Rejecting or retaining a hypothesis in statistics will vary depending on if the hypothesis is true. Reject or retain a hypothesis in statistics with help from an experienced mathematics professional in this free video clip.

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Rejecting or retaining a hypothesis in statistics will vary depending on if the hypothesis is true. Reject or retain a hypothesis in statistics with help from an experienced mathematics professional in this free video clip.

Part of the Video Series: Trigonometry, Graphs, & Other Math Tips

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Hello. My name is Walter Unglaub and this is how to reject or retain an hypothesis in statistics. So if a hypothesis is given we call that the null hypothesis which we assume is going to be a true statement and once we've stated the null hypothesis we want to actually go out and conduct surveys or conduct experiments in order to build statistics. So if the sample is large enough then usually we'll obtain a Gaussian distribution for our statistical distribution. So in order to come up with a criteria to decide whether to reject or retain such a hypothesis one needs to establish what's called the level of significance. So this level of significance can be quantified using a Gaussian distribution where mu is the mean or average value and sigma is one standard deviation in the distribution by choosing some sort of threshold or cutoff. And that's what we're going to call our level of significance. Typically the level of significance is set at 5 percent. Meaning that if 5 percent of the results from your survey are in favor of your null hypothesis this means that it's 5 percent of the mean value and this 5 percent is small enough that this implies that your original null hypothesis can not be true. So the means by which you choose this cut off value depend on the experiment or your criteria. But the point is this is a way of quantifying based off of a statistical distribution and collection of data, a threshold for whether you can deem an hypothesis as statistically significant or not. My name is Walter Unglaub and this is how to decide whether to reject or retain a hypothesis in statistics.