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Step 2 Cheat Sheet (DRAFT) by

Step 2: Collect data from a sample

This is a draft cheat sheet. It is a work in progress and is not finished yet.

Sampling for Statis­tical Analysis

Probab­ility / Non-Pr­oba­bility sampling methods
Probab­ility sampling
every member of the population has a chance of being selected for the study through random selection
Non-pr­oba­bility sampling
some members of the population are more likely than others to be selected for the study because of criteria such as conven­ience or voluntary self-s­ele­ction.
Parametric / Non-Pa­ram­etric tests
Parametric tests
can be used to make strong statis­tical inferences when data are collected using probab­ility sampling. If you want to use parametric tests for non-pr­oba­bility samples, you have to make the case that:
 
(1) your sample is repres­ent­ative of the population you’re genera­lizing your findings to.
 
(2) your sample lacks systematic bias.
Non-pa­ram­etric tests
are more approp­riate for non-pr­oba­bility samples, but they result in weaker inferences about the popula­tion.
 
non-pr­oba­bility samples are more likely to be biased, they are much easier to recruit and collect data from
 

Calculate sufficient sample size

Before recruiting partic­ipants, decide on your sample size either by looking at other studies in your field or using statis­tics. A sample that’s too small may be unrepr­ese­ntative of the sample, while a sample that’s too large will be more costly than necessary.
Signif­icance level (alpha):
the risk of rejecting a true null hypothesis that you are willing to take, usually set at 5%.
Statis­tical power:
the probab­ility of your study detecting an effect of a certain size if there is one, usually 80% or higher.
Expected effect size:
a standa­rdized indication of how large the expected result of your study will be, usually based on other similar studies. tells you how meaningful the relati­onship between variables or the difference between groups is. It indicates the practical signif­icance of a research outcome.
Population standard deviation:
an estimate of the population parameter based on a previous study or a pilot study of your own