In this chapter professor Conway will cover types of variables. It is very important to understand what type of variable you are dealing with when conducting a particular type of statistical analysis. You will cover variables such as nominal, ordinal, interval and ratio, and you will experiment with these via interactive exercises in R.

Types of variables

Basketball standings

Longitude and latitude

Nominal variables in R

Ordinal variables in R

Interval and ratio variables in R

On the Theory of Scales of Measurement (Stevens, 1946)

Two nominal variables

Quick summary

Variables

Chapter One

You will look here at distributions in graphs called histograms. A histogram is one of the simplest graphs used in statistics, but they are very useful and very informative. Studying histograms will help you to overcome the tendency to put too much of a focus on summary statistics.

Histograms and distributions

Creating histograms in R

Reading histograms

Looking at distributions by using histograms (1)

Positive and negative skew

Looking at distributions by using histograms (2)

Red wine tasting

White wine tasting

A uniform distribution

A negatively skewed distribution

Leptokurtic distribution

Histograms and Distributions

Chapter Two

When working with data it is very important to keep in mind what type of scale you are dealing with, hence this chapter on scales of measurement. This chapter will introduce you to the different types of scales with a specific focus on the standard scale, the z-scale.

Scales of measurement

Converting a value to its Z-score

Interpretation of a Z-score

Converting a distribution to Z-scale

Scales of Measurement

Chapter Three

In the previous chapters you looked at distributions and the importance of these. In this chapter the focus is more on summarizing all available information and drafting summary statistics. To make it a little bit more fun, the examples will be based on a wine tasting experiment :-).

Measures of central tendency

The mean of a Fibonacci sequence

Three measures of central tendency (1)

Measures of central tendency: mode

Choosing a measure of central tendency

Three measures of central tendency (2)

Setting up histograms

Types of distribution

Robustness to outliers

Get intuitive!

Measures of Central Tendency

Chapter Four

Measures of central tendency try to capture the center point of a distribution. Measures of variability want to capture how much spread there is, or how wide the distribution is. The two measures you will look at in this final chapter will be standard deviation and variance.

Measures of variability

Sample variance formula

Calculating variance in practice

Purpose of measures of variability

Michael Jordan's first NBA season

Calculate the variance manually

Measures of Variability

Chapter Five

Not sure if this is the type of online statistics course you’re looking for? Or perhaps not yet familiar with DataCamp’s interactive learning interface? By taking this free course, you can discover it for yourself! Via a combination of videos and interactive coding challenges, this introductory course will teach you about variables, plotting, and summary statistics like the mean and standard deviation. Enjoy learning by doing!

This introductory statistics with R tutorial will teach you about variables, plotting, and summary statistics like the mean and standard deviation.

Free Introduction to Statistics with R

A friendly introduction to fundamental concepts in statistics in R.

Intro to Statistics with R: Introduction

Measures of central tendency: mode

Intro to Statistics with R: Introduction

Exercise instructions

Hands-on interactive exercise