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Intro to Descriptive Statistics

Free Course

Mathematics for Understanding Data

Related Nanodegree Program

Data Analyst

About this course

Statistics is an important field of math that is used to analyze, interpret, and predict outcomes from data. Descriptive statistics will teach you the basic concepts used to describe data. This is a great beginner course for those interested in Data Science, Economics, Psychology, Machine Learning, Sports analytics and just about any other field.

What you will learn

  1. Intro to Research Methods
    • Introduction to several statistical study methods.
    • Learn the positives and negatives of each.
  2. Visualizing Data
    • Take your data and display it to the world.
    • Create and interpret histograms, bar charts, and frequency plots.
  3. Central Tendency
    • Compute and interpret the 3 measures of center for distributions: the mean, median, and mode.
  4. Variability
    • Quantify the spread of data using the range and standard deviation.
    • Identify outliers in data sets using the concept of the interquartile range.
  5. Standardizing
    • Convert distributions into the standard normal distribution using the Z-score.
    • Compute proportions using standardized distributions.
  6. Normal Distribution
    • Use normalized distributions to compute probabilities
    • Use the Z-table to look up the proportions of observations above, below, or in between values
  7. Sampling Distributions
    • Apply the concepts of probability and normalization to sample data sets.

Prerequisites and requirements

This course assumes understanding of basic algebra and arithmetic.

See the Technology Requirements for using Udacity.

Why take this course?

This course will teach you the basic terms and concepts in statistics as well as guide you through introductory probability. You will learn how to....

  • Use statistical research methods.
  • Compute and interpret values like: Mean, Median, Mode, Sample, Population, and Standard Deviation.
  • Compute simple probabilities.
  • Explore data through the use of bar graphs, histograms, box plots, and other common visualizations.
  • Investigate distributions and understand a distributions properties.
  • Manipulate distributions to make probabilistic predictions on data.

Learn with the best.

  • Ronald Rogers
    Ronald Rogers


  • Katie Kormanik
    Katie Kormanik


  • Sean Laraway
    Sean Laraway