Hypothesis testing Flashcards
What is a null hypothesis?
The null hypothesis (H0) is a specific claim about a parameter. The null hypothesis is the default hypothesis, the one assumed to be true unless the data lead us to reject it. A good null hypothesis would be interesting if rejected.
What is an alternative hypothesis?
The alternative hypothesis (HA) usually includes all values for the parameter other than that stated in the null hypothesis.
What is a 1-sided test? A two-sided test?
In a two-sided test, the alternative hypothesis includes parameter values on both sides of the parameter value stated by the null hypothesis.
In a one-sided test, the alternative hypothesis includes parameter values on only one side of the parameter value stated by the null hypothesis.
What is a critical value?
The threshold α is called the significance level of a test. Typically, α is set to 0.05.
What is a p-value? what does it tell you?
The P-value is the probability of obtaining a difference from the null expectation as great as or greater than that observed in the data if the null hypothesis were true.
If P is less than or equal to α, then H0 is rejected.
The P-value reflects the weight of evidence against the null hypothesis, but P does not measure the size of the effect.
What is Type I error? What level of Type I error is considered standard in science?
A Type I error is rejecting a true null hypothesis.
The probability of a TI error is set at the significance level.
It is set by experimenter will not change due to SE.
Bias will increase the chance type I error
What is Type II error? How does Type II error relate to statistical power?
A Type II error is failing to reject a false null hypothesis.
Type 2 error is used to calculate power (the probability that you fail to reject a true null)
Power= 1- Beta
Increasing the significance level will reduce type II error -> less likely to reject a true hypothesis
We fail to reject null hypothesis rather than accepting alternative hypothesis as the type II error may be high (low power)
What are the 3 steps of hypothesis testing?
1) state the hypotheses;
(2) compute the test statistic;
(3) determine the P-value;
(4) draw the appropriate conclusions.
What is hypothesis testing
Hypothesis testing uses data to decide whether a parameter equals the value stated in a null hypothesis. If the data are too unusual, assuming the null hypothesis is true, then we reject the null hypothesis.
What is a null distirbution
The null distribution is the sampling distribution of the test statistic under the assumption that the null hypothesis is true.
