As Psychology - Research Methods

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RESEARCH METHODS IN PSYCHOLOGHY include;

1. Correlation

2. Experiments

3. Sampling questionnaires and interviews

4. Questionnaires and interviews

5. Observations

6. Hypothesis

7. Additinal info

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1. CORRELATION

Correlation is a statistical technique used to quantify the strength of relationship between two variables.

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Strengths;

~ Calculating the strength of a relationship between variables.
~ Useful as a pointer for further, more detailed research.

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Weaknesses:

~ Cannot assume cause and effect, strong correlation between variables may be misleading.
~ Lack of correlation may not mean there is no relationship, it could be non-linear.

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Data can be plotted as points on a scattergraph. A line of best fit is then drawn through the points to show the trend of the data.

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If both variables increase together, this is a positive correlation

If one variable increases as other decreases this is a negative correlation

If no line of best fit can be drawn, there is no correlation

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Independent variable (IV): Variable the experimenter manipulates - assumed to have a direct effect on the dependent variable.

Dependent variable (DV): Variable the experimenter measures, after making changes to the IV which are assumed to affect the DV.

Extraneous variables (Ex Vs): Other variables, apart from the IV, that might affect the DV. They might be important enough to provide alternative explanations for the effects, for example, confounding variables.

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2. EXPERIMENTS:

Laboratory experiment:

Artificial environment with tight controls over variables.

Strengths:

~ Tighter control of variables and easier to comment on cause and effect.

~ Relatively easy to replicate.
~ Often cheaper and less time-consuming than other methods.

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Weaknesses:

~ Demand characteristics - participants aware of experiment, may change behaviour.
~ Artificial environment - low realism.

~ May have low ecological validity - difficult to generalise to other situations.

~Experimenter effects - bias when experimenter's expectations affect behaviour.

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Field experiment:

natural environment with independent variable manipulated by researchers.

Strengths:People may behave more naturally than in laboratory - higher realism.Easier to generalise from results.

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Weaknesses:
Often only weak control of extraneous variables - difficult to replicate.
Can be time-consuming and costly.

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Natural experiment:

Natural changes in independent variable are used - it is not manipulated.

Strengths:

Situations in which it would be ethically unacceptable to manipulate the independent variable.Less chance of demand characteristics or experimenter bias interfering.

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Weaknesseses:

~ The independent variable is not controlled by the experimenter.
~ No control over the allocation of participants to groups (random in a 'true experiment').

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Experimental designs;

Independent groups: Testing separate groups of people, each group is tested in a different condition. Avoids order effects. If a person is involved in several tests they man become bored, tired and fed up by the time they come to the second test, or becoming wise to the requirements of the experiment. Differences between participants in the groups may affect results, for example; variations in age, sex or social background. These differences are known as participant variables.

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Repeated measures:

Testing the same group of people in different conditions, the same people are used repeatedly. Avoids the problem of participant variables.Fewer people are needed.

Order effects are more likely to occur.

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Matched pairs: Testing separate groups of people - each member of one group is same age, sex, or social background as a member of the other group.

Reduces participant variables. Avoids order effects. Very time-consuming trying to find closely matched pairs. impossible to match people exactly, unless identical twins

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3. SAMPLING

Random sampling: Everyone in the entire target population has an equal chance of being selected.

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Opportunity sampling: Uses people from target population available at the time.

Systematic sampling: Chooses subjects in a systematic way. For example, every 10th person from a list or register.

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Self-selected sample: Participants volunteer. For example, by answering an advert.

Stratified sampling: Divides target population into groups, people in sample from each group in same proportions as population. So you would have a higher number of people between the ages of 20-30 than 70-80.

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4. QUESTIONAIRES AND INTERVIEWS (self-report):

Questionnaires (surveys) can use closed questions (fixed choice of answers), to generate data for easy analysis.

Open questions (space to write any answer) for more detailed individual answers.

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Strengths:

~ can test people easily and quickly. It is easy to generate quantitative data + easy to analyse.

~ Used to collect large amounts of data

~ Convenient - researcher does not need to be present, answers can be mailed so respondent has time to consider answers.

~ Can quickly show changes in attitudes or behaviour before and after specific events.

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Weaknesses:
~ Social desirability - people say what they think looks good not truth.People may not tell the truth, especially on sensitive issues, for example, sexual behaviour.

~ If researcher is present then this may affect answers. Also, postal surveys have low response rate.

~ Difficult to phrase questions clearly, you may obtain different interpretations of questions.

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INTERVIEWS

Interviews are face-to-face conversations, these can be unstructured, informal chats, or they can be formal, structured interviews with pre-determined questions.

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Strengths:

~ Detailed information can be obtained and avoids oversimplifying complex issues.

~ Greater attention to individual's point of view.
~ Unstructured, casual interviews may encourage openness in answers.

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Weaknesses:

~ Difficult to analyse if unstructured and qualitative in nature.

~ Time-consuming, expensive.

~ Possible interviewer effects. For example, people may build good relationship of the interviewer.

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Quantitative research:

Gathers data in numerical form and is concerned with making 'scientific' measurements. Quantitative data analysis uses a barrage of inferential statistical tests.

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Qualitative research:

Gathers information that is not in numerical form. For example, diary accounts, open-ended questionnaires, unstructured interviews and unstructured observations.

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5. OBSERVATIONS

Structured observation: Uses tables of pre-determined categories of behaviour and systematic sampling.

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Sampling in structured observations:

Time sampling: Observations may be made at regular time intervals and coded.

Event sampling: Keep a tally chart of each time a type of behaviour occurs.

Point sampling: Focus on one individual at a time for set period of time.

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Unstructured observations:

Record everything that happens. It may be difficult to avoid bias by focusing on what you want or expect to see happening, in theory all observations are noted as anything could prove to be important.

Video recording: This is useful as behaviour may be analysed in more detail later.

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Strengths:

~ More natural behaviour occurs if people are unaware of observation.

~ Studying of animals that cannot be observed in captivity.
~ Study of situations that cannot be artificially set up.

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Weaknesses:

~ Observer may affect behaviour if detected.
~ Difficult to replicate - cannot control extraneous variables.
~ Need for more than one observer.

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Hypothesis:

A supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation. There is a null hypothesis and an alternative hypothesis.

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A 'null hypothesis' (Ho) prediction is one that states results are due to chance and are not significant in terms of supporting the idea being investigated

For example, there was no significant difference between and as measured by unless due to chance.

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A alternative hypothesis states that there is a relationship between the two variables being studied.

For example, there was a significant difference between and as measure by and not due to chance.

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One-tailed directional hypothesis which predicts the nature of the effect of the independent variable on the dependent variable.

• E.g.: Adults will correctly recall more words

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A two-tailed non-directional hypothesis predicts that the independent variable will have an effect on the dependent variable, but the direction of the effect is not specified.

• E.g.: There will be a difference in how many numbers are correctly recalled by children and adults.

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ADDITIONAL INFORMATION;

Pilot study - small scale trial run of an actual experiment, allows experimenter to see flaws of the study.

Subjective - based on opinion, not factual

Objective - factual, based on scientific info

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Measures of central tendency and dispersion-

Central tendency:

Mean - add all them up and divide by amount of numbers

Median - arrange in order of number high to low then middle number

Mode - most freq occurring number

Dispersion;Range - highest score and lowest score