Researching cause and effect

Researching Cause and Effect

Chapter 2 – Second Slideshow

As a psychologist, when I hear people state a belief, I immediately start thinking in terms of variables.

I realize that most people do not do this, but this is ultimately the evidence we can collect and evaluate.

A variable is any quantity or quality that can take on different values. Here are two random examples.

Not at all Helpful Very Helpful

The Degree to which this Slideshow is Helpful.

Not at all Interested

Extremely Interested

A Person’s Interest in Scientific Research

Perhaps these two variables are related. Maybe people who are more interested in the scientific method will be more likely to find this slideshow to be helpful.

Each person watching this slideshow can place themselves along the continuum of each variable.

1. The degree to which this slideshow is helpful.

2. A person’s interest in scientific research.


Not at all Interested Extremely Interested

Here is an example of one student, Phil. Phil finds this to be a great slideshow. Phil also loves science.





Phil

Phil

Here is another example. This is where James ranks himself on both

variables.





James

James

We could ask a large group of students to mark where they fall on both variables.

Perhaps we might start to see a pattern. People who like science keep ranking this slideshow as helpful. People who do not like science rank it lower.

It is very tempting to start fitting these findings into a story. Maybe people who like science are more curious and patient. Maybe they find slideshows (which are, admittedly, kind of dull) to be more interesting.

Maybe one’s attitudes toward science causes them to like or dislike this slideshow.

How do we research Cause and Effect relationships in Psychology?

Establishing Cause and Effect

Philosophers have a lot to say about how we determine if one thing causes another. We will skip that debate and focus on three characteristics to help us establish cause and effect.

John Stuart Mill

David Hume

Immanuel Kant


Conditions to establish Cause and Effect.1. The variables are correlated.2. The cause comes before the effect.3. There are no other variables to explain the

effect.


Note that the first step is to establish a correlation.

Correlation is a fancy term for “related.” To understand how psychologists study causes and effects, we need to understand correlation.


It is very easy to think about how one thing may cause another. However, it is not always easy to see how these ideas imply a correlation. Let’s look at examples.

A B

Correlation examples

Does having a nice teacher cause students to learn more? Here are the two variables:

Not at all Nice Very Nice

Teacher’s Niceness

Very Little Learning

Mastery of Content

Student Learning

Correlation examplesIf the variables are related, then we should see

nicer teachers have classes that perform better. Pretend we observed a teacher that fits this pattern, Mr. Carter.




Mastery of Content

Student Learning

Mr. Carter

Mr. Carter’s Class

Correlation examplesIf the variables are related, then we also should

see teachers who are not nice have classes that perform poorly. Pretend we observed a teacher like this, Ms. Stark.




Mastery of Content

Student Learning

Ms. Stark

Ms. Stark’s Class

Two Sides to a Correlation

This is the hard part. Correlations have two sides, or ends. People usually only think about one. In our case, we think about good teachers having good students (the high end).

Two Sides to a Correlation

If you believe a nice teacher causes a class to do better then you are also saying that not being nice goes with students doing worse. This is the low end of the correlation. For a correlation to exist, we need to have both Mr. Carter and Ms. Stark!

More Examples – Two Sides of Correlation

If you believe that giving someone flowers will make them like you, then you also should observe that people to whom you do not give flowers would like you less.

More Examples – Two Sides of Correlation

If you believe that spanking a child causes the child to behave better, then you are also saying that not spanking should co-occur with worse behavior.

Each of these is a proposed correlation. It can be difficult to think about these, but practicing this can help you think about what type of observations you would need in order to see if two variables are correlated.

Correlational Methods

Most correlational research methods involve collecting data on at least two variables.

There are many ways to collect these data. See your text for those details.

Naturalistic ObservationArchival Research

Surveys / Questionnaires

Correlational Methods

However, we usually cannot determine cause and effect just from simple correlational studies.


The problems are the second and third conditions

Conditions to Establish Cause and Effect1. The Variables are Correlated.2. The Cause comes before the Effect.3. There are no other variables to explain the effect.

Problem2. The Cause comes before the Effect

Usually, in correlational studies, we observe both variables at the same time. It is not always possible to know which comes first.


For the example with Mr. Carter and Ms. Stark, this is a problem. The idea that a nice teacher causes a class to learn more is only one possible direction of cause between these variables. As you see below, this explanation hypothesizes that the niceness comes first.


Students’ Learning

Causes


The opposite direction is also possible. Some teachers may respond to their class’s performance. It feels great to have a class do well, and it can feel very defeating if your class is struggling and performing poorly.


Students’Learning

Causes


For every correlation you observe, be sure to consider both possible directions of cause.

Variable A Variable B

Variable A Variable BCauses

OR

Causes

But those aren’t the only possibilities…


The third condition also has to be met.

Conditions to Establish Cause and Effect1. The Variables are Correlated.2. The Cause comes before the Effect.3. There are no other variables to explain the effect.

Problem3. Are there other variables to explain the effect?

In correlational research, even if we observe a correlation and establish that one variable happens before the other one…

…we still do not know if there is a cause and effect relationship.


The problem is that correlational research observes variables as they occur in the real world. Although valuable, this leaves many questions.


In the real world, there are countless other variables. Some may also be recorded in our study, but others may vary without us knowing.


In the most simple form, this is called the third-variable problem. Does some other variable, other than our two observed variables, cause the other two to be related?

Variable A Variable B

Causes

Third Variable

Caus

es


For our teaching example, pretend that we found a correlation between teacher’s niceness and student learning (step 1 in our search for causes).


Student Learning


Next, pretend that we establish that the teacher’s niceness comes first (step 2 in our search for causes).


We still would not be able to say for certain that another variable did not cause the observed correlation.


Student Learning

Causes

Third Variable ?

Caus

es


For example, maybe the resources available to the school affects both of the other variables.


Student Learning

Causes

School Resources

Caus

es


Let’s look at another example. There is a correlation between the number of churches in a city and the amount of crime. Cities with more churches have more crime. Yes, that’s right, more churches is associated with more crime!

Number of Churches in

City

Number of Violent

Crimes in City

Don’t worry, this correlation is meaningless. It is explained by a third variable.


There is a simple third variable: Population of the City. The more people in a city, the more churches they build. The more people in a city, the more chances there are for crime.

Number of Churches in

City

Number of Violent

Crimes in City

Causes

Population Size of City

Caus

es

Review

Correlational research is a valuable tool.

There are many ways to collect correlational data.

Review

Correlation is a first step in the search for causes. To establish cause, we need all three of the following conditions:

1. The Variables are Correlated.2. The Cause comes before the Effect.3. There are no other variables to explain

the effect.

Review

Simply observing a correlation does not tell us that one variable causes the other.

The direction of cause could go either way. There may be a third variable causing the

observed variables to look correlated.

Establishing Cause and Effect Through Experiments

The Experimental Method

The experimental method is a researcher’s strongest tool for establishing cause and effect relationships. A well-structured experiment meets all three criteria for establishing cause and effect.

The Experimental MethodConditions to Establish Cause and Effect

1. The Variables are Correlated.

2. The Cause comes before the Effect.

3. There are no other variables to explain the effect.


1. The experimenter looks for a relationship between one variable that is a cause and another variable that shows the effect.

2. The experimenter manipulates the causal variable first and measures the effect variable later.

3. By using manipulation and controls, the experimenter can rule out alternate explanations.


The two variables have special names.

Independent variable – the variable manipulated by the researcher to see if it is a cause.

Dependent variable – the variable measured to see if there is an effect.


Independent Variables

Typically, independent variables describe what is different between two groups:

an experimental group and control group.


Independent Variables

Perhaps the hardest part of conducting an experiment is making sure that the independent variable, and ONLY the independent variable, differs between the groups.

The Experimental MethodIndependent Variables, Example

We could use an experiment to study the effect of teacher niceness on student learning. We would need to create two groups of students:


Experimental Group – Students assigned a teacher who has instructions in specific ways to be nice in class.

Control Group – Students assigned a teacher without instructions to be nice.


The hard part is making sure that the only thing that differs systematically between these two groups is the niceness of the teacher.


Ways to Eliminate Extraneous Variables

An extraneous variable is a variable other than the independent variable that might be affecting the dependent variable.


Ways to Eliminate Extraneous Variables

There are two main ways to eliminate Extraneous Variables:

1. Experimental Control – designing the study carefully to remove extraneous variables.

2. Randomization – If an extraneous variable cannot be removed, it can be randomly distributed across experimental groups. That way it does not vary systematically with the independent variable.

Summary

Give yourself ample time to master these ideas and the terminology. You should be able to define all of the following terms, and describe how they relate to each other.

ExperimentIndependent VariableDependent VariableExperimental GroupControl Group

Extraneous VariableExperimental ControlRandomization

Limits of the Experimental Method

Not every variable can be manipulated. Remember the first example of two correlated variables:


The Degree to which this Slideshow is Helpful.

Not at all Interested

Extremely Interested

A Person’s Interest in Scientific Research


We hypothesized that a person’s interest in science will affect how useful they think this slideshow is.

Interest in Scientific Research

Perception of this

SlideshowCauses


How would you manipulate people’s “interest in science” for an experiment, making some people very interested and others disinterested?

Interest in Scientific Research ??


Even if we could come up with a creative way to manipulate “interest in science,” would it be the same thing as the interest people develop over a lifetime?


Other variables cannot be manipulated without causing harm or other problems.


Summary

Some variables are impractical to manipulate.Experiments can be artificial.Some experiments cannot be conducted

ethically.

Review

Practice turning explanations or stories into hypotheses about the relationship between two variables.

When variables are correlated, think about both ends, or poles of the relationship: The high end, and the low end.

Review

Conditions to establish Cause and Effect.1. The variables are correlated.2. The cause comes before the effect.3. There are no other variables to explain the

effect.

Review

Correlational Research Methods can identify relations between variables that you measure.

Correlational Research cannot offer strong evidence of cause and effect!

Review

Correlations have several possible causal explanations1. The direction of cause could go either way.2. A third variable could cause both variables.

Review

The Experimental Method allows us to establish cause and effect relationships by manipulating an independent variable in a controlled setting, then looking for its effect on a dependent variable.

These are the foundational ideas to help you think about research more critically.

There are many more details in your book, which can help to improve your ability to evaluate evidence about causes and effects.

Education

Researching cause and effect