RESEARCH METHODS

Question 1

Aim

Answer 1

The aim is a statement outlining the purpose of the investigation. It can range in length from a single sentence to a short paragraph and should be expressed as clearly and precisely as possible. Some examples of appropriate research aims are:

• The aim of this investigation is to compare differences in the amount of sleep obtained by adolescents and very old people
• The aim of this experiment is to assess the effects of practice on learning
• To examine the effects of acronyms on recall

Question 2

Independent Variable (IV)

Answer 2

The variable in an experiment that is systematically changed or manipulated by the experimenter in order to measure its effect on the dependant variable.

Question 3

Dependant Variable (DV)

Answer 3

The variable in an experiment that is observed or measured and is expected to change as a result of the manipulation of the IV. It DEPENDS on the changes of the IV.

Question 4

Controlled Variables

Answer 4

A controlled variable is one that is considered to have an effect of the Dependent Variable in an experiment so it needs to be held constant (controlled) to remove its potential effects.

A controlled variable is not part of the experiment i.e. it is not relevant to the aim or hypothesis. But it is controlled because it could influence the outcome.

Question 5

Hypothesis

Answer 5

A tentative and testable prediction of the relationship between two or more events or characteristics.

• There are two different types - a RESEARCH Hypothesis which is basic and simply states that one event or characteristic (variable) influences, causes or contributes to a second event or characteristic (another variable).
  Eg. Exercise relieves Depression.
• Or an OPERATIONALISED Hypothesis which is more complex and states EXACTLY how the variables will be measured.

Question 6

Operationalised Hypothesis/Operationalising

Answer 6

Step 1: Operationalise Variables → defining how they will be manipulated of measure in the investigation.

Step 2: Creating a hypothesis:

Exercise relieves Depression.

becomes: 

Teenagers who run 5km each night (IV) will decrease the number of negative words used when writing a creative story (DV) compared to those who do not run.

This shows exactly what will be studied and how in order to test the initial idea, that exercise relieves depression.

Question 7

Hypothesis Template

Answer 7

It is hypothesised that POPULATION who IV (condition 1) will DIRECTION the DV compared to IV (condition 2)

Question 8

Sample

Answer 8

SAMPLE = a group that is a subset or part of a larger group chosen to be studied for research purposes.

Question 9

Population

Answer 9

POPULATION = The term which describes the larger group from which a sample is selected and to which the will seek to apply or generalise the results.

Question 10

Sampling

Answer 10

Sampling is the process by which a subset or part of the population is selected for an investigation. The population of research interest is often referred to as the target population.

Researchers aim to have a representative sample, that is, one that closely represents the population in key characteristics. If it does not it is known as a biased sample.

Question 11

Types of Samples

Answer 11

• Random sampling
• Convenience sampling
• Stratified sampling

Question 12

Convenience sampling

Answer 12

CONVENIENCE SAMPLING (or, Opportunity Sampling):
= Selecting participants who are readily available without any attempt to make the sample representative of a population. Quick, cheap, simple but cannot be generalised to a wider population. Often used as a pilot or a test study.

Eg. use of other students at the school, or the first people you come across who meet your requirements.

Question 13

Random sampling

Answer 13

RANDOM SAMPLING
= A procedure of selection that ensures each member of the population has an equal chance of being selected. Eg. Using electoral roll, names out of a hat etc.

Advantages:
- It helps ensure a highly representative sample, allowing for greater confidence in generalisations (however this is not always guaranteed.

Limitation:
- It can only truly be carried out if a complete list of the target population is available.

Question 14

Stratified sampling

Answer 14

STRATIFIED SAMPLING
= Involves dividing the population into subgroups or strata, then selecting a separate sample from each strata in the same proportions as they occur in the target population.

Question 15

Random allocation

Answer 15

RANDOM ALLOCATION:
= Participants have as much likelihood of being in one group as they do another.
Random allocation can be achieved by flipping a coin, drawing names out of a hat etc.

By doing this, the researcher can be more confident to say that any change in behaviour/thoughts at the end of the experiment is as a result of the independent variable.

Question 16

Control group

Answer 16

CONTROL GROUP
= exposed to the condition where the independent variable is absent. Provides a baseline for comparison.

Question 17

Experimental group

Answer 17

EXPERIMENTAL GROUP
= exposed to the condition where the independent variable under investigation is present.

Question 18

Controlled Experimental Designs

Answer 18

• Between Subjects
• Within Subjects
• Mixed Design

Question 19

Between Subjects Design

Answer 19

(previously called Independent Groups)
= where each participant is randomly allocated to one of two or more entirely separate groups.

Advantages:
- Can usually be completed at one time
- No order effects

Limitations:
- Less control over participant variables
- Larger sample needed

Question 20

Within Subjects Design

Answer 20

(previously Repeated Measures)
= a design that uses the same participants in both the experimental and control groups (or conditions). That is, the same group is used a number of times.

Advantages:
- Control of participant variables
- Smaller sample can be used

Disadvantages:
- Order effects
- Participant expectations
- Higher drop-out rates
- More time consuming

Question 21

Mixed design

Answer 21

Combines features of both a between subjects design and a within subjects design. This means that the researcher can assess the potential differences between two or more separate groups of participants (i.e. between subjects) as well as change in the individual members of each group over time (i.e. within subjects).

The main advantage of the mixed design is that the researcher can capitalise on the strengths of the between subjects and within subjects designs.
- Fewer participants are needed for the experiment and there is greater sensitivity in the results; that is, they tend to be more precise and detailed.

Question 22

Non-Experimental Studies

Answer 22

• Correlation Studies
• Self-Reports
• Observational Studies/Fieldwork
• Case Studies
• Simulation Studies

Question 23

Correlational Study

Answer 23

A correlational study is used to investigate the relationship that exists between variables without any control over the setting in which the relationship occurs or any manipulation by the researcher. There are no IVs or DVs, or control groups, nor can the researcher randomly assign participants to different conditions. The researcher merely measures the relationship between the variables of interest with no intervention.

• A positive correlation means that two variables change (‘vary’) in the same direction — as one variable increases, the other variable tends to increase (and vice versa).
• A negative correlation means that two variables change in opposite directions — as one variable increases, the other variable tends to decrease (and vice versa). As BAC increases, reaction time decreases.
• A zero correlation means that there is no relationship between two variables. For example, there is no relationship between the amount of coffee drunk and VCE grades.

Question 24

Strengths and limitations of Correlational Study

Answer 24

STRENGTHS:
- Used to test hypotheses in cases where it is not desirable or possible to experimentally manipulate the IV of interest.
- Suitable alternative when an experiment is inappropriate for ethical reasons or impractical.
- Useful for discovering relationships between variables, even if not causal. In particular, they can identify variables that are more or less important or worthwhile for further study and investigation.

LIMITATIONS:
- Do not permit the researcher to draw firm conclusions about cause-and-effect relationships.
- Difficult or impossible to control unwanted variables, such as a third variable (or others) that may offer a possible alternative explanation.

Question 25

Self Reports

Answer 25

Interviews, Questionnaires, Focus Groups

A self-report is a participant’s answers to questions presented by the researcher. For example, a self-report may be responses to questions about their beliefs or attitudes, feelings when experiencing certain emotions.

• Interviews (Structured, Unstructured, Semi-Structured): involves questions that are asked by the researcher with the intention of prompting and obtaining specific information from an individual participant (
• Questionnaires: a written set of questions or other prompts designed to draw out self-report information from participants on a topic of research interest. Questionnaires will often use Likert/Ranking Scales.
• Focus Groups: a small set of people who share characteristics and are selected to discuss a topic of which they have personal experience. A leader conducts the discussion and keeps it on target while also encouraging free- flowing, open-ended debate

Question 26

Strengths and limitations of Self Reports

Answer 26

STRENGTHS:
- Useful techniques for collecting any type of data on how people think, feel and behave (especially ones that cannot be observed)
- Good for collecting data from a large amount of people
- Cost effective
- Easy to administer
- Good for sensitive/controversial topics

LIMITATIONS:
- Bias
- Social Desirability effect: Giving false or misleading answers to create a favourable impression
- Non-response bias (sampling bias)
- Language dependant: can make responses difficult for children, ESL, intellectual disability

Question 27

Observational Study

Answer 27

An observational study involves collection of data by carefully watching and recording behaviour as it occurs without any intervention or manipulation of the behaviour being observed.

Environment:
1. Naturalistic study: in a natural environment with no manipulation.
2. Contrived study: researcher sets up a controlled environment with the purpose of conducting observations.

Role of Experimenter:
1. Participant observation: joining in with the participants (this can be known or unknown)
2. Non-participant observation: researcher conceals their presence by watching from the sidelines

Question 28

Strengths and limitations of an Observational Study.

Answer 28

STRENGTHS:
- Researchers can watch and record spontaneous, everyday behaviour without the need for any manipulation or intervention
- Does not require the co-operation of participants being observed. However, this raises the ethical issue of not obtaining informed consent, particularly if participant observation is required.

LIMITATIONS:
- Cannot be used to determine the cause of a behaviour
- Often lack a representative sample
- Observer bias: researchers sometimes unconsciously distort what they see so that it resembles what they hope to see

Question 29

Case study

Answer 29

A case study is an intensive, in-depth investigation of some behaviour, activity, event or problem of interest in a single individual, group, organisation or situation. In psychology, the ‘case’ that is the subject of ‘study’ is usually a person. It may involve any type of behaviour and/or mental process, over a short period of time or even many years.

Question 30

Strengths and Limitations of a Case Study

Answer 30

STRENGTHS:
- In-depth investigation
- Involve a single individual, group, event etc.
- Multiple types of data are usually collected
- Allow for detailed/intensive analysis

LIMITATIONS:
- Non-experimental method/cannot establish cause-effect
- Limited in the extent to which findings may be generalised

Question 31

Simulation Study

Answer 31

Simulation studies involve reproducing situations of research interest in a realistic way to investigate the behaviour and/or mental processes of individuals in that environment.

Example: Stanford Prison Experiment, participants were randomly assigned to play the role of a prisoner or guard in a mock prison.

Question 32

Strengths and Limitations of a Simulation Study

Answer 32

STRENGTHS:
- Access to environments which cannot be easily accessed/are unavailable in the real world
- Conduct experiments that would not be ethically permissible in the real world
- Potentially valuable source of hypotheses for further research or for data to support or challenge a theory
- Greater experimental control
- Wider range of data may be collected relatively easily, especially when digital technology is used e.g. simulator, VR
- Can be a time- and cost-effective alternative to a standard lab or field experiment

LIMITATIONS:
- Artificial environment so may lack realism
- Participants know that the environment they are in is fake so they may behave differently than they would in that situation in reality
- Generalisations very limited

Question 33

Extraneous Variables

Answer 33

Extraneous Variables:(an umbrella term)
= any variable other than the IV that can cause a change in the DV and therefore affect the results of the experiment. We try to account for these when planning our experiment. Eg. Try to make room quiet to avoid noise interference etc.

Question 34

Confounding Variables

Answer 34

A type of Extraneous Variable is a:
Confounding Variables: (CONcrete)
= any variable other than the IV that has an unwanted effect on the dependant variable , making it impossible to determine which of the variables produces the change in the DV.

No conclusions can be drawn – experiment is void and needs to be redone.
These are MEASURABLE and we KNOW they happened.

Question 35

Extraneous variables = Identifying and planning for possible Extraneous and Confounding Variables…

Answer 35

To avoid….
1. Individual Participant Differences
2. Placebo effects
3. Experimenter Effect/Bias
4. Situational Variables/Order Effects
5. Demand Characteristics

We can…
1. Consider participant selection and allocation
2. Use a placebo treatment
3. Use single/double/triple blind measures
4. Use Counterbalancing
5. Deception, blind procedures, placebos

Question 36

Participant differences = Identifying and planning for possible Extraneous and Confounding Variables…

Answer 36

To avoid…
Individual Participant Differences
= the differences in personal characteristics and experiences of the individual participants in an experiment; also called participant variables.

We can use…
Careful Participant Selection and Allocation
= Use of a random or stratified sampling measures to ensure representative samples that are non-biased.
- Use of random allocation to groups is also important.
- Appropriate design choices

Question 37

Situational Factors = Identifying possible Extraneous and Confounding Variables…

Answer 37

TO AVOID…
Situational factors
= associated with the experimental setting that may influence participant responses and therefore the results.
i.e. size of room, lighting, background noise, time of day, non standardised procedures/instructions

Order Effects
= Practice effects, fatigue effects, carryover effects

WE CAN USE…
Consistency
= All participants in different groups or conditions must be tested in the same way and same situation.

Counterbalancing
= Changing the order of treatment or tasks

Question 38

Placebo Effects = Identifying and planning for possible Extraneous and Confounding Variables…

Answer 38

To avoid…
Placebo Effects
= When a participant’s response is changed by their belief that they are receiving some sort of treatment.

We can use…
Placebos
= a fake treatment which provides a baseline to compare experimental groups results against. This removes the issue of expectation as each participant has equal expectation.

Question 39

Experimenter Effects = Identifying and planning for possible Extraneous and Confounding Variables…

Answer 39

To avoid…
Experimenter Effect
=The change in a participants response because of the experimenters expectations, biases or actions rather than the effect of the independent variable.

We can…
Single Blind Procedures
= a procedure in an experiment to ensure participants are not aware of the group (or condition) they are been allocated to (either placebo or experimental). This stops expectations impacting results.

Double Blind Procedures
= the participants and the researcher directly involved are unaware of the conditions to which the participants have been allocated. Prevents participant and experimenter bias.

Triple Blind Procedures
=participants, researchers and assistants doing data analysis all unaware

Question 40

Demand Characteristics = Identifying possible Extraneous and Confounding Variables…

Answer 40

To avoid…
Demand Characteristics
= cues in an experiment that may influence or bias a participant’s response, thereby distorting the results. A cue is some kind of stimulus, event or object that serves to guide behaviour.
i.e. participant may use cues such as random noises, changes in lights to determine the nature of the study and change behaviour.

We can use…
- Deception
- Single Blind Procedure
- Double Blind Procedure
- Appropriate design choice
- Standardised Instructions

Question 41

Data

Answer 41

Primary: collected directly by the researcher

Secondary: collected at an earlier time by someone else

Quantitative: information expressed numerically

Qualitative: information about the characteristics of what is being studied.

Question 42

Objective data

Answer 42

Objective data is information that is observable, measurable, verifiable and free from the personal bias of the researcher.

Question 43

Subjective data

Answer 43

Subjective data is information that is based on personal opinion, interpretation, point of view or judgment.

Question 44

Data Organisation

Answer 44

• Tables
• Bar Charts
• Line Graphs
• Pie Charts
• Scatterplots

Question 45

Scatter plots

Answer 45

A scatter plot shows the scores (or other values) on two different variables measured in a correlational study. The values of one variable are shown on the vertical y axis and the values of the other variable on the horizontal x axis.

• The spread of the dots on a scatter plot gives an idea of the strength of the correlation — the extent to which the two variables are related (or associated). Widely spread dots in the scatter plot suggest that the two variables, have little or no relationship. When dots are closely clustered around each line that represents a strong correlation.
• The direction of the correlation — whether the correlation is positive or negative — is indicated by the slope or ‘lean’ of the dots, that is, whether they slope upwards or downwards (or neither).
• Correlation is expressed on a range from +1 to -1, known as the correlation coefficent. Values below zero express negative correlation. A perfect negative correlation has a coefficient of -1, indicating that an increase in one variable reliably predicts a decrease in the other one.

Question 46

Central Tendency

Answer 46

Data are often summarised by calculating a single numerical score that can be used to describe the data for the whole group(s). This score, called a measure of central tendency, describes the ‘central’ or ‘average’ value of a set of scores.

1. Mean: The average is calculated by adding all the scores together and dividing the total by the number of scores.
   26,17,21,18,12,17,18,24,25,17
   The mean for the group is calculated by adding the scores together (195), then dividing the total by the number of scores (10). The mean is 19.5 seconds.
2. Median: The middle score is calculated by arranging the scores in order of size and select the score that falls in the middle as being typical of the whole set of scores.
   12,12,17,17,17,18,18,21,24,25,26
   18 is the mid-point and therefore Median.
3. Mode: is the most frequently occurring score in a set of scores.
   12,12,17,17,17,18,18,21,24,25,26
   The mode would be 17 because it occurs three times.

Question 47

When to use what

Answer 47

Mean: When most of the scores in a set of data cluster around a central score or value,

Median: When there are extreme scores in the data set

Mode: provides a useful indicator of a ‘common’ or ‘usual’ score because it is the most frequently occurring score.However, the mode can be very misleading because only the most frequent score is used. The mode does not provide any information about the other scores.

Question 48

Standard Deviation

Answer 48

The standard deviation summarises how far scores within a set of scores spread out, or ‘deviate’, from the mean for those scores.

Low standard deviation means data are clustered around the mean, and high standard deviation indicates data are more spread out.

Question 49

Outliers

Answer 49

An outlier is an extreme measurement, one that significantly differs from all others in a data set. They mostly look unusual or out of place, unlike the other scores.

The mean and standard deviation can be pulled severely towards outliers and distort the true results and the validity of the research. Correlations are also sensitive to the effect of outliers.

Question 50

Causes and what to do

Answer 50

Why they may occur?

An outlier is usually due to a random error, a systematic error or a personal error (see next slide)
For example:
- Mistake in calculations
- Sample bias
- Mistake when making an observation
- Use of non-standardised instructions
- A mistake when recording the data
- A naturally occurring unusual but true score

What to do if they occur.
When an outlier is identified a decision must be made as to what to do about it. Three possible actions are to:
- Fix the error that caused the outlier
- Include the outlier in the data
- Exclude the outlier from the data.

Generally, the action will depend on the cause of the outlier and the nature of the research investigation and its data.

Question 51

Measurement Errors

Answer 51

Systematic Errors: eg. sample bias, faulty instruments or using a stopwatch, uncontrolled order effects.

Random Errors: upbringing, memory, personality, mood etc.

Personal Errors: faults made by the researcher.

Question 52

Repeatability and Reproducibility

Answer 52

Repeatability refers to the degree to which a specific research investigation obtains similar results when it is conducted again under the same conditions on all occasions.

Reproducibility refers to how close the results are to each other when an investigation is replicated under changed conditions. Change could be: Observer, tool, procedure, setting, time

• Accuracy: The accuracy of a measurement relates to how close it is to the true value of the quantity being measured. Accuracy is not quantifiable; measurement values may be described as being more accurate or less accurate.
• Precision: Refers to how closely a set of measurement values agree with each other. Precision gives no indication of how close the measurements are to the true value and is therefore a separate consideration to accuracy.

Question 53

Validity

Answer 53

Validity refers to the extent to which a measure (or ‘measurement tool’) accurately measures what it is supposed to be measuring.

Internal validity refers to the extent to which an investigation actually investigated what it set out to investigate and/or claims to have investigated. If an investigation is said to have internal validity, then it is free from flaws and the results obtained are actually due to the design of the investigation and its procedures and not some other factor.

External validity refers to the extent to which the results obtained for a study can be applied beyond the sample that generated them, specifically to individuals in a different setting and over time.

Note that a measure can be reliable even though it is not valid, but a measure cannot be valid unless it is reliable.

Question 54

Conclusion

Answer 54

CONCLUSION = is a decision or judgement about the research results. It is a statement about what has been found about people in general.

Eg. It can be concluded that exercise, in particular running 5km each day, has a positive effect on depression.

Conclusions VS Generalisations - they are different!

Question 55

Generalisation

Answer 55

GENERALISATION = this is when we are able to apply our conclusion to the wider population, beyond the scope of our smaller sample. For this to be true:

The sample is representative of the population.
The method of sampling is appropriate
There have been no confounding variables.

Conclusions VS Generalisations - they are different!

Question 56

Conclusions

Answer 56

Finally, keep in mind that a conclusion based on evidence derived from scientific research is different from ones based on opinion or anecdote.

• An opinion is a point of view that is not necessarily based on verifiable evidence and is disputable. Opinions involve a judgment about a person, object, event and so on that may suggest it is based on at least some data or facts. However, they are vulnerable to change because they are not deeply based on unquestionable or overwhelming evidence.
• An anecdote is an informal verbal report of an event that has been casually observed. Anecdotes tend to be accepted as useful information but are not based on scientific evidence and are therefore considered to be scientifically inadequate.

Question 57

Outline the types of research methods (chart).

Answer 57

Question 58

List the extraneous variables.

Answer 58

Question 59

Outline = How to: Counterbalancing.

Answer 59