Unit 1 AICE Psychology

aims

• what the researcher is interested in finding out

• “to see if”

• “to investigate if”

• to explore the relationship between

hypothesis

• can be tested

• can be proven right or wrong

• must include independent or dependent variable

• measurable variables

self-reports (types of research)

• interviews: structured, unstructured, semi-structured

• questionnaires: open vs closed

• -“who do you most admire?”

• -pick yes it no; which two of three

case studies (types of research)

• detailed information

• allows for research into “unethical” situations

• results can’t necessarily be generalized

• can’t be replicated

experiment

an investigation that allows researchers to look for a casual relationship; an IV is manipulated and is expected to be responsible for change in the DV

lab experiment

a research method in which there is an IV, a DV, and strict controls. it looks for a casual relationship and is conducted in a setting that is not in the usual environment for the participants with regard to the behavior they are performing

field experiment

an investigation looking for a casual relationship in which an IV is manipulated and expected to be responsible for changes in the DV. it is conducted in the normal environment for the participants for the behavior being investigated and some control of variables is possible

self-report

a research method, such as a questionnaire or interview, which obtains data by asking participants to provide information about themselves

questionnaire

self-report research method that uses written questions through a “paper and pencil” or online technique

case study

a research method in which a single instance, ex: one person, family, or institution is studied in detail

longitudinal study

a research method that follow a group of participants over time, weeks, or decades, looking at changes in variables to explore development or changes due to experiences, such as interventions, drugs, or therapies

observation

involves watching human or animal participants

covert observation

the role of the observer is not obvious, ex: they are hidden or disguised

overt observation

the role of the observer is obvious to the participants

independent variables

the factor under investigation in an experiment that is manipulated to create two or more conditions (levels) and is expected to be responsible for change in the DV

dependent variables

the factor is an experiment that is measured and is expected to change under the influence of the IV

independent measures

an experiment design in which a different group of participants is used for each level of the IV (condition)

demand characteristics

features of the experimental situation which give away the aims. they can cause participants to try to change their behavior, for example to match their beliefs about what is supposed to happen, which resides the validity of the study

random allocation

a way to reduce the effect the confounding variables such as individual differences. participants are put in each level of the IV dug that each person has an equal chance of being in any condition

participant variables

individual differences between participants (such as age, personality, and intelligence) that could affect their behavior in a study that would hide or exaggerate differences between levels of the IV

counterbalancing

a way to overcome order effects in a repeated measures design. each possible order of levels of the IV is performed by a different sun-group of participants. this can be described as an ABBA design, as half the participants do condition A then B, and half do B then A

matched pairs design

an experiment design in which participants are arranged into pairs. each pair is similar in ways that are important to the study and one member of each pair performs in a different level/condition of the IV

hypothesis (plural hypotheses)

a testable statement based on the aims of an investigation

non-directional (two-tailed) hypothesis

a statement predicting only that one variable will be related to another, for example that there will be a difference in the DV between the levels of the IV in the experiment (or that there will be a relationship between the measured variables in a correlation)

directional (one-tailed) hypothesis

a statement predicting the direction of a relationship between variables, for example in an experiment whether the levels of the IV will produce an increase or a decrease in the DV (or in a correlation whether an increase in one variable will be linked to an increase or a decrease in another variable)

null hypothesis

a testable statement saying that any difference or correlation in the results is due to chance, that is, that no pattern in the results has arises because of the variables being studied

inter-rater reliability

the extent to which two researchers interpreting qualitative responses in a questionnaire (or interview) will produce the same records from the same raw data

generalisability

how widely findings apply, ex: to other settings and populations

order effect

practice and fatigue effects are the consequences of participating in a study more than once, for example in a repeated measures design. they can cause changed in performance between conditions that are not due to the IV, so can i sure the effect on the DV

repeated measures design

an experimental design in which each participant performs in every level of the IV

subjectivity

the effect of an individual’s personal viewpoint on, for example, how they interpret data. interpretation can differ between individual researchers as a viewpoint may be biased by one’s feelings, beliefs, or experiences, so is not independent of the situation

objectivity

the impact of an unbiased external viewpoint, for example, how data is interpreted. interpretation is not affect d by an individual’s feelings, beliefs, or experiences, so should be consistent between different researchers

correlation

a research method that looks for a relationship between two measured variables. a change in one variable is related to a change in the other (although these changes cannot be assumed to be casual)

situational variables

a confounding variable caused by an aspect of the environment, for example the amount of light or noise

opportunity sample

participants are chosen because they are available, for example university students are selected because they are present at the university where the research is taking place

volunteer(self-selected) sample

participants are invited to participate, for example through advertisements via email or notices. those who reply become the sample

random samples

sampling all members of the population (i.e. possible participants) are allocated numbers and a fixed amount of these are selected in an unbiased way, for example by taking numbers from a hat

quantitative data

numerical results about the amount or quantity of a psychological measure, such as pulse rate or a score on an intelligent test

qualitative data

descriptive, in-depth results indicating the quality of a psychological characteristic, such as responses to open questions in self-reports or case studies and detailed observations

correlation coefficients

a measure of the deviation of the responses from this regression line

operationalization

definition of variables so that they can be accurately manipulated, or quantified and replicated. this includes the IV and DV in experiments and the two measures variables in correlations

extraneous variables

either acts randomly, affecting the DV in all levels of the IV or systematically, i.e. on one level of the IV (called a confounding variable) so can obscure the effect of the IV, making the results difficult to interpret

ecological validity

extent to which findings of research in one situation would generalize to other situations. influenced by whether the situation, such as a lab, represent the the real world effectively and whether the task is relevant to real life (has mundane realism)

inter-observational reliability

consistently between two researchers watching the same event, i.e. whether they will produce the same records

test-retest reliability

measures consistency. used twice (if participants’ two sets of scores are similar, it has good reliability)

snowball sample

a way of finding a large number of people so that you can get and study their opinions about something, by finding a few and then asking them to find others

content validity

extent to which the researcher is testing what they claim to be testing (accuracy)

longitudinal study (types of research)

• studies done over long period of times

• -tuskegee syphilis study (1932-1972)

• uses cohorts: groups that are studied together as time progresses

• -lots over very specific data

• -external variables are fairly easy to identify

• -sample attrition (people pass away or leave the study

observations (types of research)

• hand washing study

• -when interviews, approximately 75% of all men say YES, i wash my hands every time i use a public restroom

• -observation results? 35%

• overt vs. covert

• -overt means you know you’re being watched

• -covert means you don’t know you’re being watched

• -covert must remain unobtrusive (observers can’t interfere)

• -overt sometimes requires blind(or masked) design - participants don’t know what they’re being observed for

• -participant vs. non-participant

• clear operationalization helps minimize observer bias and expectancy (clearly define what you’re looking for)

correlations (types of research)

• positive

• - +1 (perfect)

• negative

• - -1 (negative)

• no correlation

• - 0 (no correlation)

• correlation does not equal causation

• directionality? (not being able to tell which variable comes first)

• third variables? (ex: violent crimes and ice cream, third variable = hot weather)

experiments (types of research)

• two kinds: lab and field

• -in a lab you can hope to control everything

• -field is good for complex questions about attitude or behavior

• → ex: why do people vote the way they do?

• → bias and discrimination

• -used to determine cause-and-effect relationships

• how does the IV affect the DV?

• DV is at the end of the hypothesis

• hypothesis is a testable statement that should be falsifiable (can be proven wrong)

• directional vs. non-directional: is the effect(DV) defined/predicted?

• sometimes called “one-tailed” or “two-tailed”

other variables

• uncontrolled variables: not regulated by the investigator, so not the same for all participants

• extraneous variables: affect the outcome (DV)

• situational variables: environment; can’t necessarily be controlled, but con be accounted for

• participant variables: differences between participants, known or unknown

• demand characteristics: giving the "right" answers, or giving answers that make you seem better/more socially acceptable

• single-blind vs. double-blind studies

• confounding variables: are not taken into consideration before beginning the experiment - could there be something else that is the cause in the relationship?

• -affect the IV and the DV

experimental design

• experimental condition vs control condition

• -what we’re looking for vs. what is “normal”

• → controls are used for baseline data

controlling variables

• independent measures: participants are only used once in experimental groups

• -random allocation is necessary

• *random allocation ≠ random sample

• repeated measures: participants are part of each group at some point during the study

• -counterbalancing will be needed to help eliminate order effects (ABBA design)

• matched pair design: researchers find pairs of participants who are similar - one gets experimental treatment, one gets control treatment.

• -used when participant variables are expected to have great impact

independent measures (experimental design)

• strengths:

• no order effects

• participants see only one level of IV, reducing demand characteristics

• random allocation can reduce effects of individual differences

• weaknesses:

• participant variables can distort results

• more participants are needed than in repeated measures

repeated measures (experimental design)

• strengths:

• participant variables unlikely to distort effects of IV

• counter balancing reduces order effects

• uses fewer participants

• weaknesses:

• order effects could distort the results

• participants see the experimental task more than once; they may have greater exposure to demand characteristics

matched pairs (experimental design)

• strengths:

• participants see only 1 level of the IV, reducing demand characteristics

• participant variables less likely to distort the effects of the IV

• no order effects

• weaknesses:

• similarity is limited by the matching process

• availability of matched pairs may be limited, making the sample size small

population and sample

• population is who what group you want to study as a whole (high schoolers, north americans, women ,people over 5'6"...)

• sample: the group you actually study

• -random sample

• opportunity sample

• volunteer (self-selecting)

• → snowball

opportunity sampling (sampling techniques)

• strengths:

• quicker and easier so larger sample can be readily obtained

• weaknesses:

• non-representative as the variety of people available is to be limited

• sample could be biased

volunteering sample (sampling techniques)

• strengths:

• easy because the participants come to the researcher likely to be committed and return if needed for repeat testing

• weaknesses:

• likely to be non-representative as people who respond may be similar (all have free time)

random sampling (sampling techniques)

• strengths:

• likely to be representative as all types of people in the population are equally likely to be chosen

• the larger your sample, the more random the sample could be

• weaknesses:

• in reality, everyone may not be equally chosen (incomplete list), one type of participant happens to be selected (all girls), sample is small

data collection

1. quantitative data: numeral data

2. qualitative data: descriptive, in-depth

quantitative (data collection)

• strengths:

• typically uses objective measures

• scales/questions often very reliable

• data con be analyzed using measures of central tendency and spread making it easy to compare

• weaknesses:

• data collection method often limits responses (what if a participant wants to give an answer that is not an option?)

qualitative (data collection)

• strengths:

• data is often valid as participants can express themselves exactly rather than being limited by fixed choices

• important but unusual answers are less likely to be ignored (outliers) because of averaging

• weaknesses:

• data is relatively subjective, so recording or interpretation may be biased by opinions or feelings, making it less valid

• if detailed data can only be gathered from a few individuals it may not be generalizable

validity

• what makes data valid?

• -content validity: is it measures what it claims to measure?

• → how accurately has a researcher operationalized variables?

• -ecological validity: how well does a lab reflect real life?

• → stress in a lab = stress at home = stress in the medical profession?

• -generalizability: is the sample representative? is the sample too small?

• -replicability

reliability

• are the results of the study consistent?

• -test-retest procedure: should be high correlation between results

• -interpretations of data may be subjective

• → inter-rater and intra-rater reliability: are multiple raters consistent, and is a single rater consistent

• → inter-observer and intra-observer reliability

stats for psychology

1. summary tables

2. graphs

   • bar chart: measures multiple things (ex: baseball, soccer…)

   • histogram: measures only one thing (ex: height)

3. measures of central tendency

   • mean (most informative measure of central tendency)

   • median (helpful when there are a smaller number of outliers; however it also doesn't really take those outliers into effect)

   • mode (only measure of central tendency that can be used in data with discrete categories)

4. measures of spread

   • measures of central tendency describe the data itself, while measures of spread describe variation

   • range (does not necessarily reflect outliers, but is heavily influenced by them)

   • standard deviation (tells us how consistent (or inconsistent) the data is)

ethics

• British ethical standards are set by British Psychological Society Code of Ethics and Conduct (2018) - in US, it’s the American Psychological Association

• two sets: Human Participants and Animal Participants

• Animals:

• -replacement

• -species

• -number of animals

• -procedures.

  • pain, suffering, and distress

  • reward deprivation, and averse stimuli

• Humans:

• -protection from harm

• -valid (informed) consent

• -right to withdraw

• -lack of deception.

• -confidentiality

• -privacy

• debriefing (tell subjects results)