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This video gives you an overview of the basics of statistics. It starts with teaching you exactly what statistics is as well what data is and some examples of types of data. There are two main types of statistics used when analyzing data. They are inferential and descriptive statistics and this video provides definitions and examples of both. You will also learn about populations and samples and how they are related to one another.

This video teaches you about alpha levels and when to reject or accept a hypothesis. It provides examples of how this is done and how to interpret alpha levels in conjunction with hypotheses.

When doing hypothesis testing you often want to calculate the effect size. This is because hypothesis testing doesn't really tell you anything about the strength of the measure. The effect size measures the strength of an effect. This video teaches you how to do this as well as the difference between a small, medium, and large effect size.

In statistics we generally want to make a conclusion about a population, but often this isn't possible. Instead we use a sample size in inferential statistics to draw conclusions from sets of data. The Distribution of the Sample Mean is the probablity distribution for all possible values of a sample mean, computed from a sample size of n. Now, this may sound a little confusing which is why the video provides examples of exactly what this means and how it can be calculated. The video also shows you how to take this information and display it on a graph which is another helpful way to view the data. You will also learn about the Law of Large numbers and the Standard Error of the Mean and what those are and how to calculate them.

The video provides many different examples of distributions. We typically view "normal" distributions, but not always, and this video shows you what to do when you get a distribution that isn't deemed normal. This video also teaches you about the standard deviation and how it changes based on your sample size. You will learn about variance, standard error of the mean, and how to calculate them as well as examples of each.

Z-Scores are standardized values that can be used to compare scores in more than one distribution. The video explains this in greater detail and provides many examples of how to achieve this. It shows you how to compare different sets of data within distributions and teaches you about standard deviations and how to understand those.

This video teaches you how to perform an analysis when you don't know the population standard deviation by using the Student's T-Distribution. It shows exactly how this process is done, some examples, and what charts you use in your textbook to find the correct distribution scores. The video also teaches you about Degrees of Freedom, how to calculate it, and how to relate it to T-Distributions.