Planning And Conduction Reseach

Question 1

Research Aims

Answer 1

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.

Question 2

Research Question

Answer 2

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

Question 3

Null Hypothesis

Answer 3

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.

Question 4

Alternative Hypotheseis

Answer 4

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.

Question 5

One-Tailed Hypothesis

Answer 5

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.

Question 6

Two-Tailed Hypothesis

Answer 6

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.

Question 7

Target Population

Answer 7

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

Question 8

Random Sampling

Answer 8

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

Question 9

Snowball Sampling

Answer 9

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.

Question 10

Oppertunity Sampling

Answer 10

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

Question 11

Self-Selecting / Volunteer Sample

Answer 11

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

Question 12

Repeated Measures

Answer 12

Each participant takes part in every condition under test.

Question 13

Strength of Repeated Measures

Answer 13

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

Question 14

Weakness of Repeated Measures

Answer 14

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.

Question 15

Independent Measures Design

Answer 15

Different participants used for each level of the independent variable

Question 16

Strength of Independent Measures

Answer 16

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

Question 17

Weakness of Independent Measures

Answer 17

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

Question 18

Matched Participants / Pairs Design

Answer 18

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

Question 19

Strength of Matched Participant / Pairs Design

Answer 19

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.

Question 20

Weakness of Matched Participants / Pairs Design

Answer 20

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

Question 21

Independent Variable

Answer 21

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’.

Question 22

Dependent Variable (DV)

Answer 22

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.

Question 23

Control of Extraneous Variables

Answer 23

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.

Question 24

Behavioural Catagories

Answer 24

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.

Question 25

Coding Frames

Answer 25

Lists of behavioural categories, each with a code.

Question 26

Time Sampling

Answer 26

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.

Question 27

Event Sampling

Answer 27

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

Question 28

Open Questions

Answer 28

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.

Question 29

Closed Questions

Answer 29

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.

Question 30

Strength of Closed Questions

Answer 30

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

Question 31

Rating Scale

Answer 31

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

Question 32

Likely Rating Scales

Answer 32

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

Question 33

Semantics Differential Rating Scale

Answer 33

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.

Question 34

Weakness of Rating Scales

Answer 34

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

Question 35

Strength of Rating Scales

Answer 35

The produce quantitative data, which make results easy to analyse

Question 36

Raw Data

Answer 36

Data that has not been processed for use

Question 37

Tally Chart / Frequency Table

Answer 37

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.

Question 38

Nominal Level Data

Answer 38

A level of measurement recording darts in totals of names catagories

Question 39

Ordinal Level Data

Answer 39

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

Question 40

Interval Level Data

Answer 40

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

Question 41

Quantitative Data

Answer 41

Numerical Data

Question 42

Qualitative Data

Answer 42

Descriptive data

Question 43

Primary data

Answer 43

Data gathered first hand from the sample

Question 44

Secondary data

Answer 44

Data gathered from research conducted by another research

Question 45

Measures of Central Tendancy

Answer 45

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

Question 46

Measures of Dispersion

Answer 46

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

Question 47

Variance

Answer 47

The average of the squared differences from the mean

Question 48

Standard Deviation

Answer 48

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

Question 49

Test of Difference - independent measures - nominal data

Answer 49

Chi-Squared

Question 50

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

Answer 50

Binomial Sign

Question 51

Correlation - nominal data

Answer 51

Chi - Squared

Question 52

Test of Difference - independent measures - ordinal data

Answer 52

Mann - Whitney

Question 53

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

Answer 53

Wilcoxon

Question 54

Correlation - ordinal data

Answer 54

Spearman’s Rank / Rho

Question 55

Test of difference, independent measures, interval data

Answer 55

Mann-Whitney

Question 56

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

Answer 56

Wilcoxon

Question 57

Correlation interval data

Answer 57

Spearman’s Rank / Rho

Question 58

Type 1 Error

Answer 58

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

Question 59

Type 2 Error

Answer 59

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