Intro to Stats and Statistical Testing
1A big question in philosophy is "How do we know things?" In science, the answer to this is simple - stats. Assuming that you have correct methodology (which is not a simple or easy thing) stats tell us if two groups are distinct or not. So if you give a drug to someone and measure the impact, you look at the results and see if they are statistically significantly different from the control group that was given a placebo.
We typically use thresholds of 95% confidence (p-value less than 0.05) to publish a paper, though this goes up or down depending on the field and publication.
We started with the basic stats: the mean (average), median (score of the average person), mode (most common outcome), count (N = how many people are in the group), and standard deviation (stddev or σ or SD, which means how "wide" the bell curve is in terms of encompassing 68% of the data within +-1 standard deviation).
To do a statistical t-test you punch in the mean, stddev and N for two groups and it will tell you how likely the differences in the two groups was due to chance. This is called the "p-value" and is written with the less than character that I can't put in YouTube, so "p-value less than 0.42" means that there was a 42% chance that the difference between the two groups is due to chance. This isn't good enough to publish, but may be enough to encourage us to run the experiment more times and get more data.
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