What is the null hypothesis (Hโ)?
A statement that there is no effect or no difference; the hypothesis we are trying to disprove.
What is the alternative hypothesis?
The hypothesis that contradicts the null hypothesis; it represents what we are trying to find evidence for.
What is a p-value?
The probability of observing a test statistic as extreme as, or more extreme than, the one computed, assuming the null hypothesis is true.
What is the significance level (ฮฑ)?
The probability of rejecting the null hypothesis when it is actually true (Type I error).
What does it mean to 'reject the null hypothesis'?
To conclude that there is sufficient evidence to suggest the null hypothesis is false.
What does it mean to 'fail to reject the null hypothesis'?
To conclude that there is not enough evidence to reject the null hypothesis; it does NOT mean the null hypothesis is true.
What is the formula for the z-score in a one-proportion z-test?
z = (pฬ - pโ) / โ(pโ(1-pโ)/n), where pฬ is the sample proportion, pโ is the hypothesized population proportion, and n is the sample size.
What is the formula for the test statistic (t) in a one-sample t-test?
t = (xฬ - ฮผ) / (s/โn), where xฬ is the sample mean, ฮผ is the population mean, s is the sample standard deviation, and n is the sample size.
Explain the concept of statistical significance.
Statistical significance indicates that the observed result from a sample is unlikely to have occurred by chance alone if the null hypothesis were true, usually determined by comparing the p-value to the significance level (alpha).
Explain the relationship between p-value and the decision to reject or fail to reject the null hypothesis.
If the p-value is less than or equal to the significance level (ฮฑ), we reject the null hypothesis. If the p-value is greater than ฮฑ, we fail to reject the null hypothesis.
Explain the importance of context in the conclusion of a hypothesis test.
Including context in the conclusion connects the statistical results back to the real-world scenario, making the conclusion meaningful and interpretable in the context of the problem.
Explain the meaning of a large z-score in hypothesis testing.
A large z-score (typically > 2 or < -2) indicates that the sample statistic is far from what is expected under the null hypothesis, providing evidence to reject the null hypothesis.
Explain what the z-score represents.
The z-score represents the number of standard deviations a data point is from the mean of the distribution.