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Description

We live in a world of data. We measure everything from the current temperature to how many steps we take each day. Understanding statistics allows us to analyze and interpret numerical data.

There are two branches of statistics. Purely mathematical statistics, or statistical inference, is about drawing scientific conclusions from data. Descriptive statistics deals with the collection, analysis, presentation, and summarization of data. This introductory course explains the basic concepts of descriptive statistics. It's a must for anyone who works with data.

During this course, you will learn about the three common measures of central tendency: arithmetic mean, median, mode. You'll also learn how to measure the variability of a distribution and compute variance and standard deviation. You'll get to know how to measure asymmetry and you'll be able to define fancy words like "kurtosis" and "skewness". And you'll acquire some basic data visualization skills, too: how to create and read histograms, bar charts, and box plots.

Don't worry if you're completely new to statistics: we've designed this course for absolute beginners. All you need is some basic math skills and an Internet connection.

What Are the Requirements?

Just a web browser

This Course Will Teach You How To:

  • Read and create histograms
  • Visualize a distribution of numerical values
  • Measure the different centers of a distribution: arithmetic mean, median, and mode
  • Measure the variability of a distribution: standard deviation and variance
  • Understand quartiles, percentiles, quantiles
  • Measure the asymmetry of distribution: skewness and kurtosis

Who Should Take This Course?

  • Everyone who wants to learn about statistics
  • Students
  • Beginning data scientists
  • Beginning statisticians

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    One to Rule 'Em All

    Includes 36 courses Python Basics. Part 1, Python Basics. Part 2, Python Basics. Part 3, Python Data Structures in Practice, Built-in Algorithms in Python, Working with Strings in Python, SQL Basics, SQL Practice Set, SQL JOINs, Standard SQL Functions, Creating Basic SQL Reports, Window Functions, Revenue Trend Analysis in SQL, How to INSERT, UPDATE, and DELETE Data in SQL, Recursive Queries, Creating Tables in SQL, Statistics 101, SQL Basics in MS SQL Server, How to Insert, Update, or Delete Data in MS SQL Server, Common Functions in MS SQL Server, Revenue Trend Analysis in SQL Server, Creating Basic SQL Reports in SQL Server, Window Functions in MS SQL Server, Recursive Queries in MS SQL Server, GROUP BY Extensions in MS SQL Server, Introduction to Python for Data Science, How to Read and Write CSV Files in Python, How to Read and Write JSON Files in Python, SQL Basics in PostgreSQL, PostgreSQL JOINs, SQL Practice Set in PostgreSQL, Window Functions in PostgreSQL, Recursive Queries in PostgreSQL, Writing User-Defined Functions in PostgreSQL, PostGIS, How to Read and Write Excel Files in Python

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    Basic Data Analytics

    Includes 5 courses SQL Basics, SQL Practice Set, SQL JOINs, Statistics 101, Introduction to Python for Data Science

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    Table of contents

    Progress: 0% completed 0 of 54 exercises done

    1. Introduction

    What is statistics?

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    2. Histograms

    Learn what histograms are, how to create and how to read them.

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    3. Mean, Median, Mode

    Find out how to identify the center of a distribution

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    4. Measures of Variability

    Learn how to measure how spread out are the values. You'll learn about quartiles, percentiles, standard deviation, variance and more

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    5. Measures of Asymmetry

    Find out how to measure the asymmetry of the distribution. Learn how to calculate and interpret kurtosis and skewness.

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    6. How to Visualize Data – Other Graphs

    Learn more about graphic representations of data. Discover the true power of box charts and box plots.

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    7. Quiz

    Test your knowledge of descriptive statistics.

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