Research Methods 1.2 (Planning and Conducting Research)

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  • Created on: 06-05-16 17:10

Research Aims vs. Research Questions

·         Research aim:

-          A research aim takes a research question and makes it more specific.

·         Research question:      

-          A research question is a question about animal or human behaviour.

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Hypotheses (Alternative and Null)

·    Null hypotheses:                                                                                                           Tells us that the IV will not have the predicted effect on the DV, it always states that there will be no difference between conditions and in a correlational study it will always predict no relationship.

·     Alternative hypotheses:                                                                                                 One-tailed (directional) hypotheses:  A specific event is predicted. One-tailed’s only have one possible true tcome, if all previous research indicates that there will be a certain outcome it is logical to have a one-tailed hypothesis.In correlations it will predict if the correlation will be positive or negative.

·    Two-tailed (non-directional) hypotheses: An effect is predicted but not specified, they have two possible true outcomes, if there is no previous research or conflicting research it is logical to use a two-tailed hypothesis. In correlations it will predict that there will be a correlation but not whether it will be positive or negative.

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Target Population and Sample

·         Target population and sample

-          The section or group of people whom psychologists want to study is the target population and the target sample is a group chosen from the population to take part in the research.

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Random Sampling

·         Random sampling

-          Every member of the target population must have an equal chance of being selected to be in the sample. To obtain a random sample there has to be a clear target population where a full list of members can be drawn up and then a random sample can be taken from this list. For a large target population, a researcher can use a random number generator computer program to select the sample, for the smaller sample the researcher can put the names in a hat and pick them out from there.

·         Strengths and weaknesses: Strengths = it is more likely to produce a representative sample, weakness = time consuming to select a sample

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Snowball Sampling

·         Snowball sampling

-          The researcher will find one participant and once they have been studied the researcher will ask if they know anyone who might be interested in taking part in the researcher. This person will then be contacted and have their data collected with the researcher asking if they know anyone and so on until the sample is of an adequate size.

-          Strengths and weaknesses: Strengths = useful for obtaining a sample of difficult to obtain people, weakness = bias of the sample often acquaintances have similar characteristics e.g. age or location. 

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Opportunity Sampling

·         Opportunity sampling

-          An opportunity sample (or convenience sample) is when the researcher selects the most convenient people to study. Opportunity samples give researchers access to large numbers of easy-to-access participants.

-          Strengths and weaknesses: Strengths = quick, cheap and easy to obtain a sample, weakness = unlikely to be representative.

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Self Selecting Sample

·         Self-selected sampling

-          Here people will choose to take part or volunteer to take part in the research, typical ways of obtaining such a sample include putting an advert in a newspaper or a notice on a notice board. The people who respond to ad or notice are volunteering to take part in the study.

-          Strengths and weaknesses: Strengths = volunteers are more likely to take part in a lengthy study, weakness = volunteers tend to have certain characteristics e.g. spare time or an interest in psychology making it unrepresentative at times.

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Experimental Design

·Repeated measures design: Each P is tested in all conditions of the experiment so the P's provide their own comparison results. Strengths and weaknesses: Strengths = eliminates individual differences, uses fewer P's, weaknesses = affected by order effects e.g. boredom and fatigue, subjects may work out the IV and show demand characteristics.

·         Independent measures design: Each condition of the experiment is taken part in by different P's the results from each group are compared with the scores from the other groups.Strengths and weaknesses: Strengths = no order effects, reduced chance of demand characteristics and less time consuming than matched pairs, weaknesses = individual differences, often needs a larger sample to be sure that the IV effects the DV not the differences between the P's.

·    Matched pairs design: Each participant is paired up with someone else in the sample on the basis of relevant variables. One of the pair takes part in one condition and the other takes part in another condition, each score is compared with its related score.Strengths and weaknesses: Strengths = reduces the chance of individual differences and order effects, weaknesses = time consuming and there are still extraneous individual differences that might confound the study..

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IV vs. DV

·         Independent variable (IV) =

-          Variable that is changed.

·         Dependent variable (DV) =

-          Variables that is measured.

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Extraneous Variables (Participant and Situational)

-         Extraneous Varibles: These are other variables which might influence the behaviour and need to be controlled as far as possible, they can be participant variables or situational variables. The participant variables are the factors within a person that can vary over time or with a situation. Subject variables can also vary between people. More obvious differences include age, gender and ethnicity. Situational variables can vary in the environment including level of noise, number of people present, time of day or the way an experimenter behaves towards the participants. If any extraneous variables are not controlled and gets involved in the study it becomes a confounding variables.

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Designing Observations: Behavioural Categories

·        Behavioural categories 

-         These are used in structured observations so that the researcher knows what is going to be observed and how it is going to be observed before the study takes place. Categories of behaviours to observe are established and then used by all the observers taking part in the study.

-          Strengths and weaknesses: Strengths = they provide quantitative data to analyse and make comparisons between participants on, weakness = it restricts the observations that can be made by observers so the researcher may miss important behaviour and the data is not as in depth as recording all behaviours.

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Designing Observations: Coding Frames

·         Coding frames

-          The researcher needs to observe behaviour and identify the key features of this behaviour to code them. Initially observations are made about how the participant behaves in a certain situation and then the categories of these behaviours can be identified. Finally, an analysis can be carried out to see how the behaviours change between participants in different situations.

-          Strengths and weaknesses: Strengths = useful as they provide easily analysed quantitative date, weakness = time consuming so not cost or time effective.

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Designing Observations: Time vs. Event Sampling

·         Time sampling:

-          This is where the observer records what the participant is doing at fixed intervals during the observation.

-          Strengths and weaknesses: Strengths = manageable method of recording behaviour, weakness = key behaviours may be missed which reduces validity.

·         Event sampling:

-          This is where each time an event happens it is recorded by the observer in observation schedules or observation categories.

-          Strengths and weaknesses: Strengths = gives rich detailed data, weakness = less manageable which means that observers may not be able to record every behaviour each time they see it which reduces validity.

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Designing Self Report: Open Questions

·         Open questions

-          These allow the participant the freedom to respond and explain their answers, they provide qualitative data.

-          Strengths and weaknesses: Strengths = the psychologists get rich, detailed data, weakness = harder to analyse/compare responses and is therefore difficult to establish the reliability of the responses. 

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Designing Self Report: Closed Questions

·         Closed questions

-          Gives the participant a limited/fixed range of responses to choose from, the data is quantitative.

-          Strengths and weaknesses: Strengths = the data collected is easy to analyse/compare and easier to check for reliability, weakness = limited information gathered, participants may omit useful information. 

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Designing Self Report: Rating Scales (Likert and S

·         Rating scales:Often used in self-report questionnaires and structured interviews, rating scales provide a quantitative measure.

-        The Likert rating scale: where people are given a range of answers from which they select the one that represents the extent to which they like/dislike something or agree/disagree with something. Strengths and weaknesses: Strengths = increases ecological validity as people have a range of options to choose from, easy to interpret data into a graph and quick to complete, weaknesses = limited data and people may only circle the middle value.

-          A semantic differential scale:used to put something on a scale between 2 descriptive words. To create the scale, the researcher uses two opposite relevant words a place a number of spaces between the two words for the participant to mark their rating.   Strengths and weaknesses: Strengths = data is quantitative and easy to analyse and compare, weaknesses = subjective as one word may mean something different to two people.

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