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An Abstract is a summary of the important points found in a psychology research report. It should be about 250 words long, and should succinctly summarise the aim, background; design; sample; measures; results and statistical conclusion of your study. Write an Abstract in the past tense, and avoid personal references like 'I'.
The aim of your investigation should be found at the end of the Introduction section in your research report. Your aim concludes with the proper presentation of your null and experimental hypotheses. For further details see entry under the null hypothesis.
Null hypothesis H0: 'That gender does not have an effect on perceived intelligence at the 0.05 level of significance.'
In the Method section of a psychology research investigation you would have the sub-heading Apparatus. Here you list any apparatus you used in your investigation Here is a sample Apparatus listing for an investigation into the Stroop Effect.
1. Colour vision deficit card Appendix i
2. Literacy test Appendix ii
3. Standardised Instruction Appendix iii
4. Raw data chart Appendix iv
5. Stopwatch (you don't need to include this!!)
6. Serial verbal reaction wordlists 1-6 Appendix v
7. Debriefing statement Appendix vi
This is the last section in a research investigation where you have the likes of your raw data chart, apparatus, mean, median, t-test calculations, materials, consent form, debriefing forms etc.
Enumerate and label each element e.g. Appendix iv 'T-test calculation'. Note I have used roman numerals to identify each appendix. You do the same. Make sure each appendix has a page number that corresponds with your Contents page.
Your conclusion section is a brief non-numerical statement on your findings. Here is an example of a full mark conclusion in a psychology practical investigation.
A big issue in psychology investigations! For more details see Ethics.
Different examination bodies/institutions may have slightly different requirements as to the Contents, or what should be contained in your psychology research reports. The layout below is one that is globally recognised. Yours should be very similar. A Contents page should obviously indicate where in your report the following could be found.
A correlation is a technique that tries to establish a statistical relationship between two covariables/covariates. An example of a correlation would be the relationship statisticians have found between smoking and cancers.
A correlation can be illustrated using a descriptive statistic called a scattergram, and also measured using an inferential statistic like Spearman's rho.
Counterbalancing and ABBA
Counterbalancing is used to overcome order effect in a repeated measures design experiment. Counterbalancing attempts to control for participant practice, fatigue, or boredom when they are exposed to the measure or performance or dependent variable on second or subsequent manipulations of the independent variable. If we had 20 participants in our alcohol/driving performance experiment counterbalancing would see participants 1-10 undergoing condition A then condition B of the IV e.g. alcohol/no alcohol. Participants 11-20 would alternatively undergo condition B then condition A of the IV e.g. no alcohol/alcohol. Whatever manipulation participants undergo first or second, all would similarly have performance measured on the DV. In this case, number of errors made on the driving simulation test. Counterbalancing uses the ABBA procedure to control for order effect in a repeated measures design experiment.
Used in experiments and is a hallmark of the experimental method. In an experiment if the null hypothesis is found to be untrue, our experimental or research hypothesis by counter intuition is supported. Alternatively if the null hypothesis is found to be rue, by counter intuition our experimental hypothesis is rejected.
Something that is free to vary.
Another issue regards Ethics. All who take part in psychological research deserve to find out what it was all about! This is often done at a Debriefing, where after an experiment a participant is told about its true purpose, what it was all about for them, and when/where they can find out the results of the investigation proper. I encourage my students to have a Debriefing statement prepared that they read out to the people good enough to take time out to help them in their research investigations. They include this in their Apparatus listings. It covers ethical considerations, and is professional in purpose.
A dependent variable only occurs in an experiment, and is the variable an experimenter observes or measures as a consequence of manipulation of the independent variable.
This is the name given to numerical or graphical statistics that we use to describe or summarise any data we generate in our research. Descriptive numerical statistics are those that indicate averages in data. These include such 'sums' as the mean, median, mode and standard deviation. Descriptive graphical statistics include graphs, charts, histograms, and scattergrams etc.
The Design is the research method you adopt. Research methods in psychology fall into two categories, those that adopt an experimental design and those that are non-experimental in design. Only the laboratory, field and quasi-experiment are experimental in design. Observation, Interview, Case Study, and the Survey are non-experimental. The reason is that the latter do not have an independent variable. The researcher in non-experimental procedures changes or manipulates nothing. As a result you can NEVER make any cause-effect conclusions in non-experimental research. There is no IV if you use a non-experimental design.
Null hypothesis H0: 'That gender does not have an effect on perceived intelligence at the 0.05 level of significance.'
The part of a research investigation report where you refer back to your Introduction, briefly reminding the reader the purpose of your investigation. Tell the reader what your results are and discuss what this all means,
It is also useful in a Discussion section to refer to your descriptive statistics (graphs and charts) and/or inferential to back up what you say - otherwise what was the point of doing them! Use language like 'As can be seen from Fig x on page y, .' Identify shortcomings in your investigation e.g. your design, method, sampling technique etc.
Identify remedies/suggest improvements for the future: maybe a larger more representative sample. Identify future research you might undertake (ha!!).
An experiment is a scientific procedure that adheres to the experimental method of research. For much more on this read 'Approaches & Methods'. An experiment in psychology is the only research method that can claim a cause and effect relationship between two variables. The experimental method is thus a controlled procedure involving the manipulation of an independent variable (IV) in order to observe or measure its effect on a dependent variable (DV). The experimental method is particularly popular within the biological, cognitive and behaviourist perspectives, or approaches, in psychology.
There are three types of experiments that use the experimental method, namely the laboratory experiment, the field experiment, and the quasi-experiment. The essential difference is their LOCATION, and thus the degree of CONTROL the experimenter has over variables.
Is a testable statement of cause and effect between IV and DV and is used in lab, field, and quasi-experiments.
This category of research method in psychology includes the laboratory, field, and quasi experiment. They are 'experimental' in design because they involve the manipulation of an independent variable, and consequent observation/measurement of a dependent variable. Procedures that are experimental in design thus adhere to the scientific method of enquiry in an attempt to establish a cause-effect relationship between the independent and dependent variable.
An extraneous variable is something from the outside that creeps into an experiment and gives rise to an alternative explanation for your results. Experiments are all about establishing 'cause and effect' between an independent variable and a dependent variable. Extraneous variables that pollute cause and effect conclusions in psychology are to be avoided. Extraneous variables are of two kinds, random variables, and confounding variables. Random extraneous variables just happen. You the experimenter have no control over them. They cannot be anticipated or controlled. Examples of random variables that could give rise to another explanation for your results would be in a laboratory experiment when a radiator starts making a funny noise, and distracts participants who are in the middle of doing something. Another would be in a field experiment when it starts chucking it down with rain! Confounding variables are of three kinds. Those attributed to the experimenter; those attributed to the situation; and those attributed to the participant. For more on situational, experimenter, and participant variables see 'Approaches & Methods' Chapter 8 'The Experimental Method.' You will discover more on these confounding extraneous variables and how they can be controlled if anticipated by the researcher.
Like a laboratory experiment, the field experiment also sees the manipulation of an independent variable and the consequent observation/measurement of a dependent variable. The difference is that a field experiment takes place away from a laboratory, most often in the participants' natural environment like a school classroom, a playground, or the street.
A histogram is a descriptive statistic used to represent data in a meaningful way. Find below a Histogram representing site activity at www.gerardkeegan.co.uk from October 2003 until December 2003.
An independent variable only occurs in an experiment, and is the variable an experimenter changes or manipulates to see what influence or affect this has on a dependent variable.
Inferential statistics are used to make inferences about a target population on the basis of data got from your sample. Inferential statistics are used to determine whether your results occurred by chance or random factor. Inferential statistics allow us to find out if our results are statistically significant (if there is a real effect/relationship, rather than a chance one), and allow us to reject or accept our null hypothesis. Using counter intuition we can then accept or reject our research hypothesis.
In a psychology research report your Introduction must tell the reader a bit about the topic that is being investigated, and give an account of relevant research. An Introduction in a psychology report is shaped like a funnel going from the general at the beginning to the specific, such as your aim or what it is you are investigating towards the end.
A laboratory experiment involves the manipulation of an independent variable and the consequent observation/measurement of a dependent variable. Laboratory experiments take place in the closed, heavily controlled setting of a psychology laboratory, most often found in Universities.
Level(s) of significance
A level of significance is the bet a researcher places that their results are 'real' and did not occur by chance or random factor. The level of significance is found within your null hypothesis. You get to choose it, though the convention in psychology is to opt for a 0.05 level of significance. This is the level at which you are testing your null hypothesis. 0.05 means that even if your results allow you to reject the null hypothesis you still accept a 1 in 20 probability that your results occurred by chance or random factor.
A line graph is a descriptive statistic used to represent data in a meaningful way. Find below a line graph representing site activity at www.gerardkeegan.co.uk from Monday 8th until Sunday 14th December 2003.
A statistical term for a type of average. Click on Raw Data and look at the times for participants 1-4 for Word List 1. Their mean time is 12.5 seconds (12+12+13+13 = 50/4).
A statistical term for another type of average; see mean.
The median is the middle score in a set of data. Click on Raw Data and look at the times for participants 1-4 for Word List 1. Their median time is 12.5 seconds, or the two middle scores in the array divided by 2 i.e. 12, 12, 13, 13.
A Method section in a psychology report is a heading that refers to how you conducted your research. Underneath this come 4 sub-headings viz. Design; Participants/Subjects; Apparatus, and Procedure.
This category of research in psychology includes the observational, interview, survey and case study methods of research. They are 'non-experimental' in design because there is no independent variable involved. As a result no cause-effect conclusions can be drawn when using a non-experimental method of research.
The null hypothesis is a major feature of research procedures that follow the experimental method such as the laboratory experiment and field experiment. In an experiment we have two hypotheses. An experimental or research hypothesis, and a null hypothesis. The experimental hypothesis will predict a cause effect relationship between an independent variable and a dependent variable.
Alternatively our null hypothesis will state that there will be no observed effect as a result of change/manipulation of the IV. The null hypothesis is an assumption we take to be true. If results suggest it is untrue, by counter intuition we reject the null hypothesis and accept the experimental. If results suggest it is true, we accept the null hypothesis and reject the experimental. 'If not one, then the other' is counter intuition, and is a hallmark of the experimental method. Take the following examples of a null and experimental hypothesis in an experiment, and mull them over in terms of counter intuition. Or put more bluntly think about it!! Also note how you write an experimental/null hypothesis.
Null hypothesis H0: 'That gender does not have an effect on perceived intelligence at the 0.05 level of significance.'
Experimental hypothesis H1: 'That gender does have an effect on perceived intelligence.'
In experiments we have an experimental or research hypothesis. These can be one-tailed or two tailed. A one-tailed hypothesis is one that is uni-directional. You are predicting the direction you expect the effect to be as a consequence of the manipulation of your independent variable.
Take the experimental hypothesis H1: 'That alcohol has an adverse influence on driver performance.'
This is a one-tailed hypothesis because of the use of the word 'adverse'. You are indicating that alcohol will have a negative influence or effect on driver performance. When you do not predict the direction you expect the effect to go this is called a two-tailed hypothesis.
One of the methods available to us to get a sample of people from a target population to take part in our research is called opportunity sampling. It is the most favoured of sampling methods by psychology students because it is dead easy! An opportunity sample is quite simply those who are/were available to take part in your research. If you were running an experiment and needed 20 people to take part in it, going into various college classes and getting the first 20 folk you come across is an example of an opportunity sample. This opportunity sample represents the target population of students in a college.
Order effect is one type of extraneous variable that can arise in an experiment as a result of using a repeated measures design. Order effect occurs when participants' performance is influenced by practice, fatigue or boredom! This can be as a result of being asked to do the same thing twice, as in the repetition of a measure of performance. Order effect could occur in our alcohol/driving performance example. By using the same group of people in both conditions of the IV (alcohol/no alcohol) their performance on the driving simulation test could be influenced the second time around by previous past experience of the first time they did the test. Order effect can be controlled using a procedure called counterbalancing.
In a research investigation details of participants or subjects should be given under this sub-heading as part of your Method. A participant in a psychology investigation is a person, while a subject is an animal. You would in a participant sub-section for example indicate the number of people who helped you in your research, how many were male, how many female, ages/age range, and any other pertinent detail about them. Personal stuff like participants' names should never be given.
Pilot study / Pilot Survey
Essentially a 'dummy run' of your research. If you were conducting a survey you would get half a dozen people to complete your survey form. Their job is to tell you about any ambiguities they find, or any improvements they think could be made. You take their advice on board and pilot until you get something useful.
This is the most crucial sub-section of the Method section of any psychology research report. It comes after stating your Design, Participants/Subjects and Apparatus. Anyone using the same design, sampling technique, and apparatus should by following your Procedure be able to replicate your research and come up with the same results.
In your Procedure section tell the reader exactly what you did from the minute they entered your 'laboratory' until the minute they left.
Then say you thanked your participants, that they were debriefed (given the true purpose and nature of the study), and that they got a chance to themselves read your report at a later date.
Data that reflects how individuals feel about something. Qualitative data is subjective, personal, opinionated data got when using a non-experimental method of research such as the interview, case study etc.
A measure or a count of something. Quantitative data is objective, factual data.
Raw data is the information you collect regards participant performance/behaviour in a research investigation. An example of raw data would be the time it takes a participant to read a word list. The wise student enters this into a pre-prepared Raw Data Chart such as the one below to be typed up properly later. Your Raw Data Chart forms the basis of your descriptive statistics, and inferential statistics.
This is where you state in the globally accepted format known as the Harvard referencing system the primary source of any psychologist, psychological theory, or study DIRECTLY referred to in the text.
If you for example used a statistics book to help you do your 'sums' this would go in a Bibliography underneath the Reference section.
Where things go e.g. surnames first, initials etc. is the Harvard referencing system. Also note that journal articles are written differently from information got and referred to in a study from books. The use of italics is thus deliberate. If in doubt about how to cite references using the HRS please talk to your school/college/university librarian. They are your resident experts on this.
A type of inferential statistic used when certain statistical conditions are met, and when participant data is related. Usually as a result of a repeated measures design.
In psychology means does something measure what it claims to be measuring in a consistent fashion?
Repeated measures design
A repeated measures design occurs in an experiment when you repeat the measure of performance under the differing conditions of the independent variable with the same group of participants.
Take an experiment investigating the influence of alcohol on driver reaction time. The two conditions of the IV would be a 'no-alcohol' condition, and an 'alcohol' condition. Measure of performance or dependent variable would be a driving simulation test. On one day the participants would undergo condition A (no alcohol) and do the driving simulation test. The DV is of course recorded errors on the test. On another day the same participants would undergo condition B of the independent variable (given alcohol) and once again asked to sit the driving simulation test. Number of errors would again be recorded. This is a repeated measures design.
RMD's suffer from order effect that can skew your results. Order effect can be overcome using counterbalancing.
Reflecting a target population.
A hypothesis is a testable statement. In psychology, research hypotheses fall into two categories, the experimental hypothesis and the correlational hypothesis. An experimental hypothesis (H1) is used in experiments! It is thus a testable statement of cause and effect between two variables called the independent and dependent variable. Your independent variable (IV) is the one you manipulate or change, while the dependent variable (DV) is the one you observe or measure as a consequence. Just to confuse you (!), sometimes an experimental hypothesis is also referred to as the alternate hypothesis or HA. It is alternate to the null hypothesis.
An example of a research/experimental hypothesis is H1: 'That gender has an influence on perceived intelligence.' Another would be HA: 'That alcohol consumption affects driver reaction time.' Etc.
When using a statistical technique called a correlation we set a correlational hypothesis to measure or test the strength of statistical relationship between two co-variates. A co-variate is anything that is free to vary in itself e.g.¹ Hours spent studying; Examination mark E.g. ² Hours spent socialising; Examination mark etc.
In a results section of a research investigation you present your raw data in a statistically meaningful way, which if (sensibly) doing an experiment or correlation allows you to accept or reject your null hypothesis, and then by counter intuition reject or accept your research hypothesis.
To do this use some descriptive statistics and inferential statistics.
A sample comes from a larger target population.
In psychological research it is often impossible to investigate everyone in a target population. Hence the reason we use a sample from a target population instead. If your sample is representative of the target population, and if it is unbiased, then you can generalise your results and conclusions onto the target population.
For an example of a sample that is neither representative nor unbiased, but frighteningly went to make up the conclusions to a vital report on the future of psychology in Scotland, please read the erroneously entitled 'Consultation Methodology' in the SQA National Qualifications Review Investigation Report: Psychology August 2003.
Look closely at the numbers who have been presented in Higher psychology since its inception. Look at the number of student respondents contacted by e-mail questionnaire! Were all who made up this sample sitting in one particular year or were they from different years? What percentage of the total of psychology candidates ever presented does this miniscule sample represent? In statistical terms absolutely no one!
As examination bodies do not hold e-mail addresses of students sitting their examinations how did the writer of this document know who/how to contact to ask them if they wanted to take part in the first place? Some possibly three years after they left school!? This sample must have been pre-selected by the researcher. This is a mortal sin in psychological research. The sample used in this horrendous piece of research is neither representative, nor randomly selected. As a result its conclusions are highly suspect.
To ensure better control in psychological research it is important that any instructions given to participants are standardised. This means that all receive the same instructions, after they have been rigorously checked for ambiguity before the research itself takes place. This is done using a pilot study.
A target population is the one from which a sample of participants in psychological research is drawn. It is the population to which a researcher wants to generalise their results. This is only possible if the sample selected is representative of the target population.
The title of a research investigation should reflect what it is about. It should be short, and indicate the area of psychology that is being investigated e. g. 'An investigation into serial verbal reactions: the Stroop Effect' etc.
This is an inferential statistic to test the significance of our results regards the population from which our samples have been drawn. We use the likes of the t-test to find out if there is a real or significant difference in performance. This would be as a consequence of manipulating/changing the independent variable in one condition, and then another. Testing for significance means finding out if results occurred by chance or random factor. There are two versions of the t-test. The related t-test used when data is related - as in a repeated measures design. There is also the unrelated t-test, which can be available when our data comes from unrelated samples as in an independent group/sample design, and other conditions of its use are satisfied. For further details see the likes of Hugh Coolican Research Methods and Statistics in Psychology.
In experiments we have an experimental or research hypothesis. These can be one-tailed or two tailed. A two-tailed hypothesis is one that is non-directional. You are predicting an effect, but not the direction you expect the effect to go.
Take the experimental hypothesis H1: 'That gender has an influence on perceived intelligence.'
This is a two-tailed hypothesis in that while you are predicting gender will have an influence on perceived intelligence of oneself/another, you are not predicting whether the effect of gender will be positive or negative. When you do predict the direction youexpect the effect to go this is called a one-tailed hypothesis.
In psychology means does something measure what it claims to be measuring: e.g. does an intelligence test measure intelligence.
Name given to horizontal line that runs along the bottom of a graphical descriptive statistic like a histogram or line graph.
Name given to vertical line that runs from top to bottom at the left hand side of a graphical descriptive statistic such as a histogram or a line graph.
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