Category: statistics
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A goldmine of information…
I’ve just discovered the awesome Brandon Rohrer and his blog while trying to find an intelligible article on Bayesian inference. What a goldmine – this guy is a born educator! Thank you for sharing your knowledge – it is well-appreciated!
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Law of total probability – worked examples
According to Wikipedia the law of total probability “expresses the total probability of an outcome which can be realized via several distinct events”. We can also think of this as the marginal probability: irrespsective of what road we took to get to this outcome, what is the total likelihood of the outcome occurring? Example 1…
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Expected value refresher
The expected value of an event is its most likely outcome. Assign each potential result a probability. The expected value is sum of all the potential results x their respective probabilities: ∑ (potential_result1 x probability1,… potential_resultn x probabilityn) Consider the simplest example possible, the coin flip. You’ll be paid R10 if you pick tails, but…
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Multivariate regression
So: with linear regression (aka simple linear regression) we have one feature which we are using to predict a dependent value (for example number of rooms as a predictor of house price). With multivariate regression (aka multiple linear regression) we simply have multiple features which could be used to predict that dependent value (for example…
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Co-variance, Correlation & Linear Regression
Typically we have 2 sets of values and we want to find out if these 2 sets of values are related, and if so how, and by how much? Could height be indicative of weight? Could hours of practice be related to how many errors are made in a mathematical test paper? Co-variance is a…
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T testing – a worked example
A simple one-sample T-test This variant on hypothesis testing is used when you have limitations, specifically: The population standard deviation (σ) is unknown and your sample size (n) is <30 The fundamentals The formula is a variant of what we’ve seen thus far, where x̄ = your sample mean, μ = a hypothesized population mean,…
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Proportion testing
Using everything we’ve learned so far about the central limit theorem, the z-score, and hypothesis testing, we can now also perform proportion testing! There are just a few new concepts to add into the mix: The preliminary terrors – notation & terminology p = the proportion of items that falls into H0 q = the…
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Hypothesis testing basics
A simple example of hypothesis testing is where we know what “normal” is, and we want to evaluate whether some sample conforms to our understanding of “normal”, or is so unusual that it’s indicative of an actual shift in behaviour or pattern. Make your hypothesis statement If I…(do this to an independent variable)….then (this will…
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