Research Methods Flashcards
What are the measures of central tendency?
Mean
Median
Mode
What is the Mode?
Calculates the most frequent score in a data set. The mode is the value that occurs most frequently.
What is the Median?
The middle number within an ordered set of values
What is the Mean?
The middle number within an ordered set of values
What type of data is the mode, median and mean typically used for?
Mode - Nominal
Median - Ordinal
Mean - Interval/Ratio Level
What are the levels of measurement from lowest to highest? Explain them
Nominal data- frequency count data
Ordinal- scores in rank order
Interval- a continuous scale with no absolute zero
Ratio- a continuous scale with an absolute zero
What is a null hypothesis, what is an experimental hypothesis?
How is a null hypothesis tested?
Null- The experimenter predicts the IV will have no effect on the DV/ no significant effect will be found
Experimental- The experimenter predicts the IV will have an effect on the DV/ a significant effect will be found
It is tested by ?
What is a one-tailed directional, and a two-tailed non-directional hypothesis?
A one-tailed directional hypothesis predicts the nature of the effect of the independent variable on the dependent variable.
E.g., adults will correctly recall more words than children.
Non-directional 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.
What are extraneous variables and confounding variables?
Extraneous- All variables, which are not the independent variable, but could affect the results (DV) of the experiment. EVs should be controlled where possible.
Confounding- Variable(s) that have affected the results (DV), apart from the IV. A confounding variable could be an extraneous variable that has not been controlled.
What are situational and participant variables?
the differing individual characteristics that may impact how a participant responds in an experiment. Examples of participant variables include gender, age, ethnicity, socioeconomic status, literacy status, mood, clinical diagnosis etc.
What are field and lab experiments and outline the strengths and weaknesses.
A laboratory experiment is an experiment conducted under highly controlled conditions (not necessarily a laboratory), where 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.
Strengths: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.
Weaknesses: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.
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).
Strength: 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.
Weakness: 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.
What are demand characteristics?
The clues in an experiment that lead the participants to think they know what the researcher is looking for (e.g. experimenter’s body language).
What are order effects and how do you get rid of them?
Changes in participants’ performance due to their repeating the same or similar test more than once. Examples of order effects include:
(i) practice effect: an improvement in performance on a task due to repetition, for example, because of familiarity with the task;
(ii) fatigue effect: a decrease in performance of a task due to repetition, for example, because of boredom or tiredness.
Identify and explain the types of research/experiment design
Matched pairs
An experimental design where pairs of participants are matched in terms of key variables, such as age or socioeconomic status. One member of each pair is then placed into the experimental group and the other member into the control group.
One member of each matched pair must be randomly assigned to the experimental group and the other to the control group.
Independent group
An experimental design where different participants are used in each condition of the independent variable. This means that each condition of the experiment includes a different group of participants.
This should be done by random allocation, which ensures that each participant has an equal chance of being assigned to one group or the other.
Independent measures involve using two separate groups of participants; one in each condition.
Repeated measures
An experimental design where the same participants take part in each condition of the independent variable. This means that each condition of the experiment includes the same group of participants.
Counterbalancing is done in this method.
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.
Explain why it is helpful to have a control group.
Scientists use controlled experiments because they allow for precise control of extraneous and independent variables. This allows a cause and effect relationship to be established.
Unlike the experimental group, the control group is not exposed to the independent variable under investigation and so provides a base line against which any changes in the experimental group can be compared.
What is randomisation?
Randomly allocating participants to independent variable conditions means that all participants should have an equal chance of taking part in each condition.
The principle of random allocation is to avoid bias in the way the experiment is carried out and to limit the effects of participant variables.
Compare lab and field experiments
Communication: Field experiments provide a more open and relaxed atmosphere for discourse. The field experiment helped the communication tensions with the participants as they felt they were not being directly examined. As well as generally promoting the generation of qualitative data, the field experiments encouraged the expression of broader, as well as more contextually relevant views.
Reliability: Field experiments are undeniably more difficult to conduct than lab experiments. Confounding factors are present, for example, variations in the weather and noise. In addition, although it is desirable that participants engage in the task, their foci of attention could not be controlled and was difficult to predict. Some participants are “distracted” from the experimental tasks, and this does not occur in a laboratory setting. The greater control possible with a laboratory study produces more reliable results.
Issues with independent groups and matched pairs experimental designs.
INDEPENDENT GROUPS DESIGN
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. These differences are known as participant variables (i.e., a type of extraneous variable).
MATCHED PAIRS
If one participant drops out you lose 2 PPs’ data.
Very time-consuming trying to find closely matched pairs.
Impossible to match people exactly, unless identical twins!
Issues with independent groups and matched pairs experimental designs.
INDEPENDENT GROUPS DESIGN
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. These differences are known as participant variables (i.e., a type of extraneous variable).
MATCHED PAIRS
If one participant drops out you lose 2 PPs’ data.
Very time-consuming trying to find closely matched pairs.
Impossible to match people exactly, unless identical twins!
What is a case study?
Strengths and weaknesses?
Case studies are in-depth investigations of a single person, group, event or community. Typically, data are gathered from a variety of sources and by using several different methods (e.g. observations & interviews).
The procedure used in a case study means that the researcher provides a description of the behavior. This comes from interviews and other sources, such as observation.
The client also reports detail of events from his or her point of view. The researcher then writes up the information from both sources above as the case study, and interprets the information.
STRENGTHS Provides detailed (rich qualitative) information.
Provides insight for further research.
Permitting investigation of otherwise impractical (or unethical) situations.
WEAKNESSES
Lacking scientific rigour and providing little basis for generalization of results to the wider population.
Researchers’ own subjective feeling may influence the case study (researcher bias).
Difficult to replicate.
Time-consuming and expensive.
The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources.
What are the sampling methods?
stratified- when 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.
opportunity- when the participants are chosen because they are available at the time and place where the research is taking place.
random- when all members of the population are allocated numbers and a fixed amount of these are chosen in an unbiased way, for example, picking out numbers from a hat.
volunteer- When participants are invited to take part in studies via advertisements or emails.
what are questionnaires, observations, interviews, their pros and cons?
Questionnaires:
A research method that involves asking questions, mainly written, to gain information from the participants.
They contain closed and open questions, likert scales and rank scales. Type of data collected can be quantitative or qualitative.
STRENGTHS
Participants are more likely to give truthful answers as it does not involve talking to someone face to face
A large sample can answer the questionnaire in a short time span which should increase the representativeness and generalizability of the findings
WEAKNESSES
Participants may give socially desirable answers
Too many closed questions may force an answer that does not reflect the participant’s opinion
Response bias
Interviews:
A research method using verbal questions asked directly to the participants.
Three types: structured un and semi.
STRENGTH
Lots of open questions will make participants reveal reasons as to why they behave in a particular way or have a particular opinion
WEAKNESS
Participants may be less likely to give truthful answers as they are face to face with the interviewer or because of social- desirability
Observations:
A research method that involves watching human or animal behaviour.
An observer can be overt/covert or they can be participant/non-participant observers.
Overt observers are when the participants know who the researcher is and that they are being observed. A covert observer could be present in the group of participants observing them but they do not know who it is.
A participant observer is one who watches from the perspective of being part of the social setting of the participants. A non-participant observer does not become involved in the situation being studied.
Type of data collected: Qualitative
STRENGTHS
If participants are unaware of the observation taking place - increases ecological validity but informed consent not there
As behaviours are ‘counted’, data can be analysed statistically with minimal bias
WEAKNESSES
If the participants are aware of the observation, they may not act ‘naturally’ but show more socially desirable behaviour. This can reduce the validity of the findings
It may be difficult to replicate the study if it is naturalistic as many variables cannot be controlled which reduces the reliability
What are self-reports?
A self-report is any method which involves asking a participant about their feelings, attitudes, beliefs and so on. Examples of self-reports are questionnaires and interviews.
Differentiate between primary and secondary data
Primary data is first hand data collected for the purpose of the investigation.
STRENGTHS
Primary data is reliable way to collect data because the researcher can do it again as they know the procedures, how it was collected and analysed since they did it themselves.
Also, the chances are it will also be more up to date too. Data gathered years previously (e.g. Milgram) are less likely to provide reliable answers to the questions your data needs to address.
Since it is direct from the population in question, it is one of the best types of data to collect for research methods like the survey.
WEAKNESSES
Researchers may be subjective in what kinds of data they look for in particular data that fits the hypothesis they are trying to test. For example Milgram may have used primary data from his experiments to back up Agency Theory.
Secondary data is information that has been collected by someone other than the person who is conducting the research e.g. taken from journals, books or articles.
STRENGTHS
Less time consuming and cheaper to use as the data has already been collected – this means more information can be used than what an individual might collect themselves
Secondary data may be the only data available e.g. historical documents and research
You can check secondary data for validity and reliability by using multiple sources
WEAKNESSES
May not be valid as the data may not be specific to the research aim, so not looking at what the researcher intends
May be out of date as it may have been collected historically, this means it may not be relevant to the research aim at the time
May be unreliable as the researcher may not know how the data was collected and if it followed a standardised procedure or how the variables were operationalized.
Differentiate between open and closed questions
Open questions: questions which allow the participant to give detailed answers without any restrictions.
Closed questions: questions which allow the participant to respond using a few, stated responses without the opportunity to expand on their answers.
Differentiate between qualitative and quantitative data
Quantitative data is information about quantities, and therefore numbers
STRENGTHS
Findings can be generalised if selection process is well-designed and sample is representative of study population
Data can be very consistent, precise and reliable
Relatively easy to analyse
WEAKNESSES
Related secondary data is sometimes not available or accessing available data is difficult/impossible
Difficult to understand context of a phenomenon
Data may not be robust enough to explain complex issues
——————————————————————-Qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.
STRENGTHS
Complement and refine quantitative data
Provide more detailed information to explain complex issues
Multiple methods for gathering data on sensitive subjects
Data collection is usually cost efficient
WEAKNESSES
Findings usually cannot be generalised to the study population or community
More difficult to analyse; don’t fit neatly in standard categories
Data collection is usually time consuming
Differentiate between structured, semi-structured and unstructured interviews
Structured: an interview with questions in a fixed order which may be scripted. Consistency might also be required in the interviewer’s posture, voice, etc., and hence these are highly standardized.
Semi-structured: an interview with a fixed list of questions, however, the interviewer could add more questions if required to clarify or get details on any previous answers.
Unstructured: an interview in which most questions depend on the respondent’s answers. A list of topics may be provided that need to be covered for the interview.
What are researcher effects and how do they cause social desirability bias and demand characteristics?
Researcher effects occur when a researcher unintentionally, or unconsciously influences the outcome of any research they are conducting.
The researcher can communicate their feelings about what they are observing without realising that they have done so.
This causes the participant to change their answers to an interview as a response of the researcher’s facial expression, for example, as a way to seem socially desirable in front of the researcher.
What is thematic analysis? Is it reliable?
Thematic analysis is a method for identifying, analysing and reporting patterns
(themes) within data.
Differentiate between normal and skewed distribution.
In a normal distribution, the mean and the median are the same number.
A left-skewed, negative distribution will have the mean to the left of the median.
A right-skewed distribution will have the mean to the right of the median.
