| what are measures of dispersion | range, variance, standard deviation, |
| Ethical issues | -Consent (informed/presumptive)
- Confidentiality
- Withdrawal
-Protection
-Debrief
-Deception |
| Data analysis | - Quantitative ( numerical, compare)
-Qualitative (words rich in detail)
-primary ( you)
-secondary (pre-existing) |
| Sampling methods | -Random (s= all target pop = equal chance w= withdrawal)
-Opportunity (s=quick + convenient w= biased - generalise results)
- Selfselected/ Volunteer( s= small chance of withdrawal w=not likely to be representative )
-Snowball (S= easy to find ppts W= unrepresentative) |
| Self report methods | - Questionnaires ( s= quick and cost efficient , w= misinterpretation)
- Interviews ( s= build a relationship - honesty w= prejudices , interpersonal variables ) |
| types of questions in a questionnaire | - Open(s= qual so valid/rich info w=comparison)
- closed (quan so comparison w= validity/reflection)
- rating scale (quan/analyse w= central t bias)
-Likert scale (same as ^^)
- Semantic differential scale ( s= insightful w= interpretation and ct bias) |
| Types of interviews | - structured( set questions, pre determined order )
- semi structured ( set questions with follow up q's)
- unstructured (clear but no set questions , talk freely) |
| Types of data measurements | - Nominal ( discrete categories ( eye colour)
-Ordinal ( values that can't be ordered - rating scale)
- Interval ( equal intervals - marks ) |
| What is the independent variable? | you manipulate it - the conditions |
| What is the dependent variable ? | The behaviour your measuring |
| What is the extraneous variable? | Other variables that affect the DV |
| How do you operationalise a variable? | quantifying / measuring the dv - iv = groups |
| Types of extraneous variables and how to control them | Participant variable - sampling (random/ snowballing)
- experimental (matched/repeated measures )
-Situational variable - standardised approach / same
-Experimenter variable -randomisation and double blind |
| State the experimental hypothesis | - There will be a significant difference in (DV) between (IV1 and ( IV2) |
| Difference between one tailed and two tailed | One tailed = direction Two tailed = no direction null = no difference |
| Types of experimental method | - Lab - carefully controlled s= manipulate iv w= deception
-Field - natural environment s= eco valid w= hard to control ev's
-Quasi - pre existing s= iv natural occurs w= can't replicate |
| Types of experimental design | - Independent measures (2 groups compared)
-s= no demand c's or order effects w=participant variables / twice as many pptts
- Repeated measures (induvial compared from one condition to the other)
- s=participant variables removed w=demand characteristics/order effects
- Matched pair design ( matched characteristics to the other group )
-s= no order effects/ ppts variables reduced w= difficult/ time consuming |
| Types of of observational methods | - Participant
- Non participant
- Structured
-Un structured
-Naturalistic
-Controlled
-Covert
-Overt |
| Observational methods | - Time sampling ( set intervals / time to record/ not all behaviours will be recorded)
-Event sampling ( every time it occurs / inter-rater reliability/ hard to record all behaviours at once) |
| questions to remember to see if something is reliable | -same thing ?
- standardised ?
- fair ?
- consistency ? |
| Validity questions to ask your self | -genuine ?
- accuracy ?
-internal - intend to measure ?
- external - generalise findings to other things ? |
| Types of internal validity | - Face validity ( face value)
- Criterion validity ( predictive)
-Concurrent validity ( same scores/data)
- Construct validity ( measures the actual things ) |
| Types of external validity | -Ecological validity (generalise to settings/places)
-Population validity ( representative ) |
| Format to structure answers | P. oint
E. xplain
C. ontext |
| Correlation Methods | relationship between two variables |
| Correlation scale | -1 to -0.5 = strong n
-0.5 to 0 = weak n
o to 0.5 = weak p
0.5 to 1= strong p |
| For a 15 marker what is the structure | How would you implement + context
justify why + context (strenghs)
Own experience |
| what is a type 1 error | false positive incorrectly rejecting the null |
| what is a type 2 error | false negative incorectly accepting the null |
| central tendency measures | mean
mode
median |
| what are measures of dispersion | range, variance, standard deviation, |
| When it asks for conclusions what does it mean | the conlcusions from the findings |
| What is a non parametric test | Doesn’t fit a normal population
Equal variance
Interval data |
| Is a negative skew to the right or left | Right |
| A positive skew to the right or left | Left |
| Respect | Informed consent
Confidentiality
Withdrawal |
| Integrity | Deception |
| Responsibility | Protection of participants
Debrief |
| Competence | Awareness of professional ethics
Stay within your field |
| Induction | The theory creates a test like to prove it |
| Deduction | The testing makes a theory |
