SPEAKER 1: Steps in Planning and Conducting Research.Sir Isaac Newton explained gravity and planetary orbit.Louis Pasteur said the tiny bacteria can cause disease.Benjamin Franklin claimed that lightening
SPEAKER 1 [continued]: is electric in nature.All of these greats had something in common.They used scientific research to learn about the world.They took the knowledge they had acquired from others,came up with new ideas of their own, and tested them.These are all essential parts of what iscalled the scientific method.
SPEAKER 1 [continued]: If we know how to conduct research,we can go about answering questionsabout the nature of the environment, medicine,human beings, animals, and a host of other topics.Conducting research helps us figure out cause and effectrelationships.For example, which environmental conditions
SPEAKER 1 [continued]: cause bees to produce the most honey?Which fertility treatments will helpthe most women get pregnant?Which cancer medicine shrinks tumorswith the fewest side effects?Understanding research methods alsomakes us better consumers of research.If we're reading about a study in the newspaper,
SPEAKER 1 [continued]: we'll have a better idea of whether or notwe believe the results.Or if we're advised to undergo a medical procedure,we can read the related research that has been published,and decide whether we feel the potential benefits outweighthe risks.Let's explore the steps of scientific inquirythat will improve your ability to draw reliable conclusions
SPEAKER 1 [continued]: in your own research, and analyze published research morecritically.We'll focus on eight steps.Choose a topic.What do you want to learn about?Generate a hypothesis.What relationship do you suspect there may be between phenomena?Select and define variables.
SPEAKER 1 [continued]: Between which specific variables wouldyou like to find a relationship?Identify participants.What population are you interested in studying?Design the study.How can you observe the phenomenain a controlled setting?Plan and conduct the research.What are the specific steps you will
SPEAKER 1 [continued]: take to test your hypothesis?Analyze results and draw conclusions.How can you use your data to bolster or reviseyour hypothesis?Share your findings.How can you tell others what you have done,so that they can repeat and strengthen your results,or learn from your mistakes?
SPEAKER 1 [continued]: Let's look at each of these steps individually.Choosing a Topic.The first step in research is to choosea topic and a general research design,which means figuring out what you want to learn about,
SPEAKER 1 [continued]: and how you can best learn about it.Some of the most common types of research designsare observational, correlational,and experimental.Observational studies allow you to merely examinethe nature of a particular construct, that is a variablethat you are interested in.
SPEAKER 1 [continued]: For example, you might be interested in determiningwhat percentage of the population abuses alcohol.Correlational studies allow you to examinethe relationship between two or more different constructs.For example, you might want to knowwhether alcohol use increases as depressed mood increases.
SPEAKER 1 [continued]: Experimental studies allow you to examinethe causal effects of one variable on another variable.For example, you might want to studywhether drinking alcohol causes your motorreflexes to become slower.Next, identify your variables.
NICOLE CAIN: A variable, sometimes known as a construct,is a special topic of interest thatvaries from person to person.A person can score high on your variable,or they can score low on your variable.
SPEAKER 1: A variable, or a construct,is a phenomenon that can be measuredat higher, or lower, levels dependingupon the subjects of your study, whom or what you're observingor acting upon, and the circumstances under whichyou are studying them.Some examples of variables that are studiedin the social sciences are intelligence, aggression,
SPEAKER 1 [continued]: depression, racial prejudice, and memory.
EVELYN BEHAR: There are going to besome people who are extremely intelligent,some people who are of average intelligence,and some people who are of low intelligence.Another variable that's often studiedis aggression, or violence.Obviously in the population, you'regoing to have some people who are very, very violent,some people who have maybe some tendencies towards violence,but it inhibit it, and then some people who are not
EVELYN BEHAR [continued]: at all naturally violent.
SPEAKER 1: Next, you will need to ask a question thatis scientific in nature.In other words, ask about the relationship between onevariable and another.You could choose to ask questions such as, whatis the impact of depression on family relationships.What is the impact of racial prejudice on juror perceptions?
SPEAKER 1 [continued]: Or what is the impact of anxiety on memory?When creating your study, it is important to choose a topicthat you can actually measure.If you were a botanist, it would befairly easy to measure the effect of wateringa plant on the plants growth by controllingthe amount of water you give the plant,
SPEAKER 1 [continued]: and physically measuring how big the plant gets.Other studies, such as those in the social sciences,can be more complicated.
NICOLE CAIN: Some populations, or constructs,need special considerations in order to be measured.One example of that would be if youwere interested in examining how brain activity playsa role in depression.You would first need to make surethat you have a way of measuring brain activity before startingthe study.
EVELYN BEHAR: If you're interested in studyinggenetic transmission in schizophrenia,you obviously are going to need a wayto measure genetic transmission.So you're going to have to have accessto some sort of DNA testing technology,in order to ultimately answer your question.
NICOLE CAIN: Another example of thatwould be if you were interested in racial attitudes of jurymembers.You would want to have participantswho are actual jurors, but that might not always be possible.So you would need to create what'scalled an analog situation.
EVELYN BEHAR: An analog situation is essentiallywhen you ask your participants to pretend that theyare in a particular situation.So you might ask your participantsto imagine that they are members of a jury,and to listen to the case before them,and then to answer a series of questions.What you might want to do, in these cases,
EVELYN BEHAR [continued]: in order to establish what's a much morebelievable analog situation, is do something like set upyour laboratory to look like a courtroom,so you could have a judge, you could have a bailiff,you could have attorneys.And you could really, if you put enough money and time into it,you could really make your laboratory look very realistic.
SPEAKER 1: To summarize, you'll needto make sure that you have the technology neededto measure your variables, as well as a setting thatis conducive to accurate replication of participants'behavior.Before you settle on a research question,you'll want to take the time to read the scientific literatureto make sure that your question hasn't been answered
SPEAKER 1 [continued]: in past studies, and that there is a good theoretical basisfor asking the question.Generate a Hypothesis.By the time you finish reading the scientific literatureabout your topic, you'll probably
SPEAKER 1 [continued]: have an idea as to what impact youthink your first variable has on your second variable.This is a hypothesis.
NICOLE CAIN: A hypothesis is a predictionabout how your variables of interestswill relate to each other.Hypotheses should be based on previous research.It's not good enough to just takea wild guess about how your variables would relateto each other, you need to look at what other researchers havefound to be true.
EVELYN BEHAR: So let's say, for example,that you know based on past researchthat when people are anxious, they tendto have poor memory skills.And you want to now come along and run an actual experimentto look at the causal relationship between these twothings.So you want to ask the question, if people are anxious will that
EVELYN BEHAR [continued]: cause them to have poor memory.
SPEAKER 1: A hypothesis takes the formof an if then statement.In a correlational study, in which we are just observing,you may predict that if a certain condition exists,then it is more likely, or less likely,for some other condition to exist.In an experiment, you will be looking for cause and effect.
SPEAKER 1 [continued]: So your hypothesis will be along the lines of,if a certain action or circumstance is imposed,then a certain outcome will take place.Select and Define Variables.
SPEAKER 1 [continued]: Selecting and defining your variablesis one of the most important steps in the research process,because choosing good variables, and good definitionsof those variables, may make the difference between findinginteresting results, and not finding anything useful.
NICOLE CAIN: All experiments are made upof two different types of variables,independent variables, and dependant variables.The independent variable is a variablethat is active in your research study.It's the variable that you, as the experimenter,manipulate during the course of your study.So for example, you could be interested in studying
NICOLE CAIN [continued]: the effects of mood on memory.So you can bring people into the lab,and induce a mood in them-- a positive moodor a negative mood-- maybe through having themwatch sad or happy movie clips.Your independent variable would be the mood statethat you were inducing in your participants.In contrast, the dependent variable is a passive variable.
NICOLE CAIN [continued]: It's the variable that the independent variable acts upon.It's the variable that you're measuring as part of the study.So to use our example, the recall of the list of words,or the number of words that they can remember,is your dependent variable.All experiments must have at least one independent variablethat would have at least two different levels.
NICOLE CAIN [continued]: In our example, it would be the positiveversus the negative mood.In addition, all studies need to have at leastone dependent variable.
EVELYN BEHAR: So just to recap, the independent variableis the active variable, it's what youmanipulate as an experimenter.And the dependent variable is the passive variable,it's the thing that gets measured.It's the thing that is acted upon.
NICOLE CAIN: All variables can beexpressed in two different ways, conceptually or operationally.When you define a variable as conceptual,it's the general more abstract wayof thinking of your variable.When you want to be more specific,you look at the operational definition of your variable.This is the more specific and concrete wayof thinking about how you're going to measure or manipulate
NICOLE CAIN [continued]: your variable.
EVELYN BEHAR: Intelligence, which is a variable,is really a conceptual variable.It's kind of abstract.You want to be able to measure it in some concrete way,and you're going to operationalize itby perhaps giving people an intelligence test.
SPEAKER 1: Remember, conceptual variables are general.Operational definitions are specific.Your independent variable, which you manipulate,can be applied at two or more levels.If you include only two levels-- for example,if you have participants in your study on sleep deprivation--
SPEAKER 1 [continued]: get no sleep or a full night's sleep,you can find only a linear relationshipbetween the levels.In this case, it will appear that therewas a clear effect of sleep deprivation on depressed mood.Participants who got no sleep at all are in a depressed mood.And participants who got a full night's sleepare in a fine mood.
SPEAKER 1 [continued]: If you include three or more levels-- for example,no sleep, four hours of sleep, and eight hours of sleep-- thenyou may end up with a non-linear relationship, whichcould tell you something more complexabout the relationship between sleep and depression.In this case, it appears that getting no sleepand getting a full night's sleep may both lead to a fine mood,
SPEAKER 1 [continued]: while participants who got only four hours of sleepare in a depressed mood.Identify your Participants.The next step is to choose your participants.Who will be part of your study?
SPEAKER 1 [continued]: You may be interested in learning about everyonein the world, but more likely you'll choosea more specific population.
NICOLE CAIN: There are many different populationsthat researchers can draw from.Some of the examples would include high school students,college students, patients in mental health setting,or prisoners.Once you've identified your population,you must select your sample.Your sample is a subset of the populationthat you want to study.
EVELYN BEHAR: As researchers, we'reinterested in potentially many different populations.So for example, one researcher maybe interested in prisoners, another researcher maybeinterested in psychiatry in patients,yet another researcher might be interested in infants.Let's say that I am interested in prisoners.This is the population that I'm interested in.
EVELYN BEHAR [continued]: Now once I have established that,I need to select my sample, whichis a subset of the population.Ideally it would be lovely if I could go out there and measureevery single prisoner in the world,but obviously that's not realistic.It's going to be too expensive, it'sgoing to take up too many resources.So instead, I'm going to select a sample.Say I select a sample of 200 prisoners.
EVELYN BEHAR [continued]: One thing that I need to take into considerationis the idea of selecting a random sample.And what that means is that every single personin that population of prisoners--that means every prisoner in the world--has an equal chance of ending up in my study,ending up in my sample.That's a random sampling.And this is an ideal in research.
EVELYN BEHAR [continued]: This is something that we strive for,but we often can't actually get there, and this is why.Let's say that I live in Pennsylvania,and around me there are 10 different prisonsin the state that I could go and measure prisoners.And that's great, and that's probablywhat I'm going to end up doing as a researcherin Pennsylvania, but when I get my results
EVELYN BEHAR [continued]: we have a potential problem.The potential problem is that I may be answering questionsabout prisoners in Pennsylvania.I may not be answering a question about prisonersall over the world.Perhaps there is something different about prisonersin New York, or Florida, or Californiarelative to prisoners in Pennsylvania.
EVELYN BEHAR [continued]: So even though I'm going to strivefor getting a random sample from my study,it's probably unlikely that I'm actuallygoing to be able to get a truly random samplein my investigation.The truth is, all research investigationsare limited in terms of which the sample we're selecting.And if you think about it in the most simple term,
EVELYN BEHAR [continued]: even just picking up the telephone,and calling a potential participant alreadyensures that you don't have a truly random sample.That's because there are some people in the world whodon't have a telephone.So by definition, you are systematicallyexcluding those people who don't own a telephone, perhaps peoplein very, very rural areas.
SPEAKER 1: Select an Appropriate Design.At this point, you have a hypothesis and a population.You know what you're studying, and you know whowill participate in your study.How will you conduct your study?You are now ready to select design features that
SPEAKER 1 [continued]: will help you find answers.There are two main decisions you need to make.The first decision is whether to have more than oneindependent variable.If you choose to have only one independent variable,this is called a one-way design.This type of experiment is relativelysimple and straightforward.
SPEAKER 1 [continued]: Remember that even in a one-way design,you can include more than two levelsof the independent variable, so that youcan draw nonlinear conclusions.A factorial design has more than one independent variable.It is usually beneficial to use a factorial design,because it is very rare for only one construct, or variable,
SPEAKER 1 [continued]: to be influencing a dependent variable.
EVELYN BEHAR: It's really important to try, if you can,to have more than one independent variablein your study, and here is why.Let's say that you are interested in the effectsof sleep deprivation on mood the next day.So we all know that when we've been sleep deprived,maybe we can be a little bit crabby the next day,or a little bit overly sensitive.However it's unlikely that sleep deprivation
EVELYN BEHAR [continued]: is the only thing that's impacting mood the next day.It's probably the case that thereare lots of variables that could impactyour mood the following day.So ideally, in addition to sleep deprivation,you might want to also have a measureof people's relationship problems, maybe their foodintake, because we know that these are also variables that
EVELYN BEHAR [continued]: can impact the next day's mood.So again, just to recap, you want to make sure if you can,whenever possible, to not only have one independent variablein your study, but to have multiple ones,because in the real world we're not just affectedby only one variable.We're affected by lots of variables in our lives.
SPEAKER 1: If you examine two or more variables,you'll get a more complete pictureof what is impacting your dependent variable.If you're using a factorial design,you'll need to keep track of which levelof each independent variable is being applied in each case.The method for keeping track of these combinationsis called factorial notation.
SPEAKER 1 [continued]: For example, you may choose to havethree independent variables-- sleep deprivation, caffeineintake, and life stress.You may have three levels of sleep deprivation,two levels of caffeine intake, and three levelsof life stress.This would be called a 3 by 2 by 3 factorial design.
SPEAKER 1 [continued]: There are three numbers, because thereare three independent variables in the study.Each of these numbers tells you how many levels exist,within a given independent variable.The first three tells you that thereare three levels of sleep deprivation-- no sleep,four hours of sleep, and a full night's sleep.
SPEAKER 1 [continued]: The two tells you that there are two levels of caffeine intake--one cup or three cups.The second three tells you that there are three levels of lifestress-- low, medium, and high.In this example of factorial design,you'll have 18 unique conditions, or cells.
SPEAKER 1 [continued]: You find this number by multiplyingthe number of levels within each independent variable.Here you multiply 3 by 2, which is 6,and then multiply that by 3, which brings you to 18.If there were more independent variables,you would continue to multiply by the next number of levels.The product-- which is 18 in our example--
SPEAKER 1 [continued]: tells you the number of cells in the experiment.Using a factorial design is more complicated,but it allows you to ask more realistic questions,and create a scenario that is closer to the real world, wheremore than one variable affects the dependent variable.
SPEAKER 1 [continued]: The other major decision you needto make in designing your experimentis whether participants will serve in one, or more than one,cell of the study.In between-subject designs, each participantserves in only one cell of the experiment.For example, in the sleep deprivation study,you would need 360 different participants
SPEAKER 1 [continued]: in order to have 20 participants in each cell.That is 20 participants times 18 cells.On the other hand, if your plan isto have participants serve in more than one cell,you have within-subjects design.In our example, you might take the life stress variable,and make it within-subjects variable.
SPEAKER 1 [continued]: You would then expose each participantto each of the three stress levels,and measure their mood after each one.Plan and Conduct Research.Once you have determined who your participants are,
SPEAKER 1 [continued]: and what kind of study you are conducting,you can begin the hands on creation of the experiment.This means setting up your laboratory,so that it is appropriate for your study, which sometimesmeans transforming it into something that no longer seemslike a laboratory at all.An important concept in creating your study
SPEAKER 1 [continued]: is experimental realism.
NICOLE CAIN: Experimental realismmeans that you want to try to set up your laboratory as closeas possible to a real world.So for example, if you're interested in lookingat attitudes of jury participants,you would want to actually take the time and effortto set your laboratory up, so that it lookslike an actual court room.It gives the participants in your research study
NICOLE CAIN [continued]: a chance to act naturally, and act as though theywere actually in a court room, giving you more real life data.
EVELYN BEHAR: You might not get there 100%,but you can at least increase the likelihoodthat you're going to get individuals, participantsin your study, actually behaving as they normally would.
SPEAKER 1: Another thing to rememberwhen you're running an experiment is that youmust randomly assign your participantsto the various conditions.Without random assignment, you do not have a true experiment.Non-random assignment could lead to biased assignment.
EVELYN BEHAR: One of the hallmarks,if not the hallmark of an experimental study,is the idea of random assignment.So when you are creating or designing an experiment,you want to make sure that you are randomlyassigning your participants to the different conditionsof your experiment, and you want to do itin a way that is not at all biased.
EVELYN BEHAR [continued]: So very old-fashioned, but very effective way,is to literally flip a coin, and decideis the participant going to end upin condition a or condition b.And you want to be very careful.You don't want to let your emotions get in the way.So let's say that the first participant whoarrives for your study is a woman named Mary,
EVELYN BEHAR [continued]: who is clinically depressed and here for a studycomparing cognitive behavioral therapy for depressionto a wait list comparison condition.And you flip your coin and it lands on tails,and that means that Mary is about to gointo the weightless condition.And you haven't even told Mary, yet but Mary is all ready.
EVELYN BEHAR [continued]: She's crying, she's weepy, she's telling youabout all of her life problems thatgo along with her depression.And it starts to pull at your heartstrings a little bit.And you say to yourself, I just don'thave the heart to put Mary in the weightless condition.I'm going to save the weightless conditionfor someone maybe who's suffering a little bit less.And I'm going to go ahead and putMary in the active treatment condition,because I really care about Mary, and I like her,
EVELYN BEHAR [continued]: and I want her to get better.Even though you're being very sensitive,you have broken one of the cardinal rulesof experimentation, which is to stick to the random assignmentplan.So when somebody comes in and youflip that coin, you absolutely, without any exceptions,you must put them into the condition
EVELYN BEHAR [continued]: to which they've been assigned.
SPEAKER 1: Now you're ready to run the experimentand collect the data.This is the crux of the matter, though it is crucialthat you complete the previous steps so that your study yieldscredible information, and the upcomingsteps so that you can share what you've learned with others.
NICOLE CAIN: So it's important for youto standardize your entire studies,so that all participants in your studyundergo the exact same condition.So for example, if you were interested in studyingpersonality traits of criminals versus non-criminals,you want to make sure that you'reholding all things constant in your study,and that you're treating both groups equally.
NICOLE CAIN [continued]: This will ensure that there are no differences between the twogroups, except for your experimental manipulation.
EVELYN BEHAR: Every person who walks into your laboratoryfor that study, no matter which condition they're in,gets the thing treatment and lots of different levels,except for that one independent variable.So how do you make sure that you're treatingeverybody exactly the same?You might want to have a script that the experimenter follows.You want to make sure that everybody
EVELYN BEHAR [continued]: is going into the same room.Also it would be helpful if the research assistant,or the experimenter, were naive about the whole purposeof the study.So when you have this person working for you,and meeting with all of the different participants whocome through the door, that personshould not know what the hypotheses of the study are.
SPEAKER 1: Analyze Results and Draw Conclusions.Data analysis can be very complex, and becoming an expertrequires many years of instruction.But there are some basics you should know.Before you begin an in-depth analysis,
SPEAKER 1 [continued]: you may want to create a rudimentary graph,so that you can see if any patterns jump out at you.Your independent variable will be along the x-axis,and your dependent variable will be along the y-axis.One of the first things you want to look foris central tendency, or participants'typical performance on your variables of interest.
SPEAKER 1 [continued]: There are three measures of central tendency.The first measure of central tendency is the mean,this is the average of a distribution,usually calculated separately for unique conditionsof an experiment, so that can later be compared.Each mean is the average of all the scores for a givencondition, or set of conditions.
SPEAKER 1 [continued]: They are added up and divided by the number of participantsin that group.The second measure of central tendency is the median.Unlike the mean, which takes the average of all of the scores,the median is the middle number in a distribution of scores.If there are 25 participants in a group,
SPEAKER 1 [continued]: and you write out their scores in ascending order,the median will be whatever score appears 13th,or right in the middle.The third measure of central tendency is the mode.The mode, is the most commonly recorded valuein a distribution of scores.
SPEAKER 1 [continued]: For non-experimental research, though you are notmanipulating the variables, you caninvestigate more than one variable,and analyze your data for correlations.These correlations do not tell you about cause and effect,but they do tell you about the relationshipbetween two variables.Correlations range from negative 1 to positive 1.
SPEAKER 1 [continued]: A positive number means that thereis a positive relationship between the two variables.In other words, as one variable increases, so does the other.A negative number means that thereis a negative relationship between the two variables.As one increases, the other decreases.
SPEAKER 1 [continued]: The size of the number tells you the magnitudeof the correlation.The closer the value is to the extremes, that is to positive 1or negative 1, the stronger the relationshipis between the two variables.For example, 0.9 stronger than 0.3.3 Negative 0.4 is stronger than 0.2,
SPEAKER 1 [continued]: even though one is negative and the other is positive.When we conduct experiments, we'retrying to find cause and effect by manipulatingthe independent variables.Analyzing the data from experimental studiesdiffers depending on the experimental design.Let's first look at one-way designs,
SPEAKER 1 [continued]: experiments with just one independent variable.To understand the results of your study,you'll statistically compare the means of the different groups.In our earlier example-- examiningthe effect of sleep deprivation on mood--we had three levels of sleep, no sleep, four hours of sleep,
SPEAKER 1 [continued]: and a full night's sleep.Let's assume you measured depressed mood using the BeckDepression Inventory , or BDI.You might find the following.Participants who got no sleep had a mean BDI of 26.Participants who got four hours of sleep had a mean BDI of 18.
SPEAKER 1 [continued]: Participants who got eight hours of sleephad a mean BDI of eight.Here you would run a T-test to statistically testfor differences between the three levels of sleep,and the results of the test would tell youwhether those three levels yielded significantly differentvalues on the dependent variable-- that is,
SPEAKER 1 [continued]: depressed mood or BDI.This is necessary in order to draw conclusions, whichwe will talk about shortly.For factorial designs, experimentswith more than one independent variable,you will run an analysis of variance, or ANOVA.The ANOVA allows us to answer questions
SPEAKER 1 [continued]: about the effects of each of the independent variables,and the possible interaction between or among them.Let's consider a 2 by 2 factorial design.This is the most common type of design in research studies,and it will enable you to walk through the ANOVA process.Running an analysis of variance will allow
SPEAKER 1 [continued]: you to answer three questions.One, is there a main effect of the first independent variable?This ignores the influence of the second independentvariable.Two, is there a main effect of the second independentvariable?This ignores the influence of the first independent variable.And three, is there an interaction between the two
SPEAKER 1 [continued]: independent variables?This takes both independent variables into consideration.In our sleep deprivation example,using just two levels of sleep-- 0 hoursand 8 hours-- and two levels of stress-- low and high--you would ask these three questions.One, is there a main effect of sleep deprivation?
SPEAKER 1 [continued]: Perhaps you'll find that participantswho got no sleep at all show higher depressed moodthan participants who got 8 hours of sleep.Two, is there a main effect of stress level?Perhaps you'll find that participantswho underwent high levels of stressshow higher depressed mood, than participants who
SPEAKER 1 [continued]: underwent low levels of stress.Three, is there an interaction between sleepdeprivation and stress level?You could find that participants who receive no sleepshowed more depressed mood if they underwenthigh levels of stress, than if theyunderwent low levels of stress.
SPEAKER 1 [continued]: But that those who received eight hours of sleepshowed more depressed mood if they underwentlow levels of stress, than if they underwenthigh levels of stress.Now you're ready to draw your conclusions.
EVELYN BEHAR: At the end when you've actuallyanalyzed your data and come up with your results,what you want to do is go back to that initial hypothesis,or prediction, and compare them.You want to see well, I made this prediction,I posed this hypothesis, these were my results.Do my results support the hypothesisor do they refute the hypothesis?
NICOLE CAIN: If your original hypothesis has been refuted,you want to think about why that might be, and alsothink about how that impacts the theory that your hypothesis wasdrawn around.If your hypothesis is supported, youwant to think about replicating your results.You may have actually found this result by chance.This happens, this is statistically possible.
NICOLE CAIN [continued]: So you want to make sure that you can findthe same result a second time.If you can actually replicate your studyusing the same methods, and a different set of participants,with even a different set of experimenters,this gives you a lot more confidencethat your result is accurate.
SPEAKER 1: Share Findings.Now you're ready to share your new knowledge with the world.Here are some guidelines that willhelp you figure out what you need to includein your research report.First, you need to write an introduction describingthe theoretical background of your study, past evidence that
SPEAKER 1 [continued]: supports your hypotheses, and how this idea developedlogically, based on past studies and existing theories.Next, you'll explain how you conducted your experiment.How many participants were included,and how did you select them?What are their demographic characteristics-- their age,
SPEAKER 1 [continued]: race, or ethnicity, et cetera.You'll need to share your experimental design.For example, you can explain that you created a 2by 2 between-subjects factorial design,and discuss the independent and dependent variables.Then you'll explain your procedureby giving a step-by-step explanation of what
SPEAKER 1 [continued]: participants did in the experiment,any special equipment used to collect data,how variables were operationalized--that is defined in a way that is measurable-- and similardetails.Of course, you also want to share your results.Include all of your data analyses.Finally discuss your results in light of existing research.
SPEAKER 1 [continued]: How this adds knowledge to the world.What the limitations of the study were,and how this impacts real-world practices.You may also make suggestions for future research.Conclusion.
SPEAKER 1 [continued]: Now that you've learned about planning and conductingresearch, you can begin to think about whatyou would like to add to the worldof scientific investigation.Remember, here are the basic steps.Choose a topic, read existing researchbefore you decide what you will study, generatea hypothesis-- your if then prediction-- select
SPEAKER 1 [continued]: and define independent and dependent variables,and operationalize them, identify participants.Remember, you're finding a sample within a population.Design the study, include whether you'llhave one independent variable, or more than one.Plan and conduct the research.
SPEAKER 1 [continued]: Analyze results and draw conclusions.And finally, share your findings so that othersmay learn from your research.Good luck and see you in the laboratory.
Dr. Evelyn Behar and Dr. Nicole Cain discuss the steps involved in planning and conducting research. The steps of the scientific method help improve research and the researcher's ability to draw conclusions from the research. Behar and Cain discuss choosing a research topic, designing a study, and how to conduct research.
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Dr. Evelyn Behar and Dr. Nicole Cain discuss the steps involved in planning and conducting research. The steps of the scientific method help improve research and the researcher's ability to draw conclusions from the research. Behar and Cain discuss choosing a research topic, designing a study, and how to conduct research.