- Created by: BreeFRANCiiS
- Created on: 13-04-17 11:55
Aims - The purpose of the investigation.
Hypotheses - The formulation of a testable statement.
Directional or non-directional - Identifying a difference/correlation or not. One-tailed and two-tailed predictions.
IVs and DVs - IV is manipulated, DV is measured.
Levels of the IV - Experimental and control conditions.
Operationalisation - 'De-fuzzing' variables.
Control of Variables
Extraneous variables - Nuisance variables but randomly distributed.
Confounding variables - Vary systematically with the IV.
Demand characteristics - Participants second guess the aims and alter their behaviour.
Investigator effects - The unconscious influence of the research on the research situation.
Randomisation - The use of chance to reduce the researcher's influence.
Standardisation - Ensuring all participants are subject to the same experiment.
Independent Groups - Particpants in each condition of an experiment are different.
Repeated Measures - All participants take part in all conditions.
Matched Pairs - Similar participants put in pairs and allocated to different experimental conditions.
Inderpendent groups - Less economical. No order effect. Participant variables not controlled.
Repeated measures - Order effects. Demand characteristics. No participant variable problems. More economical.
Matched Pairs - No order effects. Cannot match participants exactly. Time-consuming.
Types of Experiments
Lab experiments - IV is manipulated in a controlled setting.
Field experiments - IV is manipulated in a natural setting.
Natural experiments - IV has been manipulated naturally, effect on DV is recorded.
Quasi-experiments - IV based on an existing difference between people, effect on DV is recorded.
Lab experiments - High internal validity (control). Low external validity (low realism). Cause and effect. Replication. Demand characteristics.
Field experiments - Lower internal validity. Higher external validity (realism). Ethical issuses.
Natural experiment - Low internal validity (no random allocation). High external validity. Unique research. Opportunites may be rare.
Quasi-experiments - Low internal validity (no random allocation). High external validity.
Random sampling - All members of the population have an equal chance of selection.
Systematic sampling - Selecting every nth person of a group.
Stratified sampling - Sample reflects the proportion of people within different population strata.
Opportunity sampling - Choosing whoever is available.
Volunteer sampling - Participants 'self-select'.
Random sampling - No researcher bias. Time-consuming. May end up with bias sample.
Systematic sampling - No researcher bias. Usually fairly representative. May end up with bias sample.
Stratified sampling - No researcher bias. Representative. Cannot account for all sub-groups.
Opportunity sampling - Convenient. Researher bias. Unrepresentative.
Volunteer sampling - Less time-consuming. Attracts a certain profile profile of people.
Ethical Issues & Ways Of Dealing With Them
Confidentiality - Protecting private personal data.
Deception - Telling the truth.
Consent - Advising participants of what is involved. May reveal research aims.
Debrief - May reveal research aims.
Right to withdraw - Allow participants to leave the research at any given time.
Protction from harm - Minimising psychological and physical risks.
Informed consent - Get permission. Presumptive, prior general, retrospective.
Deception/Protection from harm - Debriefing.
Privacy and confidentiality - Maintaining anonymity. Use numbers not names.
Pilot studies - Checking procedures and materials. Making modifications.
Single blind - Participants aren't made aware of research aims until the end.
Double blind - Neither participants nor the individual conducting the research know the aim beforehand.
Control group/condition - Used as a comparison.
Naturalistic observations - Behaviour observed where it would normally occur. No control over variables.
Controlled observations - Some control over environment, including manipulation of variables to observe effect.
Covert and overt observations - Observing participants with or without their knowledge.
Participant and non-participant - To join the group or remain an outsider.
Naturalistic observations - Low internal validity (control is difficult). High external validity (especially when covert).
Controlled observations - Low internal validity-though some extraneous variables may be controlled. High external validity (especially when covert).
Covert and overt observations - Covert: Low participant reactivity but ethically questionable. Overt: Behaviour may be affected.
Participant and non-participant - Participant: Increased external validity but may 'go native'. Non-participant: More objective but less insight.
Unstructured and structured - Researcher records everything (unstructured) or controls what is recorded (structured).
Behavioural categories - Target behaviours broken down into observable components.
Sampling methods - Continuous. Event sampling: count events. Time sampling: count at timed intervals.
Unstructured and structured - Unstructured: more information but may be too much, qualitative data harder to analyse. Structured: May miss behaviours.
Behavioural categories - Must be observable. Avoid dustbin category. No overlap.
Sampling methods - Event: Useful for infrequent behaviour, may miss complexity. Time: Less effort but may not represent whole behaviour.
Self-Report Techniques: Questionnaries
Questionnaires - Pre-set list of written questions.
Closed and open questions - Fixed number of answers or not.
Questionnaires - Can distribute to many people. Easy to analyse. Social desirability bias. Acquiesence bias.
Closed and open questions - Produces quantitative or qualitative data, affected ease of analysis.
Self-Report Techniques: Interviews
Structured interviews - Pre-set questions in a fixed order.
Unstructured interviews - No set formula, just a general topic. Questions developed based on responses.
Semi-structured interviews - Pre-set questions with flexibility to ask follow ups.
Structured interviews - Similar to questionnaires but fewer respondents.
Unstructured interviews - More flexibility. Analysis is more difficult. Social desiability bias may be reduced by rapport.
Semi-structured interviews - Advantages of both structured and unstructured.
Questionnaires - Likert scale, rating scale, fixed choice option.
Interviews - Standardised interview schedule, to avoid interviewer bias. Awareness of ethical issuses.
Writing good questions
Overuse of jargon - Don't be too technical.
Emotive languages and leding questions - Replace 'loaded' words and phrases with neutral ones.
Double-barrelled question and double negatives - Ask one question only in a clear way.
Types of correlation - Positive, negative and zero.
Difference between correlations and experiments - No IV or DV. No manipulation of variables.
- Useful preliminary tool.
- Quick and economical to carry out, using secondary data.
- Cannot demonstrate cause and effect.
- The third variable problem (interviewing variables).
- Misuse and misinterpretation.
Data Analysis: Kinds of Data - Q&Q Data
Qualitative Data - Written, non-numerical description of the participants' thought, feelings or opinions.
Quantitative Data - Expressed numerically rather than in words.
- Rich in detail.
- Greater external validity.
- Difficult to analyse.
- Conclusions may be subjective.
- Easy to analyse.
- Less biased.
- Narrow in scope.
Data Analysis: Kinds of Data - P&S Data
Primary data - Collected first haand from participants for the purpose of the investigation.
Secondary data - Collected and analysed by someone other than the researcher.
- High validity.
- Targets relevant information.
- Time and effort.
- Inexpensive and easy to access.
- Variation in the quality.
- Outdated and incomplete.
Data Analysis: Descriptive Statistics
Measures of Central Tendency
Mean - Add them all up and divide by the number.
Median - The middle value.
Mode - Most frequently occuring.
Mean - Most sensitive and representative. Easily distorted.
Median - Not affected by extreme values. Less sensitive than the mean.
Mode - Easy to calculate. Crude, unrepresentative.
Data Analysis: Descriptive Statistics Pt.2
Measures of Dispresion
Range - Subtract the lowest from the highest.
Standard Deviation - Measures how many scores deviate from the mean.
- Easy to calculate.
- May be unrepresentative of the data set.
- Much more precise than the range.
- Can be distroted by extreme values.
Data Analysis: Graphs
Presentation and display of Quantitative data
Tables - Raw scores are converted to descriptive statistics and summarised in a table.
Bar charts - Discrete categorical data represented for clear comparison. The frequency of each category is the height of the bar.
Scattergrams - Shows the strength and direction of a relationship between co-variables.
Normal distribution - Bell curve. Mean, median and mode at same point. Tails never touch zero.
Skewed distribution - Negative skew leans right. Positive skew leans left.
Percentages and fractions - Convert one to ther and to decimals.
Decimals - Appropriate number of significant figures.
Ratios - Part-to-whole. Part-to-part.
Mathematical symbols - =,>,<,>>,<<
Funding - Approval of project proposal.
Validation - Quality check.
Improvements - Minor revisions or rejection of report.
Anonymity - May permit unjustified criticisms by rivals.
Publication bias - File drawer problem, creates false impression of current knowledge.
Burying ground-breaking research - Maintains status quo.
Psychology and The Economy
- Equal care from mother and father, means more effective contribution to economy.
- Absenteeism due to moderate mental health (e.g. depression) issuses costs the economy.
Significance - Results have not occured by chance.
Probability - The 5% significance level. The more stringent 1% level.
Critical value - Cpm[arison with calculated value to determine significance.
The Sign Test
- Testing for difference.
- Nominal data.
- Repeated Measures.
- Convert to nominal data.
- Add up pluses and minuses.
- S=Less frequent sign.
- Compare calculated value of S with critical value.