Basic concepts Flashcards
Why are statistical tests important?
- Inherent in process of doing quantitative research
- Essential in designing research and interpreting results
What is a statistical test?
- A procedure for addressing a problem with a specified sequence of steps
- Relies on assumptions
- Requires the formulation of a hypothesis
What is a hypothesis?
An initial idea of expected patterns
Null hypothesis
H0 - The default - always assumed to be correct
- There is no statistically significant relationship/pattern
Alternative hypothesis
H1 - There is a statistically significant relationship/pattern
What is a confidence level?
- The probability that H1 is correct
- e.g. 99% or 95%
How does a table of critical values work?
If the output is greater than the critical value, you reject the null
Why do we ‘fail to reject’ the null instead of ‘accepting’ the alternative?
Leaves room to re-test and improve
The area under a distribution curve…
Represents the probability of an outcome in that range
What is significance level?
How likely it is that the results are due to chance/The probability that the null hypothesis is correct
When do we accept H1?
If the significance level is sufficiently low (usually 0.05 or 0.01)
When is the critical value determined?
Before the test is carried out
What is the population?
The whole body of individuals we’re interested in
What is the sample?
A collection of individuals drawn from a population
- two samples from the same population are expected to have the same characteristics
What is a sampling strategy?
A method applied to choose a sample from a population