Research Methods

Research Methods

1. testable hypothesis

   • null hypothesis the hypothesis that there is no significant difference between specified populations, any observed difference being due to sampling or experimental error.
   • The alternative hypothesis is the hypothesis used in hypothesis testing that is contrary to the null hypothesis. It is usually taken to be that the observations are the result of a real effect (with some amount of chance variation superposed).

2. types of variable

   • independant variable the experimenter manipulates (i.e. changes) – assumed to have a direct effect on the dependent variable.
   • Dependant variable the experimenter measures. This is the outcome (i.e. result) of a study.
   • Extraneous variable are any variables that you are not intentionally studying in your experiment or test.

3. designing research

   • experimental designs
     • independent measures
       • Avoids order effects (such as practice or fatigue) as people participate in one condition only. If a person is involved in several conditions they may become bored, tired and fed up by the time they come to the second condition, or becoming wise to the requirements of the experiment!
       • More people are needed than with the repeated measures design (i.e. more time consuming).
       • Differences between participants in the groups may affect results, for example; variations in age, gender or social background.
         • After the participants have been recruited, they should be randomly assigned to their groups. This should ensure the groups are similar, on average (reducing participant variables).
     • repeated measures
       • Fewer people are needed as they take part in all conditions (i.e. saves time).
       • As the same participants are used in each condition, participant variables (i.e., individual differences) are reduced.
       • There may be order effects. Order effects refer to the order of the conditions having an effect on the participants’ behavior. Performance in the second condition may be better because the participants know what to do (i.e. practice effect). Or their performance might be worse in the second condition because they are tired (i.e. fatigue effect). This limitation can be controlled using counterbalancing.
         • To combat order effects the researcher counter balances the order of the conditions for the participants. Alternating the order in which participants perform in different conditions of an experiment.
           • Suppose we used a repeated measures design in which all of the participants first learned words in 'loud noise' and then learned it in 'no noise'. We would expect the participants to show better learning in 'no noise' simply because of order effects, such as practice. However, a researcher can control for order effects using counterbalancing.
           • The sample would split into two groups experimental (A) and control (B). For example, group 1 does ‘A’ then ‘B’, group 2 does ‘B’ then ‘A’ this is to eliminate order effects. Although order effects occur for each participant, because they occur equally in both groups, they balance each other out in the results.
     • Matched Pairs
       • Each condition uses different but similar participants. An effort is made to match the participants in each condition in terms of any important characteristic which might affect performance, e.g. gender, age, intelligence etc.
         • One member of each matched pair must be randomly assigned to the experimental group and the other to the control group.
       • Reduces participant variables because the researcher has tried to pair up the participants so that each condition has people with similar abilities and characteristics.
       • Avoids order effects, and so counterbalancing is not necessary.
       • Very time-consuming trying to find closely matched pairs.
       • Impossible to match people exactly, unless identical twins!
       • If one participant drops out you lose 2 PPs’ data.
       • Members of each pair should be randomly assigned to conditions. However, this does not solve all these problems.
     • refers to how participants are allocated to the different conditions (or IV levels) in an experiment.
       • Independent measures / between groups: Different participants are used in each condition of the independent variable.
       • Repeated measures /within groups: The same participants take part in each condition of the independent variable.
       • Matched pairs: Each condition uses different participants, but they are matched in terms of important characteristics, e.g. gender, age, intelligence etc.
   • experimental settings
     • Field Experiments
       • Behavior in a field experiment is more likely to reflect real life because of its natural setting, i.e. higher ecological validity than a lab experiment.
       • There is less likelihood of demand characteristics affecting the results, as participants may not know they are being studied. This occurs when the study is covert.
       • There is less control over extraneous variables that might bias the results. This makes it difficult for another researcher to replicate the study in exactly the same way.
       • Field experiments are done in the everyday (i.e. real life) environment of the participants. The experimenter still manipulates the independent variable, but in a real-life setting (so cannot really control extraneous variables).
         • Field experiments are done in the everyday (i.e. real life) environment of the participants. The experimenter still manipulates the independent variable, but in a real-life setting (so cannot really control extraneous variables).
     • Laboratory / Controlled Experiments
       • This type of experiment is conducted in a well-controlled environment – not necessarily a laboratory – and therefore accurate measurements are possible.
         • The researcher decides where the experiment will take place, at what time, with which participants, in what circumstances and using a standardized procedure. Participants are randomly allocated to each independent variable group.
       • It is easier to replicate (i.e. copy) a laboratory experiment. This is because a standardized procedure is used.
       • They allow for precise control of extraneous and independent variables. This allows a cause and effect relationship to be established.
       • The artificiality of the setting may produce unnatural behavior that does not reflect real life, i.e. low ecological validity. This means it would not be possible to generalize the findings to a real life setting.
       • Demand characteristics or experimenter effects may bias the results and become confounding variables.

4. research procedures

   • Standardisation means keeping everything the same for all participants so that the investigation is fair.
     • For example, consider the instructions that are given to the participants. In order to ensure that all of the participants get precisely the same instructions, the experimenter should write them down.
   • Standardised instructions mean that you have a set of instructions that are applied to each participant exactly. it stops any variations that could cause experimenter bias etc
   • randomisation is using chance to produce an order for a procedure
   • extraneous variables
     • participant variables, age, intelligence, gender, personality, motivation, attention
     • situation variables, time of day, noise level, lighting, position in room
     • experimenter variables, personality, gender of experimenter
     • demand characteristics
       • prompt in the experiment that helps the participant work out the hypothesis or aim
       • may lead to the participant effects
         • wanting to please the experimenter and give results they want (social desirability bias) or the opposite
     • experimenter results
       • cues from the investigator (behaviour, appearance) which affect results (i.e. lead participants)
         • investigator may unconsciously act to bring about their prediction
       • can be reduced by double blind, neither participants or experimenter know what condition they are in
   • quantitative methods
     • emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques.
       • precise and numerical data
       • easy to compare and plot on a graph
       • reliable results
       • unopened to bias
       • less time consuming
       • inexpensive
       • can be used to observe people and animals and why we do things
       • objectiveness means data is easily agreed on and there are no outlying opinions
       • is not detailed
       • information is collected in an artificial setting
       • results cannot be generalised
       • sometimes subjectiveness is needed to represent thoughts and feelings
   • qualitative methods
     • used to uncover trends in thought and opinions, and dive deeper into the problem
       • methods vary using unstructured or semi-structured techniques. Some common methods include focus groups (group discussions), individual interviews, and participation/observations.
         • lengthy and detailed data
         • opinions can be considered as it is subjunctive
         • collected in a 'real life' setting
         • agreements cannot always be made on a conclusion
         • lack of precise numbers
         • not as reliable as quantitative data
         • bias' can influence results
         • time consuming
         • cannot compare or graph as easily
         • can be expensive

5. ethical issues

   • informed consent permission granted in full knowledge of the possible consequences
   • Deception is where participants are misled or wrongly informed about the aims of the research.
   • debriefing
     • After the research is over the participant should be able to discuss the procedure and the findings with the psychologist
     • They must be given a general idea of what the researcher was investigating and why, and their part in the research should be explained.
     • Participants must be told if they have been deceived and given reasons why. They must be asked if they have any questions and those questions should be answered honestly and as fully as possible.
     • Debriefing should take place as soon as possible and be as full as possible; experimenters should take reasonable steps to ensure that participants understand debriefing.
   • right to withdraw is a concept in clinical research ethics that a study participant in a clinical trial has a right to end participation in that trial at will.
   • confidentiality, participants, and the data gained from them must be kept anonymous unless they give their full consent. No names must be used in a research report.
   • protection from harm, participants should not be exposed to risks greater than or additional to those encountered in their normal lifestyles.

6. data handling

   • mean = sum of all values / number of values
   • mode = the piece of data that appears the most
   • median =
   • The range is the difference between the lowest and highest values.
   • Frequency table: Step 1: Construct a table with three columns. Then in the first column, write down all of the data values in ascending order of magnitude. Step 2: go through the list of data values and place one tally mark at for every data value. Step 3: Count the number of tally marks for each data value and write it in the third column.
   • normal distributions are bell shaped, symmetrical, the mean, median and mode fall on the sam central point, the two tails never touch the horizontal axis

7. sampling

   • the target population is the group the researcher is interested in
   • the sample is a small group of participants from the target population
   • sampling is the method of selecting participants from the target population, this is needed because we cannot use everyone
   • the sample should be representative of the target population (have the same characteristics) so the results can be generalised
   • random sampling
     • Everyone in the entire target population has an equal chance of being selected.
     • The advantages are that your sample should represent the target population and eliminate sampling bias
     • The disadvantage is that it is very difficult to achieve (i.e. time, effort and money).
   • Stratified Sampling
     • The researcher identifies the different types of people that make up the target population and works out the proportions needed for the sample to be representative.
       • A list is made of each variable (e.g. IQ, gender etc.) which might have an effect on the research. For example, if we are interested in the money spent on books by undergraduates, then the main subject studied may be an important variable.
     • Gathering such a sample would be extremely time consuming and difficult to do
     • the advantage is that the sample should be highly representative of the target population and therefore we can generalize from the results obtained.
   • opportunity sampling
     • Uses people from target population available at the time and willing to take part. It is based on convenience.
       • An opportunity sample is obtained by asking members of the population of interest if they would take part in your research.
     • This is a quick way and easy of choosing participants
     • but may not provide a representative sample, and could be biased
   • Systematic Sampling
     • Chooses subjects in a systematic (i.e. orderly / logical) way from the target population, like every nth participant on a list of names.
     • To take a systematic sample, you list all the members of the population, and then decided upon a sample you would like. By dividing the number of people in the population by the number of people you want in your sample, you get a number we will call n.
     • The advantage to this method is that is should provide a representative sample
     • it is very difficult to achieve (i.e. time, effort and money).

8. designing research

   • interviews
     • often involve face to face contact with small groups of people
     • interviewer asks questions verbally to interviwee, interviewer may then write them down
     • structured interviews
       • pre-planned questions mean that you can check ethical risks
       • quicker
       • more reliable
       • more quantitative
     • unstructured interviews
       • difficultly finding random questions quickly, cannot pre-check ethical risks.
       • more detail
       • more valid
       • more qualitative data
   • questionnaires
     • respondent writes answers to questions or may type over email or on a website
   • open questions are where the respondent can give any answer they like, there are an unlimited number of possible answers
     • gives qualitative data
   • closed questions have a range of possible answers determined by the researcher e.g. yes/no
     • gives quantitative data

9. observations

   • natural observation = watching people in their usual environment, researcher doesn't change anything
   • controlled observation = researcher changes something (iv) may be a part of the experiment
   • observation study = a method of collecting information about behaviour by watching and recording people's actions
   • categories of behaviour = the separate actions that are recorded as examples of the target behaviour
   • in some cases, they are more honest
   • if the people don't know they are being observed, they will display natural behaviour, this increases ecological validity
   • inter-observer reliability can help reduce the participant bias
   • can be time consuming
   • subjective
   • issues about when to gain consent, before = possible bias after = ethical issues and possible withdrawal

10. correlation

    • Correlation means association more precisely it is a measure of the extent to which two variables are related.
    • If an increase in one variable tends to be associated with an increase in the other then this is known as a positive correlation.
      • An example would be height and weight. Taller people tend to be heavier.

11. case studies

    • in depth investigations of a single person, group, event or community
    • carried out over a long period of time
    • in depth information
    • allows an insight into extraordinary cases
    • mostly lots of ecological validity
    • lots of sources used to collect data
    • results cannot be generalised
    • ethical issues
    • records can be inaccurate or incomplete
    • interviewer might to biased towards what they expect to find

12. primary and secondary data

    • primary data is what you have collected yourself, specifically for answering your research question
      • specific to your study
      • you know that you have taken measure to ensure validity
      • possible researcher bias
      • more time consuming
    • secondary data is existing data collected for another purpose that you use to answer your research question
      • not always specific
      • less chance of research bias
      • quick and easy to find
      • able to make comparisons to other studies or your own
      • sometimes organisations/researchers have a bigger budget and more resources

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