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Lecture 6

PSYB01 - Lecture 6 Typed.docx

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Connie Boudens

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PSYB01 1 Lecture 6 Experiments Example to demonstrate importance of experimental design:  taste test comparing diet Pepsi and diet Coke  Pepsi was in a bottle that was opened prior – to air it out, it was also warm & not fizzy  Coke was just bought minutes before the experiment and had ice in it = cold and refreshing  problems with experiment: o the experimenter was hinting at which one would taste better and be more refreshing o the identity of the products was not concealed – could have influenced which one the participant liked better o the two products should have been presented in exactly the same fashion – the only thing that should be manipulated is the brand of the products  they should both be at the same temperature, carbonation, in the same container, etc. Problems with establishing causality in correlational research  if you want to look at the relationship between two variables you can just collect the information on them and look at the correlation coefficient - strong positive, strong negative, no relationship  some other variables shown to be related to each other: o eating breakfast and academic performance of school aged children – if children eat a good breakfast their academic performance is better o eating disorders and watching soap operas in teenage females – teenage females who watch soap operas are more likely to have an eating disorder than teenage females who don‟t watch soap operas o these things are found to be correlated with each other BUT doesn‟t mean that one things cause another o for example, if you eat breakfast you are maybe doing better in school because you‟re better able to pay attention because you‟re not hungry – can focus you‟re energy on learning instead of listening to your stomach rumble o correlational results ONLY tell you if two variables are related to each other – can‟t tell you in what way they are related or which one causes the other or if one of them actually causes another or if there is a third variable at play o in order to answer causal questions experiments must be done!  Direction of influence problem o Class attendance and grades – strong correlation between the number of times people attend class and what their grades are like o Most people will think if students go to class more often this will result in higher grades but this may not be the case o It could be that class attendance results in a higher grade BUT it could also be that people who get good grades are more likely to go to class o Higher grades – makes them want to be in class more because they get good feedback, feel good about being in the academic environment = therefore get higher grades o Question of directional causality – which one is actually causing which PSYB01 2 Lecture 6  Third variable problem o Other problem with inferring causality from correlational results o There is third variable that is causing a change in both of the variables you correlated o Example: research shows that positive mood and charitable donations are related to each other – positively correlated  May be a third variable involved causing those things  Having just gotten paid can cause a change in both of these variables – having money in hand puts them in a good mood and also makes it more likely they will make a donation o Example: correlation between ice cream sales and drowning  But actually a third variable – temperature – is causing a change in both of these variables  When temperature is really high ice sales go up and more people go swimming – the more people go swimming the more people drown o Sometimes can have a direction of influence problem and a third variable problem  Depressed mood and impaired sleep  Those who suffer from depressed mood have a lot of sleep disturbances  It could be that depression is causing disturbed sleep or vice versa – question of direction of influence  But it could also be that family problems ( a third variable) is causing both impaired sleep and depressed moods  Other stresses can also cause a change in both of these variables  For example: just because every time there is a cat there is food all over the place doesn‟t mean the cat is putting food all over the place Three things needed to establish causality via experiments – must include the following factors  Temporal order must be correct o Cause has to come before the outcome o In correlational research unless it has some longitudinal component where you can tell what happened first you can‟t establish what came first  Variables have to covary o As one changes the other must change – ex. as one goes up the other one goes up  No other variable is causing the outcome o For example, in the taste test must make sure that the only difference is the drinks themselves  Keep all extraneous variables the same – such as the temperature of the drink, how it was presented, what the experimenter says  If all extraneous variables are controlled they have still have an influence but the influence on all participants is the same  If there‟s anything you can‟t hold constant or control – solution = random assignment; on a random basis you assign participants to one condition vs. another via random numbers table/pulling numbers out of a hat o If you have two conditions you have to put participants in = put the number 1 and 2 in a hat then draw one number and put it back in the hat, draw another number PSYB01 3 Lecture 6 put it back in the hat, etc. – over time should draw both of the numbers equal amount of times o Every participants has equal chance of being put into one condition vs. another condition  In experiments always present the independent variable first – this takes care of the temporal component – independent variables causes dependent variable so it is always presented first  Present the independent variable carefully and consistently, measure the dependent variable rigorously o Taste test – present drinks in exactly the same way ( same temperature, cups, etc.) and say exactly the same thing to participants – and take care of anything else the participant might react to in the experiment o Dependent variable – preference for drink – be careful about the measurement and operationalize the dependent variable in a meaningful way Extraneous vs. confounding variable  Confounding variables are related to the independent variable – they vary along with the independent variable, to the point that its‟ hard to see their separate effects  Extraneous variables are anything other than the independent variable that could have an effect on the dependent variable  Confounding variables are a subset of extraneous variables – type of extraneous variables  All confounding variables are extraneous variables but not all extraneous variables are confounding variables  Examples: o Temperature of drink confounded with the type of drink – one drink was warm and one was cold o If a man does something he has to apologize for, does the gazing behaviour predict if he will be forgiven  Length of relationship confounded with gaze behaviour – Kobe Bryant got accused of sexually assaulting another women but denied the rumours and said it was consensual and apologized to everyone including wife in a press conference – his wife was gazing at him at the entire time  Gazing at him with a loving expression – does the amount of gazing time predict whether a women will forgive him?  Can we estimate the probability a women is going to forgive a man based on how much time she spends looking at him during the press conference where he apologizes  BUT confound between length of relationship and gazing  Newer couples spend more time looking at each other compared to couples who have been together longer - therefore gazing behaviour may not be good way to predict if she‟ll forgive him How experiments allow you to do this  Hold all variables constant  Use random assignment  Present i.v. first PSYB01 4 Lecture 6  Present i.v. carefully and consistently, measure the d.v. rigorously Basic experimental design  One independent with two levels o Experimental group AKA treatment group – where they encounter some sort of experimental stimulus/treatment o Control group – no experimental stimulus o There should be no difference between the two groups except for the independent variable AKA experimental stimulus o May not explicitly have a control group – may just be contrasting two groups  One dependent variable  When testing drugs usually have one group of participants who get the drug vs. one group gets a placebo (sugar pill) but two pills look exactly alike – DV = health outcome such as blood pressure  Everything else about the study is the same, even the people who are administering the pills don‟t know which one is which – only content of pill difference  Example: o Effects of noises (I.V.) on memory (D.V.) – example of basic experiment o Experimental group – memorize words in a loud room – look at performance on a memory task o Control group – memorize words in a quiet room – look at performance on a memory task o Look at if there is a difference in the performance of participants in different groups o I.V has two levels – quiet vs. loud condition o D.V = performance on a memory task o Random assignment to the condition is important because you want to make sure people who get assignment to the experimental group are the same as the people who get assigned to the control group – same as far as the individual difference variables go – so that differences you find are only due to noise level and have nothing to do with how people are o One thing you don‟t want to do is find people studying in a loud area and put them in the experimental group and find people studying in the quiet room in the control group – because the differences you find may be due to individual differences and how they prefer to study o In each of the I.V. levels – you should have an equal number of people who like to study in different types of noise levels – this is what random assign does for us – allows us to see the difference due to noise only and prevents systematic groups between differences  Can add a pre-test measure – to ensure there‟s no pre-existing differences between the groups o Ensure that the groups are equivalent Pretest- posttest(measuring D.V.) design  Pretest makes sure groups are actually equivalent – extra check to make sure groups are the same PSYB01 5 Lecture 6 o Ex: checking if average ability of people to memorize things is equivalent before you put them in different noise conditions o The average memory ability of both groups should be the same  Identify people with high/low pre-existing characteristics – so that you can figure out if there is an interaction o For example, if you want to see if being an introvert vs. extroverts has an effect on how people do in different noise levels and memory  In case of mortality = people dropping out of the experiment o Sometimes you‟ll have people who won‟t finish the experiment especially if the experiment takes place over a long time o May drop out for a number of reasons – not a problem as long as people who drop out of the experiments in both groups are the same otherwise you end up with groups that are different o For example- in the noisy condition (crowd noise) – people who don‟t like crowds may drop out because their introverts – will wind up with people in the noisy conditions who already like to be in crowds o Whereas quiet room will have the same amount of people who like crowds and don‟t like crowds – experiment will be flawed because groups will be different o Pretest will give you an idea of which type of people dropped out and whether this has effected your results  Measure change in each individual o Intervention where you show people how to pouch eggs – to see if people actually learned and improving pouching skills must look at before and after experiment results and compare Independent groups vs. repeated measures  Independent: all p‟s exposed to one level of i.v. – this is also called a between groups design because looking the difference between groups (participant only in the control or experimental group not both) o Seen most often  Repeated measures: all p‟s exposed to all levels of i.v. – also called a within groups design - participants apart of control and experimental group  Advantages: o less participants – participants exposed to both conditions so only need half the number of participants  sometimes it is difficult to get participants – for example experiment on certain amnesia = limited population, may be hard to recruit participants o No individual differences  Something about the individuals that makes one group different from another = problem if you wind up with one type of people in one group over another  For example, more extroverts in noise level  In repeated measures won‟t have this problem because each participants serves as a control for themselves – have the same people in each group so PSYB01 6 Lecture 6 don‟t have to worry about there being fundamental differences between the groups due
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