|
-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.
|
|
define R problem>
|
Review of literature >
|
formulate H >
|
Design R >
|
collect data >
|
analyse the data >
|
hypothesis testing >
|
|
interpretation of data >
|
preparing report >
|
presenting results
|
||||
|
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 - 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. |
|
journals, books, review articles, abstract, internet, dissertations, professors, newspapers, etc.
|
|
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)
|
||
|
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.
|
|
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) |
||||
|
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
|
|
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 |
|
Primary Data -observation method, interview method, Questionnaires, surveys
|
secondary Data -Case Study, Government Records, Newspapers, Journals, Articles, Archives, Internet , Databases
|
No comments yet.
Cheatography n. The art of mapping complex subjects into clear, instantly navigable reference guides.