Module 2.5: Research Strategies: How Psychologists Ask & Answer Questions (Tues 9/16) Class 4

So this today we're going to kind of continue with correlational and experimental studies.

And first we're going to talk about correlational studies.

These are studies that detect naturally occurring relationships.

We can tell how well one variable predicts another.

We don't manipulate anything like, unlike in experiments, and so we're unable to often really specify cause and effect here.

So it can be a little bit misleading.

So correlation is sort of, these concepts are all related, these terms, but it's sort of a, what I call a concept, it's synonymous with relationship.

It's also a type of study which we just talked about.

The text, Natural and Current relationships assesses how well one variable predicts another.

And it's also a statistic, or we call it a correlation coefficient.

It's a statistical index between negative one and one that tells us the strength and the direction of the relationship between two variables.

So an important thing to know about correlational studies are a couple of important things, is you can take data from any descriptive study, technically, oftentimes it's surveys, but not just exclusively surveys, and you can use that data to create a correlational study.

So if you were collecting data in a survey on some questions from some folks about one variable, like, you know, drinking and then another variable about how many hours they study or something to that effect, we can correlate those two, two variables that we've collected via a survey.

And there we also have a correlational study.

An important thing to also understand about correlation, as I alluded to earlier, is that correlation does not necessarily equal causation.

So it's a limited study.

I think we can get kind of creative and also a little bit more precise with these kind of studies to get close to kind of cause and effect.

But it doesn't give us the same power that we have with experiments.

And I'll explain that in a little bit.

So when we talk about it not beating causation, I'll give you an example.

We have two variables here.

Wearing beds, choose to bed, and then headaches.

And this person on the left thinks that, you know, or notices that every time that he wears his shoes to bed, he, you know, he gets a headache.

And so he thinks that his headache is caused by shoes to bed.

And so his friend is noticing also that there's probably some other variable that's related to both of these, meaning it has to be related to word juice to bed, and it has to be related to headaches in order for this to be perhaps could be the other variable that explains this relationship.

And that's probably the more likely answer.

Here I have the arrows on the direction, because sometimes one variable kind of precedes the other variable in one direction, but sometimes it goes the other way around.

And so sometimes the order that we see the variables happen is sometimes important.

Here's another one.

We often hear instructors say that, you know, attendance leads to better performance.

We can kind of look at the direction going from attendance to performance, and they speak in causal terms, which isn't the best approach with when we're talking about correlational methods, we could, you know, argue that it goes performance leads to attendance.

And I noticed that sometimes when students don't do well, sometimes some students check out, go to attend after not doing well, then kind of come back.

And so we can see the direction happening the other way in some cases.

But we have to think about a third variable that's related to both attendance and to performance as one goes up.

You know, if we see attendance go up and performance go up at the same time, we would also see another variable related to that at the same time.

And we could argue that perhaps the real variable that explains the connection between attendance and performance, class performance, is motivation.

When students are very highly motivated, they tend to attend more.

They also tend to study more.

They often, you know, have better performance on exams.

There is a correlation there.

It's not a perfect correlation, but it is actually very much related.

And so that third variable, motivation, could be the real factor that makes a difference.

We can't run an experiment.

I mean, we could, but it would be kind of unethical to do this as an experiment where we'd be better apt to get a causation.

You know, an instructor would ask some students in the class to stay home for 30 days at the other students to come to class for 30 days and then measure their performance.

And, you know, that would be certainly unethical to do that because many students wouldn't want to be here.

We would not let them be here just to prove a point in terms of experiments.

So we can't do experiments like this.

We have to rely on correlational data.

And so one of the things that, you know, I like to say about the idea that correlation doesn't mean causation is that it doesn't mean we shouldn't take Correlational studies, Seriously.

So, for example, could the study have been ethically conducted in another way?

You know, if no, then we have to give researchers some credit that they did a study that was more feasible, more ethical, rather than doing experiment.

And so don't necessarily dismiss the study because it's correlational.

The other thing that researchers can often do is instead of actually controlling variables in the environment, as we might do with an experiment, we can control for relevant variables in a statistical way.

I'll give you an example here of how you might have a correlational study and then control for variables so we can can get closer to causation than we might otherwise.

And so there's a concern about the use of tanning booths and skin cancer.

And we do see an association here with more tanning booth use leading to more skin cancer, including melanoma, the most dangerous type.

And you know, a smart observer might argue that, well, you know, there's another variable here that could explain the relationship.

Maybe it's not really tanning those that's leading to skin cancer.

Maybe it's something else, something we already know.

And that would be there is a correlation between tanning roof use and sun exposure.

There's also a correlation between tanning with skin cancer and sun exposure.

You know, a lot of people don't tan in the sun in the summer, will tan, use tanning boots in the winter and so forth.

So we do see a lot of people who get a lot of sun exposure times of the year also have high levels of tanning booth use.

So not exclusively, but we do see that connection.

So it could really be more about the sun exposure.

So what researchers might do here is group people in ways that might look like this in terms of controlling.

So we're going to have people who have a lot of tanning booth use within that group.

We're going to have people who have a high sun exposure, medium sun exposure and low sun exposure.

Then we're going to have people who have sort of a moderate amount of tanning with use within that group.

We're going to have high sun exposure, medium sun exposure and low sun exposure.

Same thing with low tannic with is we're going to have high sun exposure, meaning sun exposure to low sun exposure.

I think, you know, the lowest group 9 there is probably the biggest group in that kind of lowest tangle booth group use.

And the highest tan booth used to probably the highest sun group is probably the highest group there.

But all of these people are going to have, you know, people populating each of these nine groups.

And then so what we're doing here is we're trying to control for sun exposure, looking at different levels of tanning with use.

And so just to give you an example, if we just look at the lowest sun exposure group, if we say that, you know, if sun exposure, if tanning with use has nothing to do with skin cancer, then people with the same level of sun exposure, in this case the lowest level of sun exposure, should have the same exact cancer risk.

Right, because they're all the same level of sun exposure, but they have different levels of tanning with use.

So if tanning with use has nothing to with do with skin cancer, then in this case we would see no difference between these groups.

But it turns out we see more skin cancer in the medium group than the lowest group and more in the highest group versus the medium group.

So tanning with use does seem to have something to do with skin cancer, because when we control for sun exposure the same levels of sun exposure, we see increased rates at higher tanning reviews.

And so we do the same thing for medium sun and high sun as well.

Hopefully that makes sense.

You don't have to remember that exact kind of example, how I came up with that and so forth.

Just to give you a sense of what does it mean when we can't control something in our environment, but we can control it statistically.

So we make sure that it's the same when we're looking at other levels of variables that differ.

Right.

So we talked about correlational research and some of the limitations there.

What we're going to do now is talk about experimental research a little bit longer.

And this is a type of study that allows us to explore cause and effect more readily.

The reason for this is because we're able to manipulate one or more variables and we also will use random assignment to groups, which makes a big difference in terms of controlling for certain variables that might be true of a particular population while manipulate other variables.

We want to see its effect.

And you know, sometimes these aren't as feasible or ethical, and sometimes they don't generalize to other contexts.

But it is a study that's very important.

And all the scientists, experimental studies are very, very important.

So, you know, I'm going to start with a simple example, one that perhaps you did in biology 6th grade or before that, I don't know.

So, you know, if we have a hypothesis, you know, the hypothesis here seems to be that, you know, using newer fertilizer is going to perhaps produce better growth in a plant than using kind of an Old fertilizer.

I'm not sure what that blob is in the middle of that picture there.

And so the hypothesis is essentially that the new fertilizer will do a better job growth rate of plants than the older fertilizer.

So the variable we're manipulating here that actually separates the two groups that we're comparing here is actually fertilizer.

So type of fertilizer, the old fertilizer, the new fertilizer, okay?

And so that the two groups, we want both of these groups to be exactly the same in every other way.

But manipulation of this variable, we call this the independent variable.

Otherwise we would explain any different growth rates by some other variable than the one we manipulated.

So the independent variable is a variable that we manipulated.

We want to see its effect on growth.

So in this case, the growth rate is the dependent variable.

Sometimes it's called the outcome variable.

It's the variable that will change in response to manipulation of the independent variable.

So ideally, here again, every single thing is exactly the same between these two groups here.

The one on the left and the one on the right, except for the type of fertilizer.

So same level of watering, same sunlight, it's just the fertilizer that's different.

It's very important for us to be able to say something about the fertilizer making a difference if everything else is the same.

So the experimental group is usually the one that's getting something new or, you know, or some.

Some version of the independent variable that's perhaps newly investigated or perhaps there is something that is happening compared to a control condition that maybe nothing is happening, they're not being exposed to anything.

So their level of variable is nothing.

But oftentimes it's actually an older, older drug or an older, in this case, fertilizer that's on the market.

So what I want to do is do a.

Show you an experiment, a demonstration that involves humans.

And so this will involve two identical twin sisters.

And as you watch this video, see if you can figure out what the hypothesis or research question is.

What one variable the researchers intended to manipulate and what did they intended manipulation to have an effect on how many groups or conditions were involved in the experiment.

And then, you know, why would it be important to have two groups or conditions in this experiment rather than one?

And so to go back to the plant example, if you ask, you know, why did we bother having a control condition where we compared that plant with the old fertilizer with the new fertilizer, why don't we just give the new fertilizer to the one plant and not bother comparing it.

You think you understand that?

Well, we don't know actually, this, the one with the new fertilizer could have grown really well.

We really liked his growth.

But maybe if we gave the old fertilizer to the other, other plant, it would grow, grow even higher.

And so we have to have something to compare it to because there's all sorts of reasons that we might be mistaken in our interpretation of something that happens if we're just looking at one group.

So again, think of these questions as you're watching this video.

Sexual attraction is triggered by many mysterious forces.

Some are secretly going on all around us, right under our noses.

In this Miami singles bar, the air is awash with molecules of lust.

Men and women have their own distinctive scent.

Our bodies secrete chemicals called pheromones.

We may not be aware of them, but when they ooze out of our skin and waft into the air, they have an electrifying effect on the opposite sex.

A woman's natural pheromones boost men's testosterone levels by 150%, which makes them feel aroused.

Some male pheromones have been shown to have a similar effect on women.

To test the effect of pheromones, a pair of identical twin sisters agree to take part in an experiment.

They're going to pretend to be the same person to check the pulling power of a synthetic pheromone scent.

Bye.

While Melita hides in the restroom, her sister Mimina, who is wearing no scent, ventures into the bar.

Mina spends an hour in the bar and only gets picked up once.

Her sister then dabs on the pheromone scent and tries her luck.

Okay, you're gonna try everybody crazy.

Even though the men in the bar assume it is still Melina, they now flock around the twin doused with pheromones.

The twins perform an identical routine.

But Merida gets approached many more times than her sister.

Pheromones act.

Okay, so, you know, think about this for a moment.

What is the hypothesis or question that would have something to do with the idea, you know, does you know a pheromone scent will lead to higher attraction?

That seems to be the, you know, compared to no pheromones.

That seems to be the hypothesis or research question in this particular demonstration.

If you think about what one variable researchers intended to manipulate.

So we're going to get to unintended in a little bit, but intended to manipulate.

What would deliberately try to manipulate and what did they intend this manipulation to have an Effect on.

Right.

So they intended to manipulate the pheromone status.

So one twin got the pheromone, the other twin did not get the pheromone.

Okay.

So in that case, it's the manipulated variable and that's the independent variable.

And they wanted to see that the manipulation, its effect on attraction, sexual attraction.

And so that sexual attraction was the dependent variable.

How the dependent variable, by the way, is specifically operationalized or defined is how many times the twin is approached by a male.

That's like a check.

That means that that is an example of independent variable being a score of 1, depending which group the twin are in.

So in this case, how many groups or conditions were involved with the experiment?

To go back to, by the way, how that dependent variable was operationalized or defined, it's very important because you have observers here, including the twins themselves, who are making a judgment on what actually involves sexual attraction for them.

It's just.

Just being approached.

And so we have to be really clear on what kind of.

What that means, someone walking up to them.

Or it could be something.

Something different.

And so we really have to be sure what we mean by sexual attraction would have been variable.

How many groups or conditions were involved in this experiment?

There were actually two.

So there was the twin that was wearing the pheromone, the other twin that wasn't wearing the pheromone.

And again, why would it be important to have two groups or conditions in this experiment rather than one?

And that would be because if we just gave the twin pheromone and she got approached by a lot of men and we didn't have anything to compare it to, it could have been that the other twin could have been been easily equally approached by these men.

And so it maybe had nothing to do with the pheromone at all.

So we have to have a comparison group.

So what I'm going to do is ask you to kind of go back and, you know, look at this video again and look at it with these other kind of questions.

You may already been able to answer these, but sort of two questions.

Were there any variables they reasonably controlled?

In other words, kept constant between the groups or conditions, and then what do they mess up and why?

In other words, what did they accidentally manipulate or not control for?

That could explain the outcome of this experiment.

They remember in an experiment, to be confident in our results, we want everything else to be the same between the two groups or conditions, except for the independent variable.

They have several kind of missteps here.

One which was easily fixable which is kind of weird.

So see if you can figure that out.

These two questions on the second viewing.

Who's insects?

Sexual attraction is triggered by many mysterious forces.

Some are secretly going on all around us, right under our noses.

In this Miami singles bar, the air is awash with molecules of lust.

Men and women have their own distinctive scent.

Our bodies secrete chemicals called pheromones.

We may not be aware of them, but when they ooze out of our skin and waft into the air, they have an electrifying effect on the opposite sex.

A woman's natural pheromones boost men's testosterone levels by 150%, which makes them feel aroused.

Some male pheromones have been shown to have a similar effect on women.

To test the effects, a pair of identical twin sisters agree to take part in an experiment.

They're going to pretend to be the same person to check the pulling power of a synthetic pheromone scent.

While Merida hides in the restroom, her sister Mimina, who is wearing no scent, ventures into the bar.

M spends an hour in the bar and only gets picked up once.

Where are you from?

Well, originally from Venezuela.

Venezuela.

Her sister then dabs on the pheromone scent and tries her luck.

Okay, you're going to try everybody crazy.

Even though the men in the bar assume it is still mamina, they now flock around the twin doused with pheromones.

The twins perform an identical routine.

But Marita gets approached many more times than her sister.

Pheromones act as.

Okay, so think about this.

Were there any variables they reasonably, you know, kept controlled, so kept constant between the two groups or conditions.

And I think, you know, when you think about something that could make a difference in the dependent variable, the sexual attraction, it would be the attractiveness of the.

Of the.

The two women, right?

So having identical twins when wearing the firm one and whatnot actually is a good, general, reasonably well controlled variable of attraction.

Doing, doing that.

They, of course, could have used one twin and used no pheromone first, and then probably put the pheromone on later.

That could have also been okay in terms of keeping the attraction the same.

It's interesting.

You know, we will talk about twin research throughout the.

Throughout the semester, including especially identical twins, which are very important.

I was showing this video for a while in class, and then in one of my variations, one of my textbooks I used to use, also they showed up in my textbook, which has actually happened a lot, the different things that I've used.

What did they, you Know, mess up and why.

Also the personalities were well controlled and so forth.

They were.

Had similar personalities and so forth, which makes a difference in terms of attraction.

But you might have caught on what they kind of messed up that were different between them.

You know, what they accidentally manipulated or not control for.

That could explain the outcome of the experiment.

Again, the sexual attraction one is that, you know, one twin goes out at one point in the night and the other twin goes.

Goes out like an hour or more later.

And so time makes a difference.

And there's a couple things that can difference here.

The men could be more drunk later in the night.

And so that may have something to do with the amount of men that were willing to approach them.

Just building up confidence, you know, later in the night they'd be more likely to build up confidence.

We don't know how restricted, you know, if there's other manner of more men in the board later, so there's more men to possibly interact with them between later on.

So that, that's.

It's not easy to control, but it is something that can be done, you know, if it's.

If the conditions are run kind of, you know, simultaneously, one twin in one end or one twin or the other switch places.

All sorts of things you can do with that.

Another thing that really got messed up here was the fact that the twins knew whether or not they agreed to farewell or not.

And that's, that's a big no no here.

If you notice that when this first sister went out, she knew she had it for everyone.

Said she kind of seemed a little bit disappointed.

I don't think she was making as much eye contact.

But when they sent the second twin out, the first twin encouraged her.

So you're going to drive everyone crazy.

The other twin may have felt encouraged by that and made more eye contact and so forth.

And that would definitely make a difference in terms of attraction.

Just, just the expectation that they are wearing something that might make a difference.

Expectation alone we actually call the placebo effect.

So these are all confounding variables, right?

Variables other than the independent variable that might produce an effect on the independent variable of the experiment.

So one of the things that we can do which was really, really easy to control was the placebo effect.

The placebo effect is any effect on the dependent variable that's caused by the rectangular expectations are low.

Right.

So them knowing they didn't have the pheromone and did have the pheromone makes a really big difference in terms of expectations and nonverbal behaviors.

And so forth.

So the easiest thing to do here is to actually give a placebo to the twin that's not getting the firm out.

So it looks, you know, it's like water, but it doesn't have the pheromone.

The other twin gets the actual pheromone.

And so now one of them gets a placebo, one gets the real pheromone, and voila.

As long as we don't tell them what group they're put in, now we've control for the placebo effect.

Expectation is exactly the same between the two groups.

So that was really easy to do here and demonstrate.

I'm not sure why they didn't do it.

So, you know, they're made aware that they may or may not wear the placebo or have the real pheromone.

But essentially when they don't know which group they've been placed into, we have what's called a single blind or single mass design.

So in this case, you see how important that would be.

That could be crucial, this particular study, especially when we looked at their kind of behavior.

Another thing we could do actually is to have a double upline or double mass design.

And the reason we might do this is if you think about an experimenter out there, maybe looking at the number of men who are approaching each twin, they might have some bias, even unintentional, if they know that one twin has the furlough and the other twin doesn't.

And so simply to keep them blind to which group the, the twins that have been placed in, someone obviously has to keep track of that.

But someone who's actually looking at measuring the dependent variable for both the groups, that person would best probably not be aware of what group the twins are in.

Just do the counting, do the observation, and then give it to someone who does know and they can make their comparisons later.

Okay, I hope that makes sense here.

In a lot of experimental studies, particularly where we have a lot of participants that we can assign to two different groups, one of the compounds that we can have.

Remember, we want the groups to be exactly the same, except the variable.

So if we, let's say, ran a lot of subjects for this particular participants for this study, we wouldn't necessarily want them as to assigned to the experimental control group.

Just, you know, choose which one you want, the firm or the not firm or the whatever.

We would want to randomly assign the participants to the groups.

Because if our groups are big enough, then random assignment kind of levels out any pre existing differences between the people, you know, age and Level of attractiveness and education and, you know, the verbal behaviors and so forth.

We randomly assign them to experimental control.

Group groups are big enough that we can be assured now the groups are equal.

And now it's just manipulation of the independent variable hopefully will be the one that we're looking for the effect of as long as, again, we're not doing some other things like messing up time and those sorts of things in our delivery of this experiment.

So in the last part of the first part of the chapter, we talked about random sampling.

So don't want students to be confused about the difference between random sampling and random assignment.

Random sampling is how participants can be selected for inclusion in the study.

So who are we going to choose to be in the study that's usually most important for things like surveys and so forth?

Random assignment occurs only in experiments, and it's how participants, once they have been selected, are actually assigned to groups or conditions.

Okay, so regardless of the type of research methodology that we have, an important consideration is, can our results be generalized to people outside our study?

We're typically looking at, you know, a sample from a population we're interested in, but we always really want to make sure how representative is that sample.

If we're going to say something like this pheromone scent, is it, you know, I don't think we can generalize the results to men wearing it.

Right.

I think it's probably going to be something that women can wear and maybe get some results from.

But unless we're testing it on men in the.

In the same way we're testing on women, I don't think we can say, oh, we're going to look at this fair amount to men.

That doesn't make sense.

We can't really generalize it outside our study.

All right, so.

So a couple things about research ethics that we'll talk about here.

Am I stuck here?

There we go.

One thing that's really important in doing research is to make sure that participants have informed consent that they both know what to expect as a research participant and that they also have the other participating voluntarily.

So for folks during the sona looking for opportunities on Sona, the reason why we have the possibility of being a research participant, but also the possibility of just having your own alternate where they're not involved in a study.

They're just summarizing the journal article that involves this, where a research study is the voluntary nature, because you can't be required to be a research participant in most cases.

And so, again, that you know exactly what you're getting into and that, that you are participating voluntarily.

Another thing that we have in research ethics is we have to make sure that we're protecting people and in some cases animals from hormone discomfort.

They shouldn't be, you know, subjected to anything that's going to create significantly greater than usual physical or emotional distress.

All research studies go through something called institutional review board.

And usually if the researchers are going to subject the participants to, you know, a bit of discomfort, more than you would normally expect, they have to really make a case for it.

If they're unable to make a case for it, there's not, you know, and you know, there is another way around it, another type of method or an experiment that doesn't involve that, then the armies will usually reject that.

And we'll see.

Actually, in a lot of studies, classic studies, this is one area that gets really problematic, is that there has been quite a bit of harm and discomfort, you know, particularly psychological discomfort to participants in some of the classic studies.

And because of that, actually they can't be recreated as they were done back in the 60s, especially because I can't think of an IRB board that would, that would actually vote or, or say yes to a study the way some of those studies were done back then.

Confidentiality has to do with individual participant information being held private and you're not releasing the names of people related to their data.

And then debriefing.

This is when, you know, participants are giving the full shebang about what's been done in the study.

Sometimes when you're doing a study, you're not told what the purpose of the study is, because if you knew the purpose of the study, it would change your behavior sort of.

There'd be no reason to do the study at all.

So, you know, we'll actually talk about that particular situations, particular studies in our next class.

But if you're using any deception at all, including what group they might have been placed in, if you're told you're being placed in the placebo or the experimental group and we can't tell you the study's over.

This is the part when the study's over that we debriefing, we tell you which group you've been placed in.

In medical studies, oftentimes if the medication or the treatment is going really well, sometimes they don't really stop the study per se, but they start to switch people to the treatment group as a placebo because they know that the treatment is actually working really well and it would be a shame to keep them in the placebo group when we know that the treatment has some really big advantages.

Okay, so what I want to do is actually tell you this sort of strange story.

I lost the actual wording of this that I had.

I don't know where it is but I kind of recreated it from different places in my memory.

So it doesn't sound as engaging as when I actually read it from the actual book.

The book is called why Zebras Gets Ulcers by Robert Sapolsky.

It's a really interesting book.

It's really related to stress and disease.

He tells you kind of weird stories.

But as I told the story, I want you to think about why the author uses the term natural experiment.

It's not really a true experiment because no variables were deliberately manipulated.

But what, what makes it look like an experiment otherwise.

So I want you to think about it as I read read the story here.

So you know, this one winds up in half.

The textbooks produce a clean result of a was designed intentionally.

The natural experiment took place in Germany after World War II.

The German orphanages in the study were run by the government.

The two orphanages, thus they had the same diet, nutrition level, medical care, etc.

The main discernible difference was the two women who ran the orphanages.

Their names even sound like the parable, but they were the true names.

And one orphanage, the orphanage was worn by far like Groom who is the warm, loving, nurturing person who seemed to like sing with the children all day long.

So I'm reminded of Maria from the Sound of Music.

That's Carrie Underwood's live version.

And that's like I think attract Maria.

And then the other was orphanage that wrote by 4line Schwartz.

She you know, discharged her daily obligations without much caring.

She was mean it cold and rigid to the children.

So I think of the character from Matilda there.

And so what they did was they actually measured the growth rates of the children in both these orphanages.

And they found that the children in four Line Groom's orphanage, the nice one, grew to normal height at weight and the children in four Line Schwartz's orphanage, the mean one lagged well behind at least that there was really a lot of problems with their birth rate.

The thought here was that it was because the real difference between these two orphanages was the women who were running.

It had to do with the kind of the personality and the treatment of the children by these two women.

That was the researchers thought.

And then in an elaboration that couldn't have been designed better than by a scientist, Frulein grew in the nice Boat moved on to greater pastures and for some bureaucratic reason for like Shorts, the mean one replaced her at her old orphanage.

So growth rates at Short's former orphanage promptly increased.

Those at her new one actually decreased.

And so we see possibly that change in women at these places actually made the reverse kind of reaction in the children turned to the growth rates.

So if you think about why this is called a natural experiment, it's an experiment, not really.

It's something that happens out there.

No one designed this.

No one's manipulating any variables.

But because so many things were the same between the two orphanages, the one real main difference that could be really seen was the webinar ran the place.

And even when there was a switch, we saw different differences in the growth rates when there was a switch.

So there seemed to be something with the women who were running these places.

But again, it wasn't a true experiment.

We weren't deliberately manipulating any variables here.

So I'm going to kind of read on a little bit about that.

So reading on from this book, the author talks about a story of a boy from a Walter family in Victoria, England.

The boy's older brother died in a tragic skating accident.

The boy enters his mother's room.

While she's in a constant state of grieving.

The mother asks David, is it you?

Is it really you?

Only to realize, oh, it's just you, but never boy.

The only solace the mother feels is that David was still a child when he died, never to grow up, grow old and away from his mother.

There seems to be no malnutrition or anything like that in this, well family.

But the boy seems to seize on the idea of his mother, his mother liking the fact that his older brother never grew old and was always a child.

So the boy seems to seize on this idea as an adult.

He's barely five feet tall.

As marriages have consummated, this boy with Jan Barry, the author of Peter Pan J. Barry's books are from.

Children who die young come back as ghosts to visit their mothers.

So I think about the Johnny Depp film that was mostly, I think, fictional Jambe's life.

I'm not really sure why, given the story seems already made for that.

So what I'm doing here now is to kind of give you a heads up.

You'll see this story comes from Weissy Pacific Ulcers.

But what you'll see is this kind of alert in some classes, it's things you didn't know, you didn't want to know.

And this is a clue that you might be getting some information, information that might relate to a bonus question on the exam.

And so here's Peter Pan and Peter Pan is played on stage mostly by women.

The first one I believe was Kathy Rigby.

She was a Olympic gymnast for the United States.

And then Allison Woman Williams played one recently from the same stage by the way that Carrie Underwood played Murder Mott Trapped in Sound Music Live broadcast other place that broadcast from there including the Wiz with Queen Latifah.

And you know, I don't know if folks know the name of the studios on Long Island.

This was actually broadcast from all of these kind of recent plays.

But it was actually Grumman Studios at Beth Page.

And to let you know, that's actually where my parents met.

So something in there might be related to a bonus question on the first exam.

Okay, okay.

Just so you can see the study guidelines for this module.

Every module is going to have similar sort of guidelines as it relates to study for a exam which I have a second of the slides here but they'll also have some different guidelines depending on the content of that particular module.

And so this module kind of the roadblocks that we talked about in the first half of this module Roblox to critical thinking we talked about hindsight class confirmation bias and reasoning, the principle of falsifiability.

That's going to be a major focus the strengths and limitations of each of the different research methods we talked about major focus about this idea that correlation doesn't necessarily causation.

Whoops I haven't spelling there causation and why that's the case and then know kind of the experimental methods.

Well particularly being able to identify independent dependent variables, experimental control groups and conditions confounding variables what they might be and approaches to eliminate or reduce them.

So for example use of random assignment use of placebo and single and or double blind kind of mask procedures.

Correlational Studies

Correlational studies detect naturally occurring relationships, revealing how well one variable predicts another without manipulation. This means they cannot specify cause and effect.

• Correlation Coefficient: A statistical index (between -1 and 1) that indicates the strength and direction of the relationship between two variables.

• Data from any descriptive study (e.g., surveys) can be used to create a correlational study.

• Correlation \neq Causation: This is a fundamental limitation.

  • Example 1: Wearing shoes to bed and headaches – a third variable (e.g., alcohol consumption or fatigue) likely explains both.

  • Example 2: Class attendance and performance – motivation could be the underlying factor affecting both.

• Researchers can statistically control for relevant variables to approach causation, even without environmental manipulation.

  • Example: Studying tanning booth use and skin cancer, while statistically controlling for sun exposure, reveals an independent risk from tanning booths.

Experimental Studies

Experimental studies allow researchers to explore cause and effect more readily by manipulating one or more variables and using random assignment. These are not always feasible, ethical, or generalizable.

• Independent Variable (IV): The variable that is manipulated by the researcher.

• Dependent Variable (DV): The variable that is measured and is expected to change in response to the IV's manipulation.

• Experimental Group: Receives the treatment or the new condition being investigated.

• Control Group: Serves as a baseline for comparison, often receiving no treatment or a standard/older treatment.

• Importance of Comparison: A control group is crucial to ensure any observed effects are due to the IV and not other factors.

• Pheromone Experiment Demonstration:

  • Hypothesis: Pheromone scent leads to higher sexual attraction.

  • IV: Pheromone scent (present vs. absent).

  • DV: Sexual attraction (operationalized as the number of male approaches).

  • Reasonably Controlled Variables: Attractiveness and personality (using identical twins).

  • Confounding Variables (Mistakes):

  • Time of night: One twin went out later, potentially affecting men's confidence or sobriety.

  • Researcher/Participant Expectation (Placebo Effect): The twins and possibly the experimenters knew who had the pheromone, influencing behavior and observations.

• Confounding Variables: Variables other than the independent variable that might produce an effect on the dependent variable.

• Placebo Effect: Any effect on the dependent variable caused by expectations rather than the actual treatment or manipulation.

• Single Blind/Mask Design: Participants are unaware of their assigned group (e.g., whether they received a placebo or the actual treatment).

• Double Blind/Mask Design: Both participants and the researchers measuring the dependent variable are unaware of group assignments, reducing bias from both sides.

• Random Assignment: A process used only in experiments to assign participants to either the experimental or control group, aiming to equalize any pre-existing differences between groups if the groups are large enough.

• Distinction between Random Sampling and Random Assignment:

  • Random Sampling: How participants are selected for inclusion in a study (who is in the study).

  • Random Assignment: How selected participants are then assigned to groups/conditions within an experiment.

• Generalizability: The extent to which research findings can be applied to other populations or contexts.

Research Ethics

Key ethical considerations in research:

• Informed Consent: Participants must be fully informed about the study and voluntarily agree to participate.

• Protection from Harm/Discomfort: Participants should not be subjected to significantly greater than usual physical or emotional distress. Institutional Review Boards (IRBs) review studies to ensure this.

• Confidentiality: Individual participant information and data must be kept private and not linked to names.

• Debriefing: After a study, participants are given a full explanation of its purpose, especially if deception was used. If placed in a specific group (e.g., placebo), they are informed post-study.

Natural Experiment (Example: German Orphanages)

A "natural experiment" occurs when conditions in the real world resemble a controlled experiment, but no variables are deliberately manipulated by researchers.

• Context: Two German orphanages post-WWII with identical diet, nutrition, medical care.

• Key Difference: The women running them: Frulein Groom (warm, nurturing) vs. Frulein Schwartz (cold, rigid).

• Outcome: Children in Groom's orphanage grew normally; those in Schwartz's lagged.

• Elaboration: When the women switched