# Secondary Catalogue

## Series: Hypothesis Testing

### Confidence Interval for the Difference of Means

We've done hypothesis testing around point estimates, like the mean or the proportion, but now we want to work a hypothesis test around the difference of two means. In this video we'll talk about how to build a confidence interval around the...Show More

### Confidence Interval for the Difference of Proportions

We've done hypothesis testing around point estimates, like the mean or the proportion, but now we want to work a hypothesis test around the difference of two proportions. In this video we'll talk about how to build a confidence interval around...Show More

### Hypothesis Testing for the Difference of Means

We've done hypothesis testing around point estimates, like the mean or the proportion, but now we want to work a hypothesis test around the difference of two means. In other words, sometimes we'll want to look at the difference between the means...Show More

### Hypothesis Testing for the Difference of Proportions

We've done hypothesis testing around point estimates, like the mean or the proportion, but now we want to work a hypothesis test around the difference of two means. In other words, sometimes we'll want to look at the difference between the...Show More

### Hypothesis Testing for the Population Proportion

In this video we'll look at how to run a full hypothesis test, from beginning to end, or a proportion, instead of a mean. We'll also consider what it looks like to run this as a one-tail test and as a two-tail test.

### Inferential Statistics and Hypotheses

We use a standard hypothesis testing procedure in order to perform inferential statistics. Our plan for running a hypothesis test will always be to state the null and alternative hypotheses, choose a level of significance at which we want to run...Show More

### Matched-Pair Hypothesis Testing

Normally when we're looking at the difference of means, we're dealing with independent samples, samples that don't impact each other. But sometimes we'll want to do hypothesis testing with dependent samples. When this is the case, we can run a...Show More

### Significance Level and Type I and II Errors

The level of significance is the alpha value of our test, and it also represents the probability of making a Type I error. A Type I error occurs when we mistakenly reject the null hypothesis when the null hypothesis is actually true.

### Test Statistics for One- And Two-Tailed Tests

When we run a hypothesis test, we can choose an upper-tail test, a lower-tail test, or a two-tail test, but it's really important that we make a conservative decision about the type of test we'll run. Once we pick our test type, then we'll...Show More

### The P-Value and Rejecting the Null

The p-value is the observed level of significance, it's the smallest level at which we can reject the null hypothesis, assuming that the null hypothesis is true. The p-value also tells us the total area of the region of rejection. So the p-value...Show More