Forecasting the future has always been one of man’s biggest desires and many approaches have been tried over the centuries. In this post we will look at a simple statistical method for *time series analysis*, called *AR* for *Autoregressive Model*. We will use this method to predict future sales data and will rebuild it to get a deeper understanding of how this method works, so read on!

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# Category: Learning R

Posts about learning R

## Learning Data Science: A/B Testing in Under One Minute

Google does it! Facebook does it! Amazon does it for sure!

Especially in the areas of web design and online advertising, everybody is talking about *A/B testing*. If you quickly want to understand what it is and how you can do it with R, read on!

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## Learning R: Build a Password Generator

It is not easy to create secure passwords. The best way is to let a computer do it by randomly combining lower- and upper-case letters, digits and other printable characters.

If you want to learn how to write a small function to achieve that read on!

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## Learning Statistics: Randomness is a Strange Beast

Our intuition concerning *randomness* is, strangely enough, quite limited. While we expect it to behave in certain ways (which it doesn’t) it shows some regularities that have unexpected consequences. In a series of seemingly random posts, I will highlight some of those regularities as well as consequences. If you want to learn something about randomness’ strange behaviour and gain some intuition read on!

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## Learning R: Build *xkcd’s* Star Wars Spoiler Generator

Star Wars is somewhat nerdy, R definitely is… what could be more worthwhile than combining both ðŸ˜‰

This Sunday was Star Wars Day (May the 4th be with you!) and suitable for the occasion we will do a little fun project and implement the following *xkcd* flowchart, which can give us more than 2 million different Star Wars plots.

Even if you are new to R, the used code should be comprehensible, so read on!

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## ZeroR: The Simplest Possible Classifier… or: Why High Accuracy can be Misleading

In one of my most popular posts So, what is AI really? I showed that *Artificial Intelligence (AI)* basically boils down to autonomously learned rules, i.e. *conditional statements* or simply, *conditionals*.

In this post, I create the simplest possible *classifier*, called *ZeroR*, to show that even this classifier can achieve surprisingly high values for *accuracy* (i.e. the ratio of correctly predicted instances)… and why this is not necessarily a good thing, so read on!

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## COVID-19: Analyze Mobility Trends with R

The global lockdown has slowed down mobility considerably. This can be seen in the data produced by our ubiquitous mobile phones.

Apple is kind enough to make those anonymized and aggregated data available to the public. If you want to learn how to get a handle on those data and analyze trends with R read on!

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## COVID-19 in the US: Back-of-the-Envelope Calculation of Actual Infections and Future Deaths

One of the biggest problems of the COVID-19 pandemic is that there are no reliable numbers of infections. This fact renders many model projections next to useless.

If you want to get to know a simple method how to roughly estimate the real number of infections and expected deaths in the US, read on!

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## Contagiousness of COVID-19 Part I: Improvements of Mathematical Fitting (Guest Post)

**Learning Machines** proudly presents a guest post by **Martijn Weterings** from the Food and Natural Products research group of the Institute of Life Technologies at the University of Applied Sciences of Western Switzerland in Sion.

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## The One Question you should ask your Partner before Marrying!

Valentine’s Day is around the corner and love is in the air… but, shock horror, nearly every second marriage ends in a divorce! Unfortunately, I can tell you first hand that this is an experience you’d rather not have. In this post, we see how *data science*, in the form of the `OneR`

package and an interesting new data set, might potentially help you to avoid that tragedy… so read on!

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