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  • Basic Statistics

Basic Statistics Courses

Basic Statistics courses can help you learn data collection methods, descriptive statistics, probability distributions, and hypothesis testing. You can build skills in interpreting data sets, conducting surveys, and performing regression analysis. Many courses introduce tools like Excel, R, and Python, that support analyzing data and visualizing results. By applying these skills and tools, you can effectively communicate findings and make informed decisions based on statistical evidence.


Popular Basic Statistics Courses and Certifications


  • Status: Free Trial
    Free Trial
    U

    University of Amsterdam

    Basic Statistics

    Skills you'll gain: Statistical Hypothesis Testing, Statistics, Scientific Methods, Quantitative Research, Data Analysis Software

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

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    M

    Meta

    Statistics Foundations

    Skills you'll gain: Bayesian Statistics, Descriptive Statistics, Statistical Hypothesis Testing, Statistical Inference, Sampling (Statistics), Data Modeling, Statistics, Probability & Statistics, Statistical Analysis, Statistical Methods, Statistical Modeling, Marketing Analytics, Tableau Software, Data Analysis, Spreadsheet Software, Analytics, Time Series Analysis and Forecasting, Regression Analysis

    4.8
    Rating, 4.8 out of 5 stars
    ·
    380 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Excel Basics for Data Analysis

    Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Analysis, Data Import/Export, Spreadsheet Software, Data Wrangling, Data Quality, Pivot Tables And Charts, Google Sheets, Data Manipulation, Data Science, Information Privacy

    4.7
    Rating, 4.7 out of 5 stars
    ·
    11K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Statistics

    Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.3K reviews

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    S

    SAS

    Statistics You Need to Know for Machine Learning

    Skills you'll gain: Exploratory Data Analysis, Logistic Regression, Supervised Learning, Applied Machine Learning, Model Evaluation, Data Modeling

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    R

    Rice University

    Business Statistics and Analysis

    Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Statistical Methods, Pivot Tables And Charts, Regression Analysis, Statistics, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Modeling, Statistical Analysis, Statistical Inference, Excel Formulas, Data Analysis, Data Presentation, Model Evaluation, Sample Size Determination

    4.7
    Rating, 4.7 out of 5 stars
    ·
    13K reviews

    Beginner · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • Status: New
    New
    Status: Free Trial
    Free Trial
    B

    Birla Institute of Technology & Science, Pilani

    Probability and Statistics

    Skills you'll gain: Data Analysis, Statistical Analysis, Data Visualization, Predictive Modeling, Applied Mathematics

    4.2
    Rating, 4.2 out of 5 stars
    ·
    6 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    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 Science, Statistics, Mathematical Modeling, Data Analysis, Data Modeling, Applied Mathematics

    4.4
    Rating, 4.4 out of 5 stars
    ·
    783 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    The Power of Statistics

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

    4.8
    Rating, 4.8 out of 5 stars
    ·
    863 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Statistics with Python

    Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Modeling, Statistical Methods, Statistical Inference, Bayesian Statistics, Data Visualization, Statistics, Matplotlib, Statistical Visualization, Statistical Software, Probability & Statistics, Model Evaluation, Statistical Analysis, Jupyter, Statistical Machine Learning, Statistical Programming, Regression Analysis, Data Visualization Software, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.3K reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Statistics and Applied Data Analysis

    Skills you'll gain: Statistical Hypothesis Testing, Descriptive Statistics, Statistical Visualization, Data Transformation, Data Cleansing, Statistical Analysis, Regression Analysis, Probability, Probability Distribution, Sampling (Statistics), Box Plots, Histogram, R Programming, Statistical Methods, Scatter Plots, Microsoft Excel, Probability & Statistics, Statistics, Data Import/Export, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    46 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Preview
    Preview
    U

    University of Zurich

    An Intuitive Introduction to Probability

    Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Statistics, Descriptive Statistics, Applied Mathematics, Risk Analysis, Finance

    4.8
    Rating, 4.8 out of 5 stars
    ·
    1.9K reviews

    Beginner · Course · 1 - 3 Months

Searches related to basic statistics

basic statistics in python (correlations and t-tests)
basic inferential statistics for psychology
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1234…414

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

  • Basic Statistics: University of Amsterdam
  • Statistics Foundations: Meta
  • Excel Basics for Data Analysis: IBM
  • Introduction to Statistics: Stanford University
  • Statistics You Need to Know for Machine Learning: SAS
  • Business Statistics and Analysis: Rice University
  • Probability and Statistics: Birla Institute of Technology & Science, Pilani
  • Advanced Statistics for Data Science: Johns Hopkins University
  • The Power of Statistics: Google
  • Statistics with Python: University of Michigan

Frequently Asked Questions about Basic Statistics

Basic statistics is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. It is essential because it provides the tools needed to make informed decisions based on data, which is increasingly important in various fields such as business, healthcare, social sciences, and more. Understanding basic statistics helps individuals interpret data accurately, recognize trends, and make predictions, which can significantly impact decision-making processes.‎

A background in basic statistics opens up various job opportunities across multiple sectors. Positions such as data analyst, market researcher, business analyst, and quality control analyst often require a solid understanding of statistical principles. Additionally, roles in healthcare, education, and social research also value statistical skills, as they rely on data analysis to inform practices and policies.‎

To learn basic statistics, you should focus on several key skills. These include understanding descriptive statistics (mean, median, mode), probability concepts, data visualization techniques, and basic inferential statistics (hypothesis testing, confidence intervals). Familiarity with statistical software or tools, such as Excel or R, can also enhance your ability to analyze data effectively.‎

There are several excellent online courses available for learning basic statistics. For instance, the Basic Statistics course provides a comprehensive introduction to the subject. Additionally, the Basic Inferential Statistics for Psychology Specialization offers a focused approach for those interested in psychology-related applications of statistics.‎

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

  1. Preview the first module of many basic 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 basic statistics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

Learning basic statistics can be approached through various methods. Start by enrolling in online courses that cover the fundamentals. Engage with interactive exercises and quizzes to reinforce your understanding. Additionally, practicing with real-world data sets can help solidify your skills. Joining study groups or forums can also provide support and enhance your learning experience.‎

Typical topics covered in basic statistics courses include descriptive statistics, probability theory, sampling methods, hypothesis testing, and regression analysis. These subjects provide a solid foundation for understanding how to analyze and interpret data effectively.‎

For training and upskilling employees, courses like the Business Statistics and Analysis Specialization are particularly beneficial. They focus on applying statistical methods to business contexts, making them ideal for workforce development in data-driven environments.‎

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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