Hypothesis testing begins long before any arithmetic: it begins with a careful translation of a claim into two competing statements about a population parameter. The null hypothesis (H0) is the statement of "no effect," "no difference," or "the claim as stated," and it always contains an equality. The alternative hypothesis (H1 or Ha) is the statement you are gathering evidence for, and it is written with <, >, or not-equal. Getting these two statements right determines everything that follows — which tail (or tails) of the sampling distribution you look at, how the p-value is computed, and what your conclusion is allowed to say.
In engineering practice, the claims you test are concrete: a supplier says a batch of fasteners averages at least a given tensile strength, a process engineer says a redesign reduced mean cycle time, a quality team says fill volume is on target and not drifting in either direction. Each of these maps to a different hypothesis form. A claim about being "on target" leads to a non-directional, two-tailed test; a claim about an improvement or a minimum guarantee leads to a directional, one-tailed test. The direction must be decided from the research question before the data are examined — choosing a tail after seeing which way the sample went is one of the most common and most serious errors in hypothesis formulation.
As you watch the videos below, pay attention to three things: (1) where the equality sign always lives, (2) how the wording of a claim ("at least," "more than," "differs from," "has changed") signals the direction, and (3) how the choice of one or two tails changes the shaded rejection region and the p-value calculation. Try writing H0 and H1 yourself from each spoken claim before the narrator does, then check your answer.
A short, focused explanation of the difference between one-tailed tests (both lower/left and upper/right) and two-tailed tests. It covers how the direction of the alternative hypothesis determines which tail or tails of the distribution are used, and shows the corresponding rejection regions.
This is the most direct match for the directional versus non-directional subtopics, and Joshua Emmanuel's statistics videos are known for clean, accurate visuals that make the tail structure easy to see in under four minutes.
A worked introduction to hypothesis testing built around a real-world claim: a fitness app's statement about average daily exercise time, tested with a z-test when the population standard deviation is known. The video walks through setting up the hypotheses from the claim and carrying the one-tailed test through to a conclusion.
It demonstrates the full path from a verbal, real-world claim to a correctly structured one-tailed H0 and H1, which is exactly the translation skill this topic emphasizes, and it shows why the formulation step matters for everything downstream.
This video focuses on the decision itself: how to read a research question and determine whether a one-tailed or two-tailed test is appropriate. It is framed around interpreting question wording rather than on computation.
It gives a second perspective on the "choosing between directional and non-directional forms" subtopic and helps you avoid the common error of picking a tail arbitrarily or after the fact.
These three videos concentrate on MO1: translating a real-world claim into correctly structured null and alternative hypotheses, including both one-tailed and two-tailed forms. The Emmanuel z-test example additionally previews MO3 and MO4 by carrying a formulated hypothesis through a test statistic and p-value to a conclusion at a stated significance level, so you can see how the setup choice propagates. They do not cover test selection among t-tests, chi-square, and ANOVA (MO2) or Type I and Type II errors (MO5); those outcomes are addressed by other materials in this module.
These videos were chosen from YouTube on October 2, 2026. Each has captions; the player turns them on. Videos on YouTube can be changed or removed — if one no longer plays, tell your instructor. If a player does not appear, use its Watch on YouTube link.