Data – What It Is, What We Can Do With It

  • 4.5
Approx. 11 hours to complete

Course Summary

This course provides an introduction to data and its applications in various fields. You will gain an understanding of how data can be collected, analyzed, and used to make informed decisions.

Key Learning Points

  • Learn the basics of data and its applications in various fields
  • Understand the importance of data analysis in decision-making
  • Explore real-world examples of data usage

Related Topics for further study


Learning Outcomes

  • Understand the basics of data and its uses
  • Learn how to collect and analyze data
  • Apply data analysis to real-world scenarios

Prerequisites or good to have knowledge before taking this course

  • Basic computer skills
  • Familiarity with spreadsheets

Course Difficulty Level

Beginner

Course Format

  • Online self-paced
  • Video lectures
  • Quizzes

Similar Courses

  • Data Science Essentials
  • Data Visualization with Tableau
  • SQL for Data Science

Related Education Paths


Notable People in This Field

  • Nate Silver
  • Hilary Mason

Related Books

Description

This course introduces students to data and statistics. By the end of the course, students should be able to interpret descriptive statistics, causal analyses and visualizations to draw meaningful insights.

Outline

  • Data and Theories
  • Welcome Video
  • Statistical Inference
  • Components of Scientific Research
  • Scientific Theories
  • Big Data is Not About the Data!
  • We're All Social Scientists Now
  • Theories in Scientific Research
  • Final Quiz
  • The Causality Framework
  • Causal Effects and the Counterfactual
  • Randomized Controlled Trials
  • Observational Studies: Overview
  • Observational Studies: Strategies for Estimating Causal Effects
  • Causal Inference Based on Counterfactuals
  • A Simplified Guide to Randomized Controlled Trials
  • Difference-in-Difference Estimation
  • Practice Problem
  • Practice Problems
  • Practice Problems
  • Final Quiz
  • Descriptive Statistics
  • Why do we need descriptive statistics?
  • Measures of Central Tendency
  • Measures of Spread
  • Dispersion
  • Descriptive Statistics: Introduction
  • Measures of the Center of the Data
  • Measures of the Location of the Data
  • Measures of the Spread of the Data
  • Skewness and the Mean, Median and Mode
  • Practice Problems
  • Practice Problems
  • Practice Problems
  • Final Quiz
  • Visualizations
  • Elements of Good Visualizations
  • Bar Plots, Histograms and Box Plots
  • Scatter Plots, Line Graphs and Side-by-Side Bar Graphs
  • Publication, Publication
  • A Complete Guide To Bar Charts
  • Comparing Box Plots and Histograms
  • A Complete Guide to Scatter Plots
  • Practice Problems
  • Practice Problems
  • Practice Problems
  • Final Quiz

Summary of User Reviews

Discover the power of data with Data: What It Is and What We Can Do with It course on Coursera. Users highly recommend this course for its engaging content and comprehensive approach.

Key Aspect Users Liked About This Course

Engaging content

Pros from User Reviews

  • Comprehensive approach to data analysis
  • Great course for beginners
  • Engaging and interactive content
  • Well-structured and easy to follow
  • Real-life examples and case studies

Cons from User Reviews

  • Lack of advanced topics
  • Some technical issues with the platform
  • Limited interaction with instructors
  • Some lectures are too basic
  • Not suitable for experienced data analysts
English
Available now
Approx. 11 hours to complete
Jennifer Bachner, PhD
Johns Hopkins University
Coursera

Instructor

Jennifer Bachner, PhD

  • 4.5 Raiting
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