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Step 1 Cheat Sheet (DRAFT) by

Step 1: Write your Hypotheses and plan your Research Design

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

Hypotheses

H0: Null Hypothesis
the H0 of a test always predicts no effect or no relati­onship between variables
H1: Altern­ative Hypothesis
H1 states your research prediction of an effect or realti­onship
 

Research Design

experi­mental design
you can assess a cause-­and­-effect using statis­tical tests of comparison or regres­sion.
 
e.g., the effect of meditation on test scores
correl­ational design
you can explore relati­onships between variables without any assumption of causality using correl­ation coeffi­cients and signif­icance tests.
 
e.g., parental income and GPA
descri­ptive design
you can study the charac­ter­istics of a population or phenomenon using statis­tical tests to draw inferences from sample data.
 
e.g., the prevalence of anxiety in U.S. college students
Betwee­n/W­ithin - subject Design
betwee­n-s­ubject design
indivi­duals receive only one of the possible levels of an experi­mental treatment
 
e.g., subjects are randomly assigned a level of phone use and follow that level of phone use throughout the experiment
within­-su­bject design
every individual receives each of the experi­mental treatments consec­uti­vely, and their responses to each treatment are measured
 
e.g., subjects are assigned consec­utively to zero, low, and high levels of phone use throughout the experi­ment, and the order in which they follow these treatments is randomized
Random­isation
completely randomized design
every subject is assigned to a treatment group at random
randomized block design
subjects are first grouped according to a charac­ter­istic they share, and then randomly assigned to a treatment within those groups
 

Measuring Variables

Dependent Variable
Variable that represents the outcome
Indepe­ndent Variable
Variables you manipulate in order to affect the outcome of an experi­ement
Controlled Variable
Variables that are held constant throughout the experiment
Confou­nding Variable
Variables that hides the true effect of another variable in your experi­ment. This can happen when another variable is closely related to a variable you are interested in, but you have not controlled it in your experiment
Latent Variable
Variables that cannot be directly measured, but that you represent via a proxy
Composite Variable
Variables that are made by combining multiple variables in an experi­ment. These variables are created when you analyze date, not when you measure it
Quanti­tative Variables
Discre­te/­integer Variable
counts of individual items or values
Contin­uou­s/ratio Variable
measur­ements of continuous or non-finite values
Categorial Variables
Binary­/di­cho­tomous Variable
Yes / No Outcome
Nominal Variable
groups with no rank or order between them
Ordinal Variables
groups that are ranked in a specific order