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Basic Research Methods Cheat Sheet (DRAFT) by

basic research methods in experimental psychology

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

Experi­mental Psychology

the branch of psychology concerned with the scientific invest­igation of basic psycho­logical processes such as learning, memory, and cognition in humans and animals.
- in a controlled setting in order to predict, explain, or influence behavior or other psycho­logical phenomena
- aims at establ­ishing quantified relati­onships and explan­atory theory through the analysis of responses under various controlled conditions

scientific Research

-a systematic and object­ive­attempt to provide answers to certain questions or problems , develop and discover an organised body ofstudy.
a systematic method consisting of enunci­ating the problem, formul­ating a hypoth­esis, collecting facts or data, analysing the facts and reaching certain conclu­sions either in solution form of genera­lis­ation for some theore­tical inform­ation.

Research Process

define R proble­m>
Review of literature >
formulate H >
Design R >
collect data >
analyse the data >
hypothesis testing >
interp­ret­ation of data >
preparing report >
presenting results

Types of Research

Descri­ptive - survey and fact finding enquir­ies.De­scribe the current state of affairs. ex Ex-post facto R
Analytical-analysis of already available inform­ation to make critical evaluation
Action or Applied - aim is finding a solution for a problem at hand
fundam­ental - concerned with genera­lis­ations and formul­ation of a theory.
Quanti­tative - measur­ement of quantity or amount
Qualit­ative - aim is to discover underlying motives of human behavior.
Conceptual - related to some abstract idea or theory. used to develop new theories or reinte­rpret existing ones.
Empirical - relies on observ­ation or experience alone. Data-based research. Alia experi­mental R.
Other - one time OR longit­udinal; field setting OR laboratory R ; Explor­atory R; Historical R.

Hypothesis

Hypothesis - a testable propos­ition; a tentative solution formed on a problem.
Types:
Null Hypothesis (Ho) - indicating no relati­onship or no-effect or negati­onb­etween variables.
Alternate Hypothesis (Ha/ H1) or working hypothesis - indicating some relati­onship between variables.

Sources of ROL

journals, books, review articles, abstract, internet, disser­tat­ions, profes­sors, newspa­pers, etc.

Sampling

Population - population or universe being considered or of interest
Probab­ility sampling likelihood of inclusion of each element in the sample.
Non Probab­ility Sampling- no way of assessing the likelihood of inclusion of each element in sample
Non Probab­ility contd.
mixed sampling - involve charac­ter­istics of prob and non prob sampling
sample - subset of popula­tion, used as repres­ent­ative of popula­tion.
Simple Random sampling -equal chance of being included. Ex. fishbowl method, Tippet's table of Random nos.
Purposive/ Judgem­ental sampling
Area Sampling - selecting a particular geogra­phical location for sample collection
 
Stratified Random sampling - Strata. Ex sex
Snowball sampling
Cluster Sampling - selecting groups rather than indivi­duals
 
Systematic sampling -Tippet's Table.
Quota Sampling - strata
Multistage sampling - + cluster sampling (large sample unit breaking into then smaller units to study)

Sampling Error

the difference between parameter (measure from popula­tionand statis­tic­(me­asure from sample)
Based on A)Vari­ability in the population & B)Size of sample
 
Higher the SE, poorer the statis­tical inference.

Research Design

conceptual structure within which a R is conducted, in Underbuilt for collec­tion, measur­ement and analysis of data; a framework for R plan of action
charac­ter­istics of R Design - Neutral, Reliable, Valid, Genera­lisable
Two Approaches to R Design: Qualit­ative & Quanti­tative
Types of R Designs
Descri­ptive Research Design - explan­ation of situat­ion­/case in depth explan­ation of situat­ion­/case in depth; theore­tical basis; presen­tsdata in an unders­tan­dable manner ; no contro­l/c­hange in variables ; only observ­ati­onal.Do customers prefer product A, B or C ?
Experi­mental R Design- manipu­lation of variable to observe changes in another variable; controlled and random­ized.
Include DV, IV, hypoth­esis, operat­ional definition
Correl­ational R Design - relati­onships between two/more variables ; non experi­mental ; no manipu­lation of variables ; gives a + or - or 0 correl­ation; result presented with numerical value called correl­ation coeffi­cient
Explan­atory R Design - explores when limited inform­ation is available; helps increase unders­tanding of a topic; answers why, how; predicts future occurr­ences; cause and effect model ; improved unders­tanding of previously unresolved problem.
 
Types : cross sectional- studying one particular section of society at a given point in time. ex. tracking social media use in Gen Z in Netherlands.
Longitudinal - extended period of time on a group of people. ex. cyber bullying from 2022-2024
Normative-comparison of result with an existing norm
Correlational- find out relati­onship between variables. Ex video games and mental health
Comparative- Comparison of two or more. Ex salary of emploees at teo different companies
Classification- arrange data into catego­ries. Ex classi­fying customers based on their buying beh
Archival- search for past records and get info. Ex tracking company sales over years
Types:True experimental
pretest posttest design w/o control group
pretest posttest with control group
posttest with control group design , Quasi-­exp­eri­mental
Types: Natura­listic observ­ation
Survey
Archival Research
   
Between subjects design­(se­parate groups­)-R­and­omised groups design:
Two randomised groups design
More than two randomized groups design
   
Matched group design-all subjects are tested on a matching variable sn then formed into groups
Factorial design­-values of two/more IV are studies in all possible combin­ations to find out indepe­ndent and intera­ctive effects on DV
Within subjects design (only one group of subjects)

Variables

Attributes of objects, events, things, being, etc that can be measured. There are contro­lled, manipu­lated or observed by the experi­menter.
IV-man­ipu­lat­ed,­mea­sured and selected by experi­mental for purpose of observing changes in DV.
Directive & Non-di­rective hypothesis
DV -exper­imenter makes prediction about this variable

Measur­ement Scales

Nominal scale - use of numbers to name objects.
Ordinal scale - rank order of objects
Interval scale - includes charac of nominal & ordinal scales , numerical equals distance on a scale indicating equal distances in properties of objects measured.
Ratio scale -includes properties of all other scales & an absolute zero point.
Interval scale is most commonly used in psychology

Data Collection sources

Primary Data -obser­vation method, interview method, Questi­onn­aires, surveys
secondary Data -Case Study, Government Records, Newspa­pers, Journals, Articles, Archives, Internet , Databases