4 Flashcards
Hypothesis testing?
How unusual is it to get our data if the null hypothesis is true
!!!!How to undergo hypothesis testing?
•Imagine if the hypothetical population (null hypothesis H_0 true).
•generating a distribution of
Hypothesis testing usually assumes that sampling is?
Random
Null hypothesis?
Specific statement about a population parameter made for the purposes of an argument.
Alternative hypothesis?
Another possible possibility.
Test statistic?
Number calculated to represent the match between a set of data and a null hypothesis. In other words, if n exceeds the test statistic, the null hypothesis can be rejected since the values are extreme.
If the value of the test statistic is approaching y = 0 under the null hypothesis, then?
It is surprising.
P-value is the?
Probability of getting the data or smth as or more unusual if the null hypothesis were true in a test statistic.
Null distribution?
For a test statistic, is the probability distribution of alternative outcomes when a random sample is taken from a hypothetical population in which the null hypothesis is true.
If the null distribution approaches x = +-oo, then?
The null hypothesis is more likely to be disproved.
Statistical significance (alpha)?
Probability used as a criterion for rejecting the null hypothesis.
Alpha is often set as?
0.05, 1/20, which means that its okay for 5% extreme values.
If P < alpha, then?
We can reject the null hypothesis.
What does a p value mean?
Probability of getting the results if the null hypothesis is true.
Type 1 error?
When rejecting a true null hypothesis since the p value calculated was low enough to reject. (Does not depend on sample size because the test takes into account of sample size)
P-hacking
Type II error?
Not rejecting a false null hypothesis. If null hypothesis is false, the probability of a Type II error is beta. The smaller beta, the more power a test has. Beta is lower with a larger sample size.
Power?
Ability of a test to reject a false null hypothesis.
Power = ?
1 - beta
Why do we usually don’t know beta?
Because we don’t know the truth
A larger sample size will tend to give an estimate with a larger/smaller confidence interval?
Smaller
Critical value?
Value of a test statistic beyond which the null hypothesis can be rejected.
Statistically significant?
When p < alpha
