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# Intro to Statistics with R: Introduction

A friendly introduction to fundamental concepts in statistics in R.

Start Free Course4 Hours16 Videos45 Exercises

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## 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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### 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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### 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.

Histograms and distributions50 xpCreating histograms in R100 xpReading histograms50 xpLooking at distributions by using histograms (1)50 xpPositive and negative skew50 xpLooking at distributions by using histograms (2)50 xpRed wine tasting100 xpWhite wine tasting100 xpA uniform distribution50 xpA negatively skewed distribution50 xpLeptokurtic distribution50 xpQuick summary50 xp - 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.

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### 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 :-).

Measures of central tendency50 xpThe mean of a Fibonacci sequence100 xpThree measures of central tendency (1)50 xpMeasures of central tendency: mode50 xpChoosing a measure of central tendency50 xpThree measures of central tendency (2)50 xpSetting up histograms100 xpTypes of distribution50 xpRobustness to outliers100 xpGet intuitive!50 xpQuick summary50 xp - 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.

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