Basics
What does H₀ mean?
It is the assumption that there is no significant effect or difference.
What is a Type I error?
Rejecting H₀ when it’s actually true.
What is a 5% significance level?
There’s a 5% chance we reject H0H_0H0 by mistake.
What is a critical region?
The range of values where we reject H₀.
What does H₁ mean?
The idea that something has changed or is different.
What is a Type II error?
Not rejecting H₀ when it’s actually false.
What symbol represents the significance level?
alpha
If our result is inside the critical region, what do we do?
Reject H₀.
What are we trying to find out in hypothesis testing?
Whether we have enough evidence to reject H₀.
Which type of error is like “missing the real problem”?
Type II error.
If αlpha = 0.05, how confident are we in our decision?
95% confident.
If our result is outside the critical region, what do we do?
Do not reject H₀.
What’s the test based on?
The sample.
Which type of error is like a “false alarm”?
Type I error.
Is a 1% significance level more or less strict than 5%?
More strict.
What does two-tailed test mean?
We test for changes in both directions (higher or lower).
What are the two possible decisions we can make in hypothesis testing?
Reject H₀ or do not reject H₀.
True or False: Making the significance level smaller reduces Type I errors.
True.
What happens when we use a smaller significance level?
We make fewer Type I errors but more Type II errors.
What does “one-tailed test” mean?
We only test if the value is bigger or smaller, not both.