Session 5: Statistical testing Flashcards
inferential statistics
drawing conclusions about a population based on sample data
- we formulate hypotheses using a sample drawn from the population
Sampling error
random variability in a statistic from sample to sample
- bc. they sample statistics are not perfect estimated of their corresponding population parameter
Nulll hypothesis tetsing
formal approach to decicidng whther a statistical relationship in a sample reflects a real relationship in the population ot is just due to chance
What is a research hypothesis?
claims a more or less precise relationship between two or more variales that is expected to holf for a given population
Research hypothesis can be classified into..
- Hypothesis about differences
- Hypothesis about correlations
- HYpothesis about changes
The logic of null hypothesis testing
How likely the sample result would be if the null hypothesis were true?
- if the sample result would be extremely unliekly if the null hypothesis were true then we reject the null hypothesis in favor of the alternative hypothesis
- if the sample result would not be extremely unlikely if the null hypothesis were true, then we retain the null hypothesis
p- value (and it’s meaning)
probability of the sample result or a more extreme result if the null hypothesis were true
- low p-value: the sample result would be unlikely if the null hypothesis were true, rejection of the null hypothesis
- high p-value: the sample result would be likely if the null hypothesis were ture, retention of the null hypothesis
alpha
says how low the p-value must be before the sample result is considered unlikely enough to reject the null hypothesis (0.05)
- if there is a 5% chance or less of a result if the null hypothesis were true, then we rejcet the null hypothesis (result is significant)
- if there is a greater chnace than 5% pf a result if the null hypothesis were ture, the null hypothesis is retained
sampling distribution
- probability distribution of a statistic based on a large number of sample from a given popuation
- in each null hypothesis tetsing study, we determine a statistic tat summarizes, as much as possible, all of the hypothesis relevant info of a study (sample dependent)
Type 1 error
Rejecting the null hypothesis when it is true
Type 2 error
retaining the null hypothesis when it is false