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    • Statistics

    필터링 기준

    "statistics"에 대한 2866개의 결과

    • 무료

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      The Hong Kong University of Science and Technology

      Python and Statistics for Financial Analysis

      획득할 기술: 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

      (3.6k개의 검토)

      Intermediate · Course · 1-4 Weeks

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      University of Virginia

      Marketing Analytics

      획득할 기술: Marketing, Business Analysis, Market Analysis, Brand Management, Communication, Customer Analysis, Market Research, Marketing Management, Research and Design, Benefits, Change Management, Compensation, Conflict Management, Correlation And Dependence, Customer Relationship Management, Digital Marketing, FinTech, Finance, Financial Management, HR Tech, Human Resources Operations, Investment Management, Leadership Development, Marketing Design, Mergers & Acquisitions, Payments, Probability & Statistics, Professional Development, Recruitment, Regression, Regulations and Compliance, Risk Management, Securities Sales, Securities Trading, Statistical Analysis, Talent Management, Underwriting, Entrepreneurship, Experiment, General Statistics, Leadership and Management, Sales, Strategy, Strategy and Operations

      4.7

      (6.2k개의 검토)

      Beginner · Course · 1-3 Months

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      Coursera Project Network

      Power BI الحصول على البيانات وشكلها ودمجها باستخدام

      획득할 기술: Advertising, Business Intelligence, Communication, Data Analysis, Data Engineering, Finance, Journalism, Marketing, Mergers & Acquisitions

      Beginner · Guided Project · Less Than 2 Hours

    • 무료

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      Universitat de Barcelona

      Prehospital care of acute stroke and patient selection for endovascular treatment using the RACE scale

      획득할 기술: Epidemiology, Probability & Statistics, Planning, Sales, Strategy and Operations, Supply Chain and Logistics

      4.8

      (95개의 검토)

      Intermediate · Course · 1-4 Weeks

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      Coursera Project Network

      R أساسيات لغة البرمجة

      획득할 기술: Computer Programming, Statistical Programming, Data Analysis, Data Science, R Programming

      Beginner · Guided Project · Less Than 2 Hours

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      SAS

      Statistical Thinking for Industrial Problem Solving, presented by JMP

      획득할 기술: Business Analysis, Correlation And Dependence, Data Analysis, Exploratory Data Analysis, Probability & Statistics, Statistical Analysis, Process Analysis, Statistical Tests, Advertising, Communication, Entrepreneurship, Marketing, Regression

      4.8

      (66개의 검토)

      Beginner · Course · 1-3 Months

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      Coursera Project Network

      الترجيح الإحصائي أو Statistical Weighting فى Microsoft Excel

      획득할 기술: Accounting

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      How To Create Effective Metrics

      획득할 기술: Business Analysis, Business Intelligence, Data Analysis, Strategy

      4.2

      (6개의 검토)

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Intro to Time Series Analysis in R

      획득할 기술: Data Analysis, Forecasting, General Statistics, Probability & Statistics, R Programming, Statistical Programming

      4.4

      (239개의 검토)

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Predict Sales and Forecast Trends in Google Sheets

      획득할 기술: Basic Descriptive Statistics, Data Analysis, Forecasting, Probability & Statistics, Business Intelligence, Feature Engineering

      4.4

      (27개의 검토)

      Beginner · Guided Project · Less Than 2 Hours

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      Johns Hopkins University

      Algebra: Elementary to Advanced - Equations & Inequalities

      획득할 기술: Algebra, Mathematics, Linear Algebra

      4.8

      (313개의 검토)

      Beginner · Course · 1-3 Months

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      무료

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      École Polytechnique Fédérale de Lausanne

      Interest Rate Models

      획득할 기술: Finance, Investment Management, Calculus, Mathematics, Accounting, Business Analysis, Data Analysis, Financial Analysis, General Statistics, Probability & Statistics

      4.5

      (178개의 검토)

      Advanced · Course · 1-3 Months

    statistics과(와) 관련된 검색

    statistics for data science
    statistics with r
    statistics with python
    statistics for data science with python
    statistics with sas
    statistics for genomic data science
    statistics for international business
    statistics for marketing
    1…456…84

    요약하자면, 여기에 가장 인기 있는 statistics 강좌 10개가 있습니다.

    • Python and Statistics for Financial Analysis: The Hong Kong University of Science and Technology
    • Marketing Analytics: University of Virginia
    • Power BI الحصول على البيانات وشكلها ودمجها باستخدام: Coursera Project Network
    • Prehospital care of acute stroke and patient selection for endovascular treatment using the RACE scale: Universitat de Barcelona
    • R أساسيات لغة البرمجة: Coursera Project Network
    • Statistical Thinking for Industrial Problem Solving, presented by JMP: SAS
    • الترجيح الإحصائي أو Statistical Weighting فى Microsoft Excel: Coursera Project Network
    • How To Create Effective Metrics: Coursera Project Network
    • Intro to Time Series Analysis in R: Coursera Project Network
    • Predict Sales and Forecast Trends in Google Sheets: Coursera Project Network

    통계에 대한 자주 묻는 질문

    • Statistics is the science of organizing, analyzing, and interpreting large numerical datasets, with a variety of goals. Descriptive statistics such as mean, median, mode and standard deviation summarize the characteristics of a dataset; statistical inference seeks to determine the characteristics of a large population from a representative sample through statistical hypothesis testing; and statistical regression techniques establish the correlations between an dependent variable and one or more independent variables.

      A familiarity with statistics is critically important for describing and understanding our world. From stock market volatility to political polling to the three-point percentage of your favorite basketball player, statistics help to make the complexity of the world comprehensible - and tell us what to expect. The era of big data has made the use of statistics even more necessary, and data science software like Python and R programming have made data analysis techniques more powerful and more accessible than ever.‎

    • Just as statistics have become more important for making sense of our world, an ability to understand and use statistics has become increasingly essential for a variety of careers. Whether you are working in business, government, or academia, it is increasingly expected that assertions and decisions are backed up by data. Thus, you’ll need a familiarity with statistics whether you’re an operations manager preparing a presentation on process improvements for a CEO or a policy analyst writing a research paper on criminal justice reform for a legislator.

      If you have a passion for building Markov chain models or debating the relative merits of frequentist and Bayesian statistics, you can pursue a career as a full-time statistician. According to the Bureau of Labor Statistics, statisticians earned a median annual salary of $91,160 as of May 2019, and these jobs are expected to grow much faster than average due to the demand for keen statistical analysis across all fields. Statisticians typically have at least a bachelor’s degree in mathematics, computer science, or other quantitative fields, and many positions require a master’s degree in statistics.‎

    • Yes, with absolute certainty. Coursera offers individual courses as well as Specializations in statistics, as well as courses focused on related topics such as programming in Python and R as well as the applied use of business statistics. These courses and Specializations are offered by top-ranked universities such as the University of Michigan, Duke University, and Johns Hopkins University, ensuring that you won’t sacrifice educational rigor to learn online. You can also learn about statistics through Coursera’s hands-on Guided Projects, which allow you to build skills with step-by-step tutorials from experienced instructors to help you learn with confidence.‎

    • Before starting to learn statistics, you should already have basic math skills and be able to do simple calculations. You also could take math courses in algebra or calculus to prepare for learning statistics, but many people are able to successfully complete basic statistics courses without experience using advanced math. Other skills that may be useful include analytical, problem-solving, and inferential skills. Experience working with computer programming languages can be helpful if you want to take a course to learn how to use a specific language like Python to analyze data sets.‎

    • The kind of people best suited for roles in statistics enjoy working with data and sharing their findings with others. They tend to be analytical thinkers who look for trends and patterns in the data they collect and spend time asking and answering the questions the data prompts. They're able to work with a variety of people, including team members who help them collect and analyze data and the business executives and researchers relying on the information derived from the data. People who have roles in statistics may also have strong communication and presentation skills.‎

    • If you are an analytical thinker who likes collecting, analyzing, and interpreting data, learning statistics may be right for you. Learning statistics can be a logical choice if you like to make predictions or solve problems. You may be able to use the information you learn in a statistics course as preparation for additional studies in fields like mathematics, data science, or marketing. Learning statistics may be for you if you want to work in a field where you’ll use data regularly, such as business administration, marketing, public policy, finance, or insurance. Feeling comfortable organizing information, analyzing data, and viewing it from multiple perspectives can give you an edge over your competition.‎

    이 FAQ 콘텐츠는 정보 전달 목적만으로 사용할 수 있습니다. 학습자는 과정 및 기타 학점 정보가 개인적, 직업적 및 재정적 목표에 부합하는지 확인하기 위해 추가 조사를 수행하는 것이 좋습니다.
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