Aaron Simumba has completed

# Intro to Statistics with R: Introduction

4 hours
2,850 XP

## Course Description

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!

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1. 1

### Variables

Free

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.

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Types of variables
50 xp
50 xp
Longitude and latitude
50 xp
Nominal variables in R
100 xp
Ordinal variables in R
100 xp
Interval and ratio variables in R
100 xp
On the Theory of Scales of Measurement (Stevens, 1946)
50 xp
Two nominal variables
50 xp
Quick summary
50 xp
2. 2

### Histograms and Distributions

Free

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.

3. 3

### Scales of Measurement

Free

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.

4. 4

### Measures of Central Tendency

Free

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 :-).

5. 5

### Measures of Variability

Free

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.