Research requires a testable hypothesis and systematically gathered data
This approach is important because
Anecdotal evidence is often meaningless
We need a clear and objective way to compare differences and possible outcomes



The independent variable is manipulated to study its effect

This may be a variable that the experimenter does not actively control, such as gender.

This may also be the condition a participant is in for an experiment
The dependent variable is the participant’s response



Quantitative: Numerical variables that represent quantities

Ex. height, weight, time spent on a task, etc.
vs.
Categorical/Nominal: A name or a symbol indicating belonging to a group


Ex. profession, gender, etc.
Numbers are sometimes used as category labels

Ex. calling the first base player “1”, second base “2”, etc.

 When a number is used as a label, the numbers cannot be added to each other
+

Quantitative variables can be discrete or continuous
 Discrete


There are a limited number of possible values for the variable
There are gaps between the numerical values of the variable

Ex. The number of pairs of shoes that you have
 Continuous

The variable can have an infinite number of possible values

No matter how close the numerical values are, there can be another value between them

Ex. reaction times of 23.4 seconds and 23.5 seconds

Values in between can be 23.41, 23.411, 23.412 etc.

 Mean
 Median

Mode



The mean is the most commonly used average
It is the sum of the data points, divided by the number of data points.
 For example, if I wanted to find the average age of a group of friends:
Ages: 26, 27, 27, 27, 28, 29, 30, 31, 32
26 + 27 + 27 + 27 + 28 + 29 + 30 + 31 + 32 = 257
257/9 = 28.5
The mean age is 28.5 years




The mode is the most repeated data point in a set
The mode is primarily useful for categorical variables

Ex. if you were buying t-shirts for a large group of people, the most common size would be useful information
It may also be used for ordered discrete categories

Ex. participants are asked to rate a movie on a scale of 1 – 5.
The mean rating may be 4.2, but participants were only allowed to give whole number answers. Therefore, the mode would be 4.

 Sometimes there are two modes. If the modes are far apart, the data set is considered bimodal.

Ex. t shirt sizes: S, S, S, S, S, S, M, M, L, XL, XL, XL, XL, XL, XL




The median is the midpoint in an ordered set of data
It divides a set of data points into two halves, with an equal number of data points above and below it
In the example where I was finding the average age of a group of friends:
Ages: 26, 27, 27, 27, 28, 29, 30, 31, 32


Note that the numbers MUST be in order for this to work
Ages: 27, 31, 26, 27, 32, 27, 30, 29, 28
Wrong!

If there are an even number of data points, the two middle ones are averaged using the mean
26, 27, 27, 27, 27, 28, 29, 30, 31, 32
(27 + 28)/2 = 27.5



Imagine you were trying to determine the average number of children in a family
The mode would probably be the best average to use because one cannot have .5 of a child

 An outlier is a data point that is far apart from the rest of your data


Ex. I’m trying to find the average age of the group I’m with, and my grandmother joins us
Ages: 26, 27, 27, 27, 28, 28, 29, 30, 31, 32, 87



The median is unaffected by outliers

Ages: 26, 27, 27, 27, 28, 28, 29, 30, 31, 32, 87
The mean is affected by outliers:

Mean without my grandmother = 28.5

Mean with my grandmother = 33.82

 The standard deviation (SD) tells us how much the data spreads out from the mean

How much do the data points vary from each other?

Z-Scores (or standard scores)
 Z-scores are based on standard deviation from the mean



Using z-scores lets us compare the meaning of data points from different sources
The z-score provides information about where a data point is relative to the average
A z-score of 1 means that the data point is 1 standard deviation above the mean (2 is 2 standard deviations above the mean, etc.)

Imagine you and a friend are trying to figure out which one of you performed better on an aptitude test.
however
You each took a completely different test.

 You got a score of 36, your friend got a score of 100

The average score on your test is 30, with a standard deviation of 3.

Therefore, your z-score is 2

The average score on your friend’s test was 80, with a standard deviation of 20.

Therefore, their z-score is 1
Therefore, you performed well above the mean, whereas your friend performed slightly above the mean





The mean is in the center
Approximately 68% of data points are within
1 SD of the mean
95% of data points are within 2 SD of the mean
Almost all data is within 3 SD of the mean

 If you are dealing with large number values, it is OK if the SD is larger.
 i.e., the standard deviation may seem small or large relative to the numbers your are dealing with

For example, you are catering a dinner party and 10 extra people show up.
 If you were expecting 100 people, the 10 more will not be a problem and you’ll still have enough food.
 If you were expecting 20 people, 10 more is a relatively large number of extra guests and you will not have enough food.



We look for patterns to make sense of things, and sometimes see patterns when there is really no pattern or relationship there




“Lucky” items

You will have success at times when you have the item.

You will also have failure at times when you have the item.
It’s also quite likely that the item will “make” you more successful by boosting your confidence (self fulfilling prophecy)
If you attribute too much to luck, you may also be less likely to put in effort (therefore making it seem unlucky!)

Example: The Sports Illustrated cover jinx
 The idea that an athlete will have a run of bad luck after appearing on the magazine cover
 What really may be happening:

Athletes fluctuate; more people may notice after the athlete is brought to their attention

An athlete will probably be featured on the cover at the peak of his or her career; at some point, they are bound to stop performing so well

Example: We attribute major changes to whomever holds office when something good or bad happens
 There are natural fluctuations (in the economy, crime, etc.) that have nothing to do with who’s in charge


Imagine that you have flipped a (fair) coin three times, and gotten heads each time.

How likely do you think it is that the next flip will be heads?


The next toss is no more or less likely to be heads than tails

Each toss, there is the same chance of getting heads or tails



On the old game show Let’s Make a Deal, a prize was hidden behind one of three doors.
The contestant would choose a door; Monty Hall then eliminated a no prize door and offered the contestant the chance to change their choice.
Do you think it was better to change doors, keep the first choice, or no difference?

 Initially, you had a 1 in 3 chance of getting the prize
 After a door is eliminated, what are your chances of winning a prize?



People generally believe that after a door is eliminated you have a 1 in 2 chance of winning
In reality, you have a 2 in 3 chance of winning

A headline shown on Jay Leno’s show said “The average American is getting older.” His addition was
“the average American doesn’t have a choice!”
 Statistically, the statement does make sense. The headline was actually stating that the mean age of
Americans is increasing.

Studies find that 3 in every 4 people make up 75% of the population

They say that 1 in every 4 people suffers from some form of mental illness. Look at your three closest friends. If it’s not them, it’s you.



Type 1 Error:


A false positive
Finding a difference when there really is none
Type 2 Error


A false negative
Finding no difference when there really is a difference

Participants in a study are usually in a control condition or experimental condition
 In the control condition, there is no manipulation
 In the experimental condition, there is a manipulation or extra information given



The Null model says that the experimental conditions will give a result no different from average/chance
The full model says that the experimental conditions will give cause a different outcome

The goal of basic research is to increase understanding of human behavior.

The goal of applied research is to increase understanding of real world needs and contribute to the solution of problems

Naturalistic observations

The researcher observes but does not manipulate or become actively involved with the subjects


Case studies

Observational research in which one person is studied intensively


Experimental

The researcher obtains a group of participants and manipulates conditions

Establishes cause and effect



Correlational

Examines the association between two variables

Correlations can be used for predicting and generating hypotheses

Correlations are often useful when one cannot manipulate variables





Worksheet

 T-tests are used to compare the null and full models.




ANalysis Of VAriance
An ANOVA is used instead of a t-test if there are 3 or more variables
An ANOVA can be used to look at subcategories of variables



The chi square is used with categorical variables
It looks at how many observed data points fit in a category compared to the number of expected data points in that category.

For example, if you were trying to find out if there is a difference in the number of men and women who like action movies.

Imagine you are doing a survey on whether there is a difference in the number of men and women who like action movies.
Your categories are:
1.
Action Movies Yes
2.
Action Movies No
----------------------------
1.
Male
2.
Female

Imagine you are doing a survey on whether there is a difference in the number of men and women who like action movies.
The null hypothesis says that the numbers of men and women who like action movies are equal.
Therefore, one might expect that if everything were left completely to chance, half of each group would like action movies, half of each group would dislike action movies.
You have 100 participants, 50 male and 50 female

Action Movies
Like
Count
Expected
Dislike
Count
Expected
Male Female
90
50
10
50
25
50
75
50

 When constructing an experiment, you need to clearly define what you are going to study and how

Statistics in Advertising:


Many commercials use statistics.
For example, everything seems to be recommended by
“4 out of 5” members of a profession

Statistics in Advertising:
However, they never explicitly define what the given alternatives were
 “4 out of 5 dentists recommend this brand of sugarless gum”

In some of these studies, the dentists were asked what they recommend for patients who chew gum.


They were given the multiple choice answers: regular, sugarless, or none
The 1 in 5 recommended “no gum”
 “4 out of 5 doctors favored this brand of pain reliever”

Statistics in Advertising:
However, they never explicitly define what the given alternatives were
 “4 out of 5 doctors favored this brand of pain reliever”



What were the other options?
Reportedly, in some of these surveys the possible answers were
“our brand” or “none”
This really means that doctors did not necessarily favor a given brand, but they find it more effective than nothing at all

 Another example of defining variables comes from a former classmate who wanted to study when parents start teaching their sons vs. daughters about money.

She did not explain what she meant by money:


“This is a dime, it’s worth 10 cents; this is a quarter, it’s worth 25 cents; etc.”
“Money needs to be earned and saved.”


“Money is used to buy things.”
“We do have money, they don’t./We don’t have money, they do.”

All research methods used must be reliable and valid!

Does the method measure what you are trying to measure?



Will the measure give you (approximately) the same results each time?

For example, if within a matter of 3 minutes a thermometer gives temperatures of 98.6, 101.3, and 95.4 it is not reliable.
Will other researchers using the same method agree with your results?

Short Term vs. Longitudinal


Short term research gathers data over a short amount of time (generally one incident)
Longitudinal research collects data over extended periods of time, sometimes following the same participants from birth to adulthood

Twin Studies
 Twin studies use pairs of twins (identical or fraternal)

Some use twins who were raised separately and then compare them to each other (to study the impact of genetics vs. environment)

Independent Groups (or between subjects design)
 Each participant is in only one condition
 Each participant is assigned to a group independently of all other participants vs.
 Matched Pair Design

Within Subjects

Matched Pair Design
 Each participant is in only one condition, but the assignment of one participant dictates the assignment of the second participant.
vs.

Within Subjects

Independent Groups (or between subjects design)

Within Subjects Design


Each participant is studied in multiple conditions
The participant obtains two scores, which are compared

Ex. if each student was in the reward and no reward condition for the boring task vs.

Independent Groups (or between subjects design)
 Matched Pair Design

Double Blind
 This structure is normally used in drug studies



Some participants are given the actual drug, others are given a placebo (an inactive pill)
Neither the participant nor the experimenter knows what the participant is taking
This prevents the experimenter from treating participants differently based on which condition they’re in

 In the placebo effect, a person who is given an inactive pill experiences benefits and side effects from the “drug”
• Placebos are used as a control condition in drug studies

There are multiple theories about what makes the placebo effect work
The participant wants to please the researcher, so they respond accordingly
• (“The doctor gave me a pill to make me feel better, so I will.”)

There are multiple theories about what makes the placebo effect work
 The participant expects the treatment to have certain outcomes, and therefore produces those outcomes.
(This is based on internal motivation, not the external motivation of pleasing someone else.)
 The brain expects a certain reaction to a pill and causes the body to physiologically react that way.

 How we answer self-report questions usually doesn’t depend on our own personal answer in a vacuum; we look for comparison points

Self-reports rely on the following happening:


The participant will accurately interpret the researcher’s question
The participant then honestly answers the question

The researcher will accurately interpret the participant’s answer

How do people answer self-report questions?
 One theory on the steps taken when answering a question include that one interprets what is being asked, finds an answer and possibly adjusts it to fit a series of given choices, and finally may edit the answer to make it desirable

Context and Intent
 How the question is framed and who’s asking
 Desirable vs. undesirable responses

What is “normal” or socially acceptable?
 Threatening vs. Non-Threatening

 Interpreting what is being asked requires an understanding of the questioner’s intent.
 Imagine being asked to rate your health as being excellent, good, fair, or poor.
 The examinee is required to think in the following terms:

 Counting the number of visits to the doctor
 Emotional health vs. physical health

“Relative” health/comparisons to:

One’s usual state of health
 The health of people in general
 The health of peers
Groves, Fultz & Martin (1992)


People want to appear desirable to whomever is asking the question.

Ex. asking teenagers about drug use



If a teenager is questioned by an adult, he or she is less likely to admit to drug use.


It would be threatening to report drug use.
If a teenager is questioned by another teenager, he or she might exaggerate drug use to appear
“cool.”
It would be non-threatening to report real incidences of drug use
Schwarz & Oyserman, 2001



Pepsi Challenge

A Pepsi representative would set up a table and offer people a sample of coke and a sample of Pepsi and then ask which they preferred
Supposedly, more people preferred Pepsi



A person might be more tempted to say they preferred
Pepsi to appease the Pepsi representative
When I took the
Pepsi challenge, people were offered a prize if they reported preferring Pepsi, further skewing the result


It is assumed that anything said is said for a reason and is therefore relevant to your interpretation of the question.

Clearly, it is also desirable to answer relevantly.

Researchers identifying themselves as personality psychologists or as social psychologists asked participants to explain hypothetical behavior.

Answering Relevantly
(continued)
 Participants who believed they were answering for social psychologists gave social explanations.
 Participants who believed they were answering for personality psychologists gave trait explanations.
Schwarz, 1999


The context behind a question provides clues to the questioner’s intention.
 Understanding the context and intention gives information about what would make a desirable answer.

 Imagine being asked to report your daily levels of stress.

OR
Imagine being asked to report your daily levels of stress leading up to a stressful event.

(continued)
 Reporting increased stress is appropriate and
“desirable” in the context of a stressful event.
 Acknowledgement of a stressful event in a question implies that the event is relevant to your response.
Eisenkraft, 2004



Two week long study using undergraduate students in an intro psych class
Participants were given a “daily diary” to complete every night before going to bed and two “weekly diaries” to complete once a week


The daily diaries asked participants how many hours they had spent since the previous day in class, sleeping, socializing, and studying
The weekly diaries asked participants on average how many hours they’d spent per day in each activity over the previous week

Results were obtained by calculating the arithmetic means of daily hours spent in activities (daily average) and the arithmetic mean of the weekly estimates (weekly average).
Daily average reports were compared to weekly average reports.



In weekly diaries, participants reported having spent significantly more time in class than in daily diaries

Participants reported fewer hours sleeping in weekly diaries

Participants reported more time studying in weekly diaries
There was no difference in reports of time spent socializing

An honest error in memory


Time spent socializing was usually concentrated over a few days, making it easier to keep track of the total number of hours for the week
Participants may have estimated hours spent in class per week based on their schedules and how much time should have been spent in class

Forgetting times when a professor dismissed the class early, or a student came in late

Protecting Image

Participants reported spending more time studying
(desirable behavior) and less time sleeping

This interprets sleeping as a less desirable behavior – less time spent sleeping would imply more time spent studying

There is less motivation to alter the report of hours spent socializing


Less socializing implies the person is not popular
More time socializing implies the person is neglecting their studies

Self Report and Depression
Self Report depression measures are often used in large screenings, such as at university health centers

Self Report and Depression
 Participants were divided into three conditions
 All used the same questionnaire, BDI-II
 The conditions varied by the title put on the questionnaire:

Student condition said “Student Responses to the Depression
Questionnaire for Students”

Psychiatric condition said “Student Responses to the
Depression Questionnaire for Psychiatric Patients”

Neutral condition said “Student Responses to a Depression
Questionnaire”
Participants completed the questionnaire online

Pick out the one statement in each group that best describes the way you have been feeling during the past two weeks, including today.
1. Sadness
0 I do not feel sad.
1 I feel sad much of the time
2 I am sad all of the time.
3 I am so sad or unhappy that I can't stand it.
2. Pessimism
0 I am not discouraged about my future.
1 I feel more discouraged about my future than I used to be.
2 I do not expect things to work out for me.
3 I feel my future is hopeless and will get only worse.
4. Loss of Pleasure
0 I get as much pleasure as I ever did from the things I enjoy.
1 I don't enjoy things as much as I used to.
2 I get very little pleasure from the things I used to enjoy.
3 I can't get any pleasure from the things I used to enjoy.

Self Report and Depression

After completing the questionnaire, participants were asked demographic questions, including:

Whether the participant had seen the BDI previously


If the participant was in treatment for a mood disorder
The participant’s major

Self Report and Depression


Participants who were in the psychiatric condition and in treatment for a mood disorder had the lowest score
Participants who were in the student condition and in treatment for a mood disorder had the highest score

Self Report and Depression
Condition
Psych
Student
Treatment Mean
Yes 7.47
No
Yes
No
11.01
21.00
8.63

Self Report and Depression
 Participants who were in the psychiatric condition were significantly more likely to leave comments than participants in the student or neutral condition
50% of participants in the psychiatric condition left comments vs. 18.6% of the participants in the student/neutral condition




Needs more range between “completely fine” and 1 st degree of “I feel crappy”
Ridiculously negative. I feel better about myself than
I used to, and yet my only choices were between feeling the same as ever or three stages of feeling worse.
There should be more middle ground between the 1 st and 2 nd selections. For instance, I feel sad sometime wasn’t an answer it was either I feel sad never or much of the time

Self Report and Depression
Comments
None
Psych
Count 15
Expected 21.2
Student/
Neutral
48
41.8
Yes
Count 15
Expected 8.8
11
17.2

Self Report and Depression

For participants who were not in treatment and in the psychiatric condition:

The title of the condition was not threatening and they did not hesitate to report some level of actual symptoms

While as a non-psychiatric patient the participant should not have a high score, if the questionnaire was being used with students then it must be somewhat relevant to them

Self Report and Depression

For participants who were in treatment and in the psychiatric condition:

The title was more threatening and primed thoughts about stigma

The participant would then refrain from reporting depressive symptoms in order to distance him or herself from the negative impressions of what a psychiatric patient is

Self Report and Depression

For participants who were in treatment and in the student condition:

The participant would identify with the symptoms and not feel threatened by reporting them

The participant may have compared him or herself to the other people completing the questionnaire

The participant would over report symptoms because any symptom should be more severe than other students’

Self Report and Depression

Participants in the Psych condition leaving more comments suggests that they did find the process of completing the BDI-II more disturbing.

Many comments reflected on the gap between the first and second answer choices, complaining that the first option was no symptoms and there was no middle ground

This supports the idea that participants in the Student and
Neutral conditions felt that the questionnaire gave more appropriate options, and therefore a “no symptoms” answer in the Student or Neutral conditions meant something different from a “no symptoms” answer in the Psych condition.


Note: this would normally require a signature
This study is examining students’ responses to a Depression
Questionnaire.
There is no anticipated risk involved in participating in this study, but questions are about a sensitive topic and you may decide to discontinue your participation at any time without penalty.
Responses are anonymous.
Please answer each question honestly.
Please click here to verify that you are over the age of eighteen years and choose to participate.
Button: (No) and (Yes. Continue to Depression Questionnaire)

The questionnaire that you completed is called the Beck Depression Inventory II (or
BDI-II). The purpose of this study is to look at whether the description of the questionnaire and heading will influence participants’ answers. In reality, the BDI-
II is used in a variety of settings and is not intended solely for a specific population.
If you choose to forward the main webpage link to others, please do not disclose the purpose of the study because that may influence the results. If you have any questions, or are interested in the results, you may contact me at mse214@nyu.edu
.
Everyone occasionally feels blue or sad, but these feelings are usually fleeting and pass within a couple of days. When a person has a depressive disorder, it interferes with daily life, normal functioning, and causes pain for both the person with the disorder and those who care about him or her. Depression is a common but serious illness, and most who experience it need treatment to get better.
Many people with a depressive illness never seek treatment. But the vast majority, even those with the most severe depression, can get better with treatment.
Intensive research into the illness has resulted in the development of medications, psychotherapies, and other methods to treat people with this disabling disorder.
(from http://nimh.nih.gov/health/publications/depression/introduction.shtml
)