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  • Statistics

Results for "statistics"


  • G

    Google

    The Power of Statistics

    Skills you'll gain: A/B Testing, Sampling (Statistics), Data Analysis, Analytics, Statistics, Descriptive Statistics, Statistical Analysis, Statistical Hypothesis Testing, Probability & Statistics, Advanced Analytics, Probability Distribution, Data Science, Statistical Inference, Statistical Programming, Statistical Methods, Probability, Python Programming

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    4.8
    Rating, 4.8 out of 5 stars
    ·
    902 reviews

    Advanced · Course · 1 - 3 Months

  • J

    Johns Hopkins University

    Advanced Statistics for Data Science

    Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, Probability Distribution, R Programming, Biostatistics, Data Analysis, Data Science, Statistics, Mathematical Modeling, Analysis, Data Modeling

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    4.4
    Rating, 4.4 out of 5 stars
    ·
    800 reviews

    Advanced · Specialization · 3 - 6 Months

  • G

    Google

    Google Advanced Data Analytics

    Skills you'll gain: Interactive Data Visualization, Statistics, Descriptive Statistics, Logistic Regression, Decision Tree Learning, Advanced Analytics, Probability & Statistics, Probability Distribution, Statistical Inference, Applied Machine Learning, Data-Driven Decision-Making, Supervised Learning, Workflow Management, Statistical Methods, Statistical Modeling, Data Cleansing, Data Structures, Interviewing Skills, NumPy, Professional Development

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    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    12K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • E

    ESSEC Business School

    Strategic Business Analytics

    Skills you'll gain: Data-Driven Marketing, Marketing Analytics, Business Analytics, Statistical Programming, Forecasting, Peer Review, Statistical Methods, Data Presentation, Predictive Analytics, Customer Analysis, Case Studies, R (Software), Information Technology, Analytical Skills, Digital Transformation, Business Marketing, Advanced Analytics, Complex Problem Solving, Data Synthesis, R Programming

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    4.4
    Rating, 4.4 out of 5 stars
    ·
    1.3K reviews

    Advanced · Specialization · 3 - 6 Months

  • C

    Corporate Finance Institute

    Practical Data Science for Data Analysts

    Skills you'll gain: Classification Algorithms, Data Preprocessing, Feature Engineering, Data Visualization, Model Evaluation, Data Import/Export, Matplotlib, Exploratory Data Analysis, Data Presentation, Data Science, Plot (Graphics), Regression Analysis, Financial Data, Data Analysis, Business Analytics, Data Cleansing, Machine Learning Algorithms, Correlation Analysis, Advanced Analytics, Predictive Analytics

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    4.8
    Rating, 4.8 out of 5 stars
    ·
    31 reviews

    Advanced · Specialization · 3 - 6 Months

  • C

    Corporate Finance Institute

    Advanced Tableau

    Skills you'll gain: Star Schema, Data Presentation, Data Modeling, Tableau Software, Interactive Data Visualization, Business Intelligence, Extract, Transform, Load, Dashboard, Business Intelligence Software, Dashboard Creation, Performance Tuning, Technical Analysis, Model Optimization, Database Design, Data Visualization Software, Plot (Graphics), Market Data, Statistical Visualization, Data Visualization, Trend Analysis

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    4.7
    Rating, 4.7 out of 5 stars
    ·
    35 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: New
    New
    C

    Coursera

    Forecast Financials with Monte Carlo Mastery

    Skills you'll gain: Financial Forecasting, Financial Modeling, Risk Analysis, Risk Modeling, Forecasting, Financial Data, Cash Flow Forecasting, Simulation and Simulation Software, Microsoft Excel, Financial Analysis, Trend Analysis, Probability Distribution, Risk Management, Time Series Analysis and Forecasting, Data Analysis

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    Advanced · Course · 1 - 4 Weeks

  • C

    Corporate Finance Institute

    Python Fundamentals

    Skills you'll gain: Data Visualization, Matplotlib, Data Presentation, Plot (Graphics), Financial Data, Exploratory Data Analysis, Data Storytelling, Statistical Methods, Pandas (Python Package), Financial Analysis, Data Visualization Software, Statistical Analysis, Data Manipulation, NumPy, Seaborn, Data Analysis, Case Studies, Data Wrangling, Data Science, Data Transformation

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    Included with Coursera Plus

    4.9
    Rating, 4.9 out of 5 stars
    ·
    13 reviews

    Advanced · Course · 1 - 3 Months

  • M

    Macquarie University

    Statistics and Data Analysis with Excel: Advanced

    Skills you'll gain: Data-Driven Decision-Making, Microsoft Excel, Forecasting, Regression Analysis, Data Literacy, Excel Formulas, Statistical Analysis, Data Analysis Software, Time Series Analysis and Forecasting, Spreadsheet Software, Analytics, Data Visualization, Statistical Methods, Advanced Analytics, Data Analysis, Statistics, Analysis, Statistical Hypothesis Testing, Probability & Statistics, Statistical Inference

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    4.6
    Rating, 4.6 out of 5 stars
    ·
    41 reviews

    Advanced · Course · 1 - 3 Months

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  • S

    Stanford University

    Probabilistic Graphical Models 1: Representation

    Skills you'll gain: Bayesian Network, Decision Intelligence, Bayesian Statistics, Graph Theory, Probability Distribution, Network Model, Statistical Modeling, Markov Model, Probability & Statistics, Network Analysis, Dependency Analysis

    Coursera Plus

    Included with Coursera Plus

    4.6
    Rating, 4.6 out of 5 stars
    ·
    1.4K reviews

    Advanced · Course · 1 - 3 Months

  • Status: New
    New
    C

    Coursera

    Automate, Optimize, and Benchmark Data Pipelines

    Skills you'll gain: Performance Analysis, Performance Testing, Performance Measurement, Benchmarking, Data Modeling, Analysis, Data Processing, Extract, Transform, Load, Statistical Analysis

    Coursera Plus

    Included with Coursera Plus

    Advanced · Course · 1 - 4 Weeks

  • C

    Columbia University

    Causal Inference

    Skills you'll gain: Statistical Inference, Regression Analysis, Applied Machine Learning, Statistical Methods, Statistical Machine Learning, Statistical Analysis, Statistical Hypothesis Testing, Statistical Modeling, Machine Learning, Experimentation, Data Collection, Probability & Statistics, Research Design

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    Included with Coursera Plus

    3.3
    Rating, 3.3 out of 5 stars
    ·
    107 reviews

    Advanced · Course · 1 - 3 Months

1234…6

In summary, here are 10 of our most popular statistics courses

  • The Power of Statistics: Google
  • Advanced Statistics for Data Science: Johns Hopkins University
  • Google Advanced Data Analytics: Google
  • Strategic Business Analytics: ESSEC Business School
  • Practical Data Science for Data Analysts: Corporate Finance Institute
  • Advanced Tableau: Corporate Finance Institute
  • Forecast Financials with Monte Carlo Mastery: Coursera
  • Python Fundamentals: Corporate Finance Institute
  • Statistics and Data Analysis with Excel: Advanced: Macquarie University
  • Probabilistic Graphical Models 1: Representation: Stanford University

Frequently Asked Questions about Statistics

Statistics is the branch of mathematics that deals with collecting, analyzing, interpreting, presenting, and organizing data. It is crucial because it provides the tools and methodologies to make informed decisions based on data. In an increasingly data-driven world, understanding statistics allows individuals and organizations to identify trends, make predictions, and validate hypotheses. Whether in business, healthcare, social sciences, or technology, statistics plays a vital role in guiding strategies and improving outcomes.‎

A background in statistics can open doors to various career opportunities. Jobs in this field include data analyst, statistician, biostatistician, market researcher, and quantitative analyst. These roles often require the ability to interpret complex data sets and communicate findings effectively. Additionally, industries such as finance, healthcare, and technology are increasingly seeking professionals skilled in statistics to help drive decision-making processes and improve operational efficiency.‎

To pursue a career in statistics, you should develop a range of skills. Key competencies include proficiency in statistical software (like R or Python), a solid understanding of probability theory, data visualization techniques, and the ability to interpret and communicate statistical results. Additionally, critical thinking and problem-solving skills are essential, as they enable you to approach data analysis with a strategic mindset. Familiarity with data collection methods and experimental design is also beneficial.‎

There are many excellent online statistics courses available that cater to different levels of expertise. For beginners, the Foundations of Probability and Statistics Specialization offers a solid introduction. For those looking to apply statistics in data science, the Data Science: Statistics and Machine Learning Specialization is highly recommended. Additionally, the Business Statistics and Analysis Specialization provides practical skills for applying statistics in a business context.‎

Yes. You can start learning statistics on Coursera for free in two ways:

  1. Preview the first module of many statistics courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in statistics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

Learning statistics can be approached through various methods. Start by identifying your learning style‚Äîwhether you prefer structured courses, hands-on projects, or self-study. Online platforms like Coursera provide a range of courses that cater to different preferences. Engage with practical exercises to apply what you learn, and consider joining study groups or forums to discuss concepts with peers. Regular practice and real-world application will reinforce your understanding and build confidence.‎

Typical topics covered in statistics courses include descriptive statistics, probability theory, inferential statistics, hypothesis testing, regression analysis, and data visualization. More advanced courses may explore Bayesian statistics, multivariate analysis, and statistical modeling. These topics provide a comprehensive foundation for understanding how to analyze and interpret data effectively, which is essential for making informed decisions in various fields.‎

For training and upskilling employees, courses like the Statistics and Applied Data Analysis Specialization are particularly beneficial. This specialization focuses on practical applications of statistics in real-world scenarios. Additionally, the Business Statistics and Analysis Specialization equips learners with essential skills for data-driven decision-making in business contexts. These courses can enhance workforce capabilities and drive organizational success.‎

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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