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OCR A-Level Psychology > Planning And Conduction Reseach > Flashcards

Flashcards in Planning And Conduction Reseach Deck (59):
1

Research Aims

A statement that broadly points out what the research aims to accomplish and the desired outcomes of the research. It identifies the purpose of the investigation.

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Research Question

A question that asks about what a study intends to investigate.

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Null Hypothesis

Predicts that there will be no difference or no relationship between the variables being studied and the results are due to chance and are not significant in terms of supporting the idea being investigated.

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Alternative Hypotheseis

Predicts that there will be a difference or a relationship between the variables being studied and the results are not due to change but are significant in terms of supporting the idea being investigated.

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One-Tailed Hypothesis

Predicts that nature of the effect of the independent variable will have an effect of the independent variable on the dependent variable or the direction of the relationship.

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Two-Tailed Hypothesis

Predicts that the independent variable will have an effect on the dependent variable will have an effect on the depended variable or that there will be a relationship but the direction of the effect is not specified.

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Target Population

The group of people the researcher is interested in and from which the sample is drawn.

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Random Sampling

The selecting of the participant in the way that each member of the target population has an equal chance of being chosen.

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Snowball Sampling

Relies on initial participants recruiting others to generate additional participants. The sample is unlikely to be representative, though it is an easy way of gathering a sample if specific sample features are required.

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Oppertunity Sampling

Produced by selecting people who are most easily available at the time of the study.

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Self-Selecting / Volunteer Sample

Produced by asking people to volunteer to take part in a study

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Repeated Measures

Each participant takes part in every condition under test.

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Strength of Repeated Measures

Few participants will be needed and individual differences will be controlled as the same participants are used in all conditions.

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Weakness of Repeated Measures

Participants may suffer from boredom, order effects and practice effects. Boredom and order effects tend to result in poorer performance in the second or subsequent conditions and practice effects often lead to improved performance in the second or subsequent conditions.

15

Independent Measures Design

Different participants used for each level of the independent variable

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Strength of Independent Measures

There is no chance of boredom, order effects or practice influencing performance in the second or subsequent conditions.

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Weakness of Independent Measures

More participants will be needed, and as different people will take part in each condition, individual differences may influence the results.

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Matched Participants / Pairs Design

Participants who are similar on key variables with one participant being placed in one experimental condition and the other in the other experimental conditions.

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Strength of Matched Participant / Pairs Design

Allows participants to be matched on features that are important to the study. For example, Bandaranaike matched participants on aggression levels, which was an important aspect of his study into the transmission of aggression.

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Weakness of Matched Participants / Pairs Design

It may be difficult to find an adequate number of participants who can be matched to the desired features.

21

Independent Variable

The factor in an experiment that is manipulated, changed or compared by the researcher with the expectation that it will have an effect on the dependent variable. In a quasi experiment, this is not manipulated, as it is naturally occurring. For example, in Baron-Cohen’s study, he could not manipulate whether the participants were autistic, had Tourette Syndrome or were ‘normal’.

22

Dependent Variable (DV)

The factor in an experiment that is measured by the research to asses the effects of the IV. The DV is therefore any observed changes in behaviour which result from the manipulation (or natural occurrence) of the IV.

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Control of Extraneous Variables

The control of any factors other than the IV that might potentially affect the DV and so influence the findings. Environmental factors such as noise, temperature, time of day, etc., if not controlled, can influence findings. Likewise, individual factors such as gender, age, occupation, etc., if not controlled, can influence findings.

24

Behavioural Catagories

Objective methods used in observation to break a continuous stream of activity into discrete recordable events. For example, if observing behaviour in a sixth form common room, behavioural categories could include talking/using a mobile phone/working on a computer/reading/playing cards etc.

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Coding Frames

Lists of behavioural categories, each with a code.

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Time Sampling

A data recording method that involved recording pre-determined behaviours at regular intervals, for example every five seconds, or taking a sample at different times of the day or month.

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Event Sampling

Data recording method that involves counting the number of behaviours in a specified time period, for example using a tally chart.

28

Open Questions

Allow participants to give full and detailed answers in their own words. They produce qualitative data, which is in depth and very detailed. However, because open questions usually give qualitative data, it is often difficult to identify trends and patterns or make comparisons between participants.

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Closed Questions

Offer a small number of explicitly stated alternative responses from which the participant must choose. There is non opportunity to expand on answers and they produce quantitative data.

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Strength of Closed Questions

Results are easy to analyse, so trends and patterns can be identified and comparisons between individuals and/or groups can be made.

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Rating Scale

Numerical scales on which participants indicate the strength of some measure. They produce quantitative data.

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Likely Rating Scales

Allow participants to indicate hoe much they agree or disagree by choosing an option.

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Semantics Differential Rating Scale

Allow participants to choose between two extremes, rating their response towards an opposing pair of descriptive words. The partcip[ant chooses one of several numerical values.

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Weakness of Rating Scales

They are very subjective and therefore do not always give valid or useful findings.

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Strength of Rating Scales

The produce quantitative data, which make results easy to analyse

36

Raw Data

Data that has not been processed for use

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Tally Chart / Frequency Table

A grid used in an observation which shows the possible categories of results; a tick or tally is made each time the item is scored. These can be added together to give a Total in each category.

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Nominal Level Data

A level of measurement recording darts in totals of names catagories

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Ordinal Level Data

A level of measurement recording data as points along a scale where gaps between the points are not necessarily equal.

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Interval Level Data

A level of measurement recording data as points on a scale where the gaps between the points are equal.

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Quantitative Data

Numerical Data

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Qualitative Data

Descriptive data

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Primary data

Data gathered first hand from the sample

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Secondary data

Data gathered from research conducted by another research

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Measures of Central Tendancy

A mathematical way to describe a typical or average score from a data set

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Measures of Dispersion

A mathematical way to describe the variance or spread of scores in a data set.

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Variance

The average of the squared differences from the mean

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Standard Deviation

A measure of how spread out the scores are in a data set. It is the square route of the variance.

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Test of Difference - independent measures - nominal data

Chi-Squared

50

Test of difference - repeated measures / matched pairs - nominal data

Binomial Sign

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Correlation - nominal data

Chi - Squared

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Test of Difference - independent measures - ordinal data

Mann - Whitney

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Test of difference - repeated measures / matched pairs - ordinal data

Wilcoxon

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Correlation - ordinal data

Spearman’s Rank / Rho

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Test of difference, independent measures, interval data

Mann-Whitney

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Test of difference, repeated measures / matched pairs, interval data

Wilcoxon

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Correlation interval data

Spearman’s Rank / Rho

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Type 1 Error

Rejecting the null hypothesis when it is true / accepting the alternative hypothesis when it is not true.

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Type 2 Error

Accepting the null hypothesis when it is not true / rejecting the alternative when it is true.