HNC Research Methodology: The EXPERIMENTAL METHOD• THE EXPERIMENTAL METHOD OF RESEARCH IS A CONTROLED PROCEDUREINVOLVING THE MANIPULATION OF AN INDEPENDENT VARIABLE (IV), TOOBSERVE AND MEASURE ITS EFFECT ON A DEPENDANT VARIABLE.FEATURES…• Establish cause and effect;• Allows for generalisation (standardised procedure), replication and validity;• One variable is manipulated, the other observed;• Variables – anything that changes;• Manipulate the IV (cause): observe the DV (effect).Variables Identify the following IV / DV :• Alcohol affects reaction time;• Particular teaching techniques affect exam results;• Watching too much TV increases aggression.• Other variables exist, known as extraneous / confounding variables – these, atbest, can be perceived as pollutants.Other variables:• Generally known as extraneous variables:coming from the outside. Random variables – almost impossible to anticipate; Confounding variables – can be controlled, and are of three types : Situational variables (refer to the experimental situation, for example theenvironment); Experimenter variables (the experimenter effect – e.g. expectancy effect); Participant variables (individual differences).The Hawthorn Effect• This is participant expectancy! This also pollutes the results : 1939, by the world‟s first occupational psychologists (Dickson et al). Assessed productivity and light and noise levels. Because theparticipants expected lower productivity, under conditions of the IV,productivity actually increased! The Hawthorn effect sees the participant behave in an unusual way –the cues that give the game away are known as DEMANDCHARACTERISTICS.Demand Characteristics• Demand characteristics are any features of the experiment, which help participantswork out what is expected of them, and consequently lead them to behave inartificial ways. These features demand a certain response. Participants search for
cues in the experimental environment about how to behave and what (might) beexpected from them. Keegan, 2002.Types of Experiment• The main difference is location and extent of manipulation!! Laboratory Experiments Field experiments Natural experimentsLaboratory Experiments• Set within the artificial environment of the lab;• Control; the experimenter has the highest level of control over the IV and the DV asis possible to infer cause and effect• Replication; in a laboratory setting the experiment can be directly replicated in future• The experimenter manipulates the IV, this involves direct manipulation of the IV totest cause and effect between the IV and the DV• Example: Asch (1955) Conformity researchExamples: Asch, social pressure (1951: 52: 53).Advantages…• Control;• Replication;• Generalising results;• Quantitative data;Disadvantages…• Low ecological validity;• Sampling bias, demand characteristics, experimenter expectancy;• Ethics : can be stressful to participants, deception might be involvedField experiments• Take place in everyday surroundings;• Participants are often unaware!• The experimenter manipulates the IV directly• The effects of the IV on the DV are less controlled than in the laboratory setting butthis method is more applicable to real life• examples:• Piliavin et al (1969): the good Samaritan, an underground phenomena?Advantages & disadvantages:• Improved ecological validity;• Avoids sampling bias;
• Reduction in demand characteristics.Disadvantages: Establishing control; Difficult to replicate; Ethics: consent, deception, privacy.Natural experiments…• No manipulation of IV! It is already in place.• The experimenter does not interfere with the IV in this type of experiment, there is nomanipulation• There is the least control over variables in this type of experiment, but it is veryapplicable to real life as there is no interference from the experimenter• Example: Oscar Lewis (1960s): Operation Head Start.Advantages & disadvantages…• Advantages• Reduction in demand characteristics;• Great ecological validity;• No sample bias;Disadvantages: Cause and effect difficult to establish between IV and DV; Little control, or replication; Ethics (privacy, consent, deception).Experimental designs…• Repeated Measures Design: The same participants are used in all conditions of the IV. Example: alcohol and reaction time. May produce order effects: fatigue, boredom, and prior practice leading tobetter performance. Counterbalancing (swapping the order of conditions) will reduce this.Independent Groups Design• Different participants are exposed to different conditions of the IV – the researcherwill use different participants for each condition.• Problem: subject variables (personal differences between the two, or more, groups).• Costly and time consuming.• Apply matched participants design.Control group and experimental group…• The control and experimental group undergo different conditions of the IV – takealcohol…
THE EXPERIMENTAL HYPOTHESIS…• A testable scientific prediction of cause and effect between an independent anddependant variable.• Two hypothesis – Experimental Hypothesis (or alternative): the IV will affect the DV ; Null Hypothesis: the IV will not affect the DV – if a result occurs, it is due to chancefactors.One or two tailed?• The experimental hypothesis can be : One tailed, ordirectional: predicts the direction of outcome: reduce, increase, lower,etc. Two tailed, or non-directional: no predication of outcome; this hypothesis simplystates that the IV will affect the DV: changes, affects, influences, etc.Probability and significance…• Probability is the likelihood of an event happening: a night out without alcohol, etc.• The like hood of results in a psychological experiment being due to chance factorsother than the manipulation of the IV, are expressed in terms of significance. Levelsof significance indicate the probability level (pvalue) of chance factors being thecause of your result. P values are normally set at : p = 0.05 – this means there is aone in twenty possibility of your results occurring due to chance factors, and not themanipulation of the DV.Participants, samples and populations…• Participants – take part in research!• Participants taken from a sample of the population;• Results generalised to the target population, or population at large;• Should obtain an unbiased sample: it should be representative!!• Representative samples have the same characteristics as the population it wasdrawn from!Methods of Sampling…• Opportunity sampling – the researcher will use anyone available at the time!!• Self-selected sampling – advertisements.• Imposed sampling – the participant had no choice!!• Random sampling – every member of the population has an equal chance ofbeing selected.• Systematic sampling – e.g. every 10thperson from a target population list. Thismay involve asking every tenth person to complete a survey at a supermarketcheckout• Quota sampling – the population is analysed and individuals are chosen inorder to ensure the sample has the same characteristics as the target or
general population in equal quantities. Gender is a good example – male andfemale participants are used in equal proportionsThe Scientific Approach: Terminology and key concepts Inductive – generalising to create laws so that they may be applied to the generalpopulation. Deductive – producing theories from observations so that hypotheses may beconstructed and tested. Reliability – results that can be consistently found when the experiment is repeated. Validity - Measuring results to ensure accuracy – your research should be testing forwhat you are actually measuring Ecological Validity – Whether Something is true to life (if the results can be appliedto real life situations) Scientific Validity – “Cause and effect” can be confidently concluded Quantitative data – Is any data in numerical form(can be quantified and statisticallyanalysed Qualitative data – In depth, detailed answer or summaryCommon Sense and Research Methods: Features and DifferencesCommon SenseSimple logicBiasedGeneral ignoranceBased on assumption, rumour and hearsayLearned from those around youIndividual experience/opinionsSubjective (narrow minded)Lacks validity and reliabilityNo attempt to substantiate its claimsUseful to the individualResearch MethodsBased on the scientific methodThere to support hypotheses, theory and conclude phenomenaUnbiasedValidity and reliabilityObjective (generalisation)Systematic process to collect dataRecognised research methodsEmpirical evidenceUseful to the social sciencesResearch MethodsSurvey
• The survey method of research asks a representative sample of people oral orwritten questions to find out about their attitudes, behaviours, beliefs, opinions orvalues. Gerard Keegan, Higher Psychology, 2002.• Mostly used by social psychologists;• Good design is imperative :• Standardised instructions;• Open (qualitative) and closed (quantitative) questions;• Likert scales;• Representative sample used (prevents response bias).• Surveys can be done in person, by phone or by post.• Quantitative data from closed and likert questions (categorical or numerical answers)• Qualitative data from open questions (in-depth answers)Advantages• Large amounts of data in a short space of time ;• Cheap ;• Range of data: qualitative & quantitative.• Good for future research.Disadvantages• No cause and effect conclusions ;• Open questions – hard to quantify ;• Closed questions – restrict creative answers;• GIGO effect (garbage in, garbage out)• Demand characteristics (social desirability bias)• Researcher effects: ethnic origin, gender, body language.An example• Adorno (1950): researching prejudice behaviours.• Adorno found authoritarian personalities to be more prejudice.InterviewsA conversation with a purpose!”• Verbal questionnaires ;• One-to-one questioning ;• Can be structured – pre-planned : un-structured – in - depth ; or semi – structured(Clinical interview) ;• Standardisation of structured interviews gives quantitative information (ascomparisons between participants can be made) ;• Highly qualitative (particularly the unstructured interview) ;
Features• The clinical interview: Piaget (conservation): some pre-set questions, but theinterviewer will ask spontaneous questions as a consequence of previous answers(semi – structured!). Very flexible and sensitive to participants.Advantages• Very detailed data obtained ;• Can be quantifiable (numerical), or qualitative (descriptive; high ecological validity) ;• Structured interviews can be generalised.Disadvantages• Self-report by the interviewee is an un-scientific method of gathering data ;• Cannot infer cause and effect relationship ;• Inexperience and lack of training of interviewer can be anextraneous variable;• Demand characteristics: interviewer effects.Examples• PSYCHOLOGY• Hodges and Tizard (1989): longitudinal study: institutionalised and ex-institutionalised children.• Result: institutionalised children found it difficult to form attachments with others –this impacted on their emotional, and social development.• SOCIOLOGY• Willis (1977) „Learning to Labour‟OBSERVATION• The observational method of research concerns the planned watching, recording,and analysis of observed behaviour as it occurs• It is a non-experimental method, cause and effect relationships cannot beestablished• Observation is a very useful method that can produce quantitative and qualitativedata depending on how it is designed for use• Observation can be used with other research methods within a multi-methodapproachThere are five main types that we should concern ourselves with:• Participant ( researcher joins the group and is involved with the participants, theresearcher might manipulate the situation in a covert or overt role)• Non-participant (researcher does not join the group and does not get involved withthe participants, but observation is usually planned observation and recording)• Natural observation (used within comparative psychology where the researchermight be interested in natural behaviours within animal subjects, e.g. Lorenz)
• Structured observation – involve the planned watching and recording of behaviourswithin the controlled environment of the laboratory• Unstructured observation – unplanned and informal, observations take place innatural environments and recorded on a casual basisFeatures• Qualitative (descriptive) and quantitative (numerical) information.• Data always recorded: check lists ; video recordings.• Can be covert or overt.• Covert involves the researcher joining the group and being „undercover‟, oftenpretending to be part of the group without the group‟s knowledge a researcher ispresent• Overt involves telling the group a researcher will be present but perhaps allowing thegroup to think you are observing something other than what you are observingExamples• Participant : James Patrick (1960s) ; Rosehan (1973) ; Piliavin et al (1969); Willis(1977)• Non – participant: Ainsworth et al (1978): strange situations; Bandura Ross andRoss (1961) aggression studies.• Natural observations: Lorenz and Imprinting (1960s).Advantages• Establish relationships before experimentation ;• Ecological validity (naturalistic, covert) ;• Avoidance of observer effects (non-participant) ;• Useful with ethological studies (of animals in habitats)Disadvantages• Ethics – lack of consent with covert studies;• Ethics – confidentiality ;• Observer effect ;• Possible lack of objectivity (participant) ;• Replication difficult ;• Poor control over confounding variables.CASE STUDIESThe case study method of research is a detailed, in-depth investigation of an individual (orsmall group) with unique or interesting characteristics.Features:• Idiographic in nature;• Involves many other methods of enquiry: case histories; interviews; questionnaires;psychometric tests; diaries; observation; and experimental research.
• Two types: retrospective & longitudinal.• Retrospective: recall of past events (Freud’s case studies of Anna O / Little Hans).• Longitudinal : follow the same individual or group over an extended period of time(BBC’s 7-Up, currently at age 56)Advantages• Large amounts of qualitative data ;• High ecological validity ;• Sensitive to the individual, and sensitive to issues concerning the individual.Disadvantages• Cannot generalise results ;• Replication impossible, to confirm earlier results ;• Reliability of information is self-report (subjective, inaccurate) ;• Interviewer/observer bias ;• Lack of scientific validity: no cause effect conclusions can be drawn.Primary and Secondary sources of dataPrimary– These are data that you have collected first hand– You carry out your own research in the laboratory or field (can be timeconsuming and expensive)– You set your own parameters, control your own variables and select your ownparticipantsSecondary– Use of data that someone else has collected– You use information you perhaps could not have collected first hand– You save time and money over primary research but you accept existingbiases– Desk based researchPrimary sources of data The main primary sources of data are:– Experiment– Correlation– Case study– Observation– SurveyPrimary and Secondary sources of reading Primary
– Think autobiographies– First-hand accounts written by people who were there– Authentic and detailed but often highly subjective– Invaluable insight into phenomena or events Secondary– Think biographies– Examination of primary sources by a more objective third party– Evaluation and new understanding of primary sources– Often collates a wide range of primary sources with a commentary to addunderstanding and strengthen viewpointsQualitative and Quantitative data Qualitative– Rich– Insightful– Verbal– Time consuming– Difficult to compare and contrast Quantitative– Numbers– Statistics– Numerical analysis– Graphical display– Objective– Can lack depthResearch and MethodologyWhere do we start? The Research Process Start with a general aim (based on theory or prior research) Formulate a hypothesis (a specific statement to test) Test the Hypothesis Collect and collate the evidence Analyse the data Understand what the data mean Write up your findingsMain types of Research for Primary Data Experimental
– This is the most scientific method– You change something and study the effect this has on something else Non-Experimental– Correlation– Case study– Observation– Survey Experiments can take place in one of three settings:– Laboratory – very controlled, can be easy to replicate but low in ecologicalvalidity– Field – less control, more difficult to replicate but high in ecological validity– Natural – researcher has no real control but very high in ecological validity,and probably no other opportunity to study phenomena. Often takingopportunity to study something otherwise unavailable to researchers Hypotheses– Experimental (Sometimes called „Alternative‟) Hypothesis– Null Hypothesis Before you carry out research, you make a statement to test. This is your Experimental (or Alternative) Hypothesis. It states that when you manipulate one variable it will have an effect on another. Experiment is the only method that can determine cause and effect - a causalrelationship (NB not „casual‟!) The Null Hypothesis states that there is no experimental effect. You will always have both hypotheses. One will be correct in that there will either bean effect or not (although we‟ll come back to this when we look at directionalhypotheses) You can either predict the direction of change in a hypothesis or just say that therewill be an effect. 1-tailed is when you predict direction– (think – it will go that way) 2-tailed is when you just predict effect– (Think of the caterpillar in Alice in Wonderland – could go thisaway or could gothataway!) Even if you find a cause and effect relationship between your variables the directioncould be wrong if you used a 1-tailed hypothesisEthics
When you carry out research using human participants you must consider ethics. Atuniversity level, research proposals go before an ethics committee for approvalbefore you start to carry out research. Key aspects include:– Informed consent– Deception– Distress– Confidentiality– Right to Withdraw Informed Consent– Participants should know what will be required of them (and what they areletting themselves in for!) Deception– Sometimes you need to hide the true purpose of the experiment until you havefinished. Where deception takes place there needs to be a clear debrief Distress– Taking part in research should not cause any distress to a participant. Thereshould be no physical or psychological harm to participants. Confidentiality– Participants should not be identified within the study. Participation and resultsshould be anonymous and confidential. Right to Withdraw– Participants have a right to withdraw consent for their contribution to be used. Right to Withdraw– Participants have a right to withdraw consent for their contribution to be used.– They have the right to withdraw at any stage. This means they can changetheir mind at the consent/briefing stage; during the experiment/study; after thestudy has taken place (give a timeline, e.g. 2 weeks after they take part)– Give clear guidelines as to how their contribution will be used and the last datefor withdrawal.Sampling It is unlikely that you will undertake research with every potential participant. The aimis usually to:– Identify your target population (who you are interested in researching)– identify a representative sample– carry out research with this small group– generalise the results back to the target population
Identify your target population. This is the group of people you want to be able to talkabout. Your sample should represent your target population. Select your sample using an accepted technique:– E.g. Random Sampling; Opportunity Sampling Carry out the research on your sample. Generalise your findings back to your target population. Random Sampling Opportunity/Convenience Sampling Self-selecting Sampling Realism - Ecological Validity Random Sampling– This is effectively names out a hat. Every person has an equal chance of beingselected with every name drawn. Can use computers. Opportunity/Convenience Sampling– Place yourself where you have access to your target population, e.g. footballcrowd or college Self-selecting Sampling– Ask for volunteers to take part in your researchAnalysis and Presentation of Findings Before you carry out your research you need to know how you are going to makesense of your results Analysing and Representing Findings: Quantitative Analysis– Percentages– Measures of Central Tendency Mean, Median, Mode– Measure of dispersion– Charts and Graphs Once you have carried out your research you need to find out what your resultsmean. This involves calculations and presentations. Unusual results can be talked about in isolation but normally you will be talkingabout the results as a whole. To do this, you will look at patterns, trends, differencesand similarities in the data.Quantitative Analysis Measures of Central Tendency– Mean (arithmetic average)– Median (mid-point when ordered)
– Mode (most frequently occurring) PercentagesQuantitative Analysis: MMM– Mean(arithmetic average)Add up the scores then divide by the number of scores. This is the mean.– Median (mid-point when ordered)Put responses in ascending order and count in from each side to the middle score.This is the median.– Mode(most frequently occurring)Find the score that occurs most frequently. This is the mode. (There may be a tie –you can have one, two or even three modes, but no more!)Quantitative Analysis: Range This is a measure of dispersion, or how spread out your scores are. Mean, Medianand Mode could all fall on the same score but one variable could have a small range(all scores clustered tightly together) and another could be very spread out. Rangeshows this spread. Range = (maximum score – minimum score) + 1Quantitative Analysis: % As there can be different numbers of participants in different studies, or even withindifferent groups in the same study, it is helpful to consider what equivalent scoresare „per hundred‟ or per cent (%). E.g. to calculate the percentage of people scoring at a particular level or above:count up how many participants are in this category, divide by the total number ofparticipants, (=), then multiply by 100. Round to the nearest whole number.Presentation of Findings When you present findings you should label every graph or chart clearly. Make sureit is clear what variables you are presenting. Always describe what the graph shows. Graphs and charts should display data in a visual and accessible way, otherwise youwould just talk about your findings.Line Graph– Used for continuous scores. Good to show trends and patterns.Graph showing 2009 profits in yellow and 2010 profits in blue
Histogram/Histograph– Each variable can be shown with a solid bar. Like aline graph, it also needs a continuous scale on the x-axis. There isarelationship between thebars – the scale is usuallyincreasingfrom left to right.Bar Chart– Each variable can be shown with asolid bar. There is no relationship betweenbars.Pie Chart– These can be calculated with degrees but there are pie-chart templates that allow you to use percentages (much easier!) When you present a correlation graphically you would use a scatter graph. Make sure you label both axes clearly.