Data Visualization, Econometrics, Experiment, Machine Learning, Markov Model, Plot (Graphics), Statistical Analysis, Statistical Visualization
4.5
（1.9k 條評論）
Beginner · Course · 1-3 Months
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The Hong Kong University of Science and Technology
Python and Statistics for Financial Analysis
您將獲得的技能： Business Analysis, Computer Programming, Data Analysis, Financial Analysis, Python Programming, Statistical Programming, Finance, Investment Management, Probability & Statistics, Probability Distribution, Statistical Analysis, Basic Descriptive Statistics, Correlation And Dependence, General Statistics, Regression, Risk Management, Securities Trading, Statistical Tests, Accounting, Estimation
4.4
（3.6k 條評論）
Intermediate · Course · 1-4 Weeks
University of Pennsylvania
A Crash Course in Causality: Inferring Causal Effects from Observational Data
您將獲得的技能： General Statistics, Probability & Statistics, Econometrics, Forecasting, Business Analysis, Data Analysis, Experiment, Statistical Analysis, R Programming, Statistical Programming, Entrepreneurship, Graph Theory, Machine Learning, Market Research, Marketing, Mathematics, Regression, Research and Design, Statistical Tests
4.7
（485 條評論）
Intermediate · Course · 1-3 Months
DeepLearning.AI，Stanford University
Machine Learning
您將獲得的技能： Machine Learning, Probability & Statistics, Machine Learning Algorithms, General Statistics, Theoretical Computer Science, Algorithms, Applied Machine Learning, Artificial Neural Networks, Regression, Econometrics, Computer Programming, Deep Learning, Python Programming, Statistical Programming, Mathematics, Tensorflow, Data Management, Data Structures, Statistical Machine Learning, Reinforcement Learning, Probability Distribution, Mathematical Theory & Analysis, Data Analysis, Data Mining, Linear Algebra, Computer Vision, Calculus, Feature Engineering, Bayesian Statistics, Operations Research, Research and Design, Strategy and Operations, Computational Logic, Accounting, Communication
4.9
（7.9k 條評論）
Beginner · Specialization · 1-3 Months
University of Michigan
Statistics with Python
您將獲得的技能： Probability & Statistics, General Statistics, Statistical Programming, Python Programming, Data Science, Business Analysis, Regression, Computer Programming, Data Analysis, Statistical Analysis, Statistical Tests, Experiment, Econometrics, Machine Learning, Machine Learning Algorithms, Data Visualization, Statistical Visualization, Bayesian Statistics, Correlation And Dependence, Data Analysis Software, Estimation, Basic Descriptive Statistics, Mathematics, Plot (Graphics), Programming Principles
4.6
（3k 條評論）
Beginner · Specialization · 1-3 Months
University of Illinois at Urbana-Champaign
Managerial Economics and Business Analysis
您將獲得的技能： Market Analysis, Marketing, Entrepreneurship, Business Analysis, Data Analysis, Research and Design, Basic Descriptive Statistics, Finance, Financial Management, Market Research, Probability & Statistics, Statistical Analysis, Business Development, Exploratory Data Analysis, Leadership and Management, Sales, Spreadsheet Software, Strategy, Strategy and Operations, Statistical Tests, Regression, Accounting, Data Visualization, Financial Analysis, Investment Management, Plot (Graphics), Survey Creation, Big Data, Change Management, Data Management, Decision Making, Econometrics, Experiment, Game Theory, General Accounting, General Statistics, Mathematics, Planning, Project Management, Supply Chain Systems, Supply Chain and Logistics
4.7
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Beginner · Specialization · 3-6 Months

與 econometrics 相關的搜索

econometrics: methods and applications

econometrics for economists and finance practitioners

enjoyable econometrics

the econometrics of time series data

hypotheses testing in econometrics

topics in applied econometrics

econometria básica aplicada

總之，這是我們最受歡迎的 econometrics 門課程中的 10 門

Econometrics: Methods and Applications: Erasmus University Rotterdam
Econometrics for Economists and Finance Practitioners: Queen Mary University of London
Enjoyable Econometrics: Erasmus University Rotterdam
Introduction to Statistics: Stanford University
Python and Statistics for Financial Analysis: The Hong Kong University of Science and Technology
A Crash Course in Causality: Inferring Causal Effects from Observational Data: University of Pennsylvania
Machine Learning: DeepLearning.AI
Statistics with Python: University of Michigan
Managerial Economics and Business Analysis: University of Illinois at Urbana-Champaign
Linear Regression and Modeling: Duke University

您可以在 Probability And Statistics 中學到的技能

關於計量經濟學的常見問題

Before starting to learn econometrics, you typically need to already have an understanding of advanced mathematics and the different statistical methods used in economic models. Probability theory is another topic you typically need to understand before proceeding into econometrics. It can help to have experience with research techniques like data collection. R programming language, linear regression, regression analysis, and time series are three other topics that can typically support your econometrics studies. Additionally, you could benefit from studying causal inference, machine learning, social sciences, or qualitative modeling in coordination with your econometrics studies to support your learning efforts.‎
People who have a highly analytical nature and who also have the patience to solve complex problems are typically the best suited to roles in econometrics. It can also be important to be a person who enjoys advanced mathematics, such as statistics and calculus when pursuing an econometrics role. People who work in fields like finance, computer science, auditing, or teaching courses like economics can also be well suited to econometrics roles that complement existing jobs in those fields.‎
Consumer scientists and computer programmers are two common career paths for people in econometrics because computer technology helps with processing large amounts of data. Another common career path for people in econometrics is in the educational field as an economics professor teaching others about this field. Auditors, such as IRS agents, and government jobs in regulatory affairs are also potential career paths for those who learn econometrics. Businesses may also hire compliance specialists and those with knowledge of regulatory affairs who are strong in the area of econometrics.‎
Data science, including statistics, linear regression and modeling, and machine learning like AI is a broad topic you can study that is related to and encompasses econometrics. Finance, quantitative modeling, and R programming language are some more numbers-based topics that are related to econometrics. Those interested in econometrics may also enjoy the econometrics-related topics of causal inference, social science, regression analysis, and regression modeling. Additionally, cliometrics, which uses numbers pulled from historic documents like parish registries and population census records to interpret economic history is another topic that is closely related to econometrics.‎