Significance in statistics is generally expressed as a P-value, which measure the chance of obtaining obtaining the answer you got randomly, even if there is no actual effect. In general, to be sure that there is an effect and you aren't just reading into noise, you want a P-value of less than 0.05, or 5%. Fortunately for us, this isn't an entirely scientific enterprise, so we're more willing to accept less surety in our values.

There are two things that effect significance, the size of the effect and the number of data points you have. In the last post, I chose predictors that I hoped would have a large effect to demonstrate what we're looking for. Even so, the data across the 2800 or so games was so sparse that only the intercept showed significance. Even smaller effects, such as the influence of individual tank types on the outcome of battles, will require a lot more data to show significance. This is why we ask you to contribute your replays through the Uploader, which is linked in the sidebar. Information on how to use it can be found in this post.

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