Research Methods in Psychology. Josh and friends were discussing recent changes in the DUI laws. Jasmin stated that anyone can drink a few beers with.

• Research Methods

in Psychology

Josh and friends were discussing recent changes in the DUI laws. Jasmin stated that anyone can drink a few beers with no impact on their driving. Ben said a few beers would impact Jasmin but not a big guy like him.

The discussion raised questions in Josh’s mind on just how much beer it takes to impact driving. He then wondered how to go about answering this question.

In this chapter we will explore how Josh might explore the impact of drinking beer on driving.

What is “Good” Research?

• Good research– Is done in a systematic and deliberate manner– Uses agreed upon procedures – Can be repeated (replicated) by other

researchers

• The more you learn about research methods, the more you will recognize how much poorly designed research exists

Theories

• A theory attempts to provide a framework for studying some aspect of behavior

• Theories are abstract statements of relationships that are designed to describe behavior in a very broad manner

• For our study of alcohol consumption and driving, our theory suggests a relationship between alcohol and performance

Hypotheses

• Hypotheses are specific tests of theories • Hypotheses for our study include:

– Hypothesis 1 suggests that the more beer subjects drink the more likely they will run into an orange cones in a driving experiment

- Hypothesis 2 suggests that those served “near beer,” will run into fewer orange cones than those who drank real beer

- Hypothesis 3 suggests that there is no relationship between body weight, alcohol consumed, and the number of cones hit

Theories & Hypotheses

• Let’s try a metaphor:

• The apex of the umbrella represents a theory

• Each spoke of the umbrella represents a different hypothesis

• Each spoke touches the apex (theory) and can also touch the ground (real world) when you set the umbrella upright

• The apex (theory) of the umbrella never touches the ground. It’s links to the ground are the hypotheses (spokes of the umbrella)

Hypotheses and Variables• Hypotheses measure some form of behavior

• The things being measured are called variables– Variables vary, they are not static

• Continuous variables involve amounts– Temperature– Blood alcohol level– Body weight

• Categorical variables involve either/or circumstances– Male/female– Real beer/near beer

Independent Variables

• Independent Variables (plural)

• Things the researcher manipulates (controls) as part of a study

• For our experiment the researcher would control– Amount of alcohol each subject consumed

– Spacing of the orange cones

– Type of vehicle used

– Weight of subjects

Dependent Variables• Dependent Variable (singular)

• The behavior being investigated by the researcher

• Not under the direct control of the researcher

• Only one dependent variable for each study

• In our study the dependent variable is the number of orange cones hit by each subject

• The dependent variable must be able to fail

Standardized Procedures

• For research to be effective subjects need to be treated in the same way as much as possible

• For example:– Same model of car in the driving experiment– Same kind of alcohol (beer/wine)– Same distance between orange cones

Samples

• Since it is impossible to include everyone in a given experiment, researchers use a “sample” of people who were selected to represent the “population” their drawn from

• For example, a small group of students serve as a “sample” of all the students from a university

• Professors could not be in a sample of students as they are not from the same population (students on campus)

Internal Validity

• Internal Validity addresses the way a study is constructed

– The design of the study must be sound

– If the researcher didn’t record how much alcohol students consumed then the study’s internal validity would be poor

External Validity

• External validity refers to he ability to generalize beyond the sample

• If we used 18-20 year old college students in our study is it reasonable to generalize our findings to:

• 18-20 year old college students from across the USA

• 18-20 year old college students from anywhere in the world

• But not to a group of 40 + old alcoholics in a treatment center

Objective Measures

• Objective measures are designed to control for the researcher’s inherent bias

• Let’s look at two examples of poor objectivity. Which of the following questions was submitted for a survey by the NRA and which one by Handgun Control:

– Do you support our Constitution’s Bill of Rights , including the 2nd

Amendment’s Right to Bear Arms?

– Do you support anyone having access to guns, including convicted criminals, drug addicts, and child molesters?

Reliability of Measures

• Reliability refers to how consistently a measure comes up with similar results

• Professors normally use several measurements to ensure they have a reliable estimation of each student’s performance

• Those who do well on exams usually write excellent papers

• A measure is unreliable if we cannot depend on it to produce similar results over repeated trials

Test-Retest Reliability

• Administer a test this week

• Administer the exact same test a week later

• The scores should be similar, not exact, but similar

Internal Consistency

• Internal consistency involves consistency of answers across several items

• Do you like mushrooms?

• Do you like mushrooms with ketchup?

• Do you like mushrooms on pizza?

• (If you don’t like mushrooms, then you should answer no to the other questions)

Interrater Reliability

• Several individuals rate a variable on a given scale

• Three raters stand at an intersection and record subjects estimated age– 0-30 years old – 30-60 years old– 60 + years old

• If two raters estimate a subject as being 30-60, and two rate the subject as over 60, we have poor interrater reliability

• Often used in naturalistic observation studies

Validity

• Validity addresses whether a tool is measuring what it is suppose to measure

• Once you establish than a measure is reliable then you determine if it is valid

• A researcher never addresses whether a measure is valid until is first demonstrated that it is reliable

• You might say we have lots of RVs in the world of research but not a single VR

Validity

• Suppose when you applied for a driver’s license you were measured on the following:

• Drive around the block and not hit anything

• Park the car between two orange cones

• Take a paper and pencil test on street signs

• Take a shorthand test

Shorthand test to drive a car?

• Reliability– Very good reliability as everyone consistently

fails the shorthand test

• Validity– Poor validity as shorthand has nothing to do

with driving a vehicle

Forms of Validity

Face Validity:

– Does a question look like it belongs on a measure

– Shorthand test to drive a car would have very poor face validity

Forms of Validity

Construct Validity:– Convergent

• A measure correlates with similar tools designed to measure the same phenomena under investigation

– Discriminate Validity• The measure correlates poorly with tools of an

unrelated nature

Forms of Validity

Criterion– A measure’s ability to accurately differentiate

among those in a sample

• Difficult, but fair, final examination has good criterion validity

• An easy exam that everyone passes easily has poor criterion validity

Error

• Studies involving humans are never 100% accurate

• The difference between the actual outcome and 100% is referred to as “error”

• Any measurement of humans- Measurement & Error

• The lower the error rate the better the measurement tool

• Good research often involves the use of multiple measures in order to reduce the degree of error

Descriptive Research

Descriptive research describes phenomena as it exists in the “real world”

Case Study

• In-depth observation of one person (or small group)

• Difficult to generalize results beyond the person under investigation

• Interpretive approach involves trying to understand why this one person did what they did (hit their partner)

• Very susceptible to researcher bias

Naturalistic Observation

• In-depth observation of a phenomena in its natural setting

– Observe how many people wear a team jersey on game day

• No contact with subjects

– Researchers count how many people wear jerseys and how many do not

• Can only record “what is” and cannot ask the subjects “why”

• Researcher try to not be noticed by those being observed

Survey Research

• Ask subjects questions– In person, paper and pencil, on line

• A key issue is the honesty of responses– Asking your peers how many beers they drank as they

are getting in their cars to drive home

• Did the intended person actually competed the survey– A survey for a CEO is delegated to a subordinate of the

CEO

Survey Research

• Surveys often use samples from a given population

• Stratified Random Sample– Breaks up sample by some criteria– 40% of sample to be male– 20% males over 50 and 20% males under 20

Mean, Median, Mode

• Mean– Add up all scores, divide total

by number of scores and you have the arithmetic mean for a group of scores

• Median– Have the scores in a sample

are above the median score and half are below it

• Mode– Most frequent score in a

sample of scores

• Scores:– 10,10,10,9,9,11,11=70

• Mean– 70/7=10

• Median– 10– 2 scores over 10– 2 scores under 10

• Mode– 10 (Three 10s)

Range and Standard Deviation

• Range– The difference between the lowest and highest

scores in a sample

• Standard Deviation– The amount a given score deviates from the

mean of a sample

Experimental Research

• Involves manipulation of independent variables in order to determine the impact on a dependent variable

• Designed to confirm a causative connection– Doing this causes that

• In our hypothetical experiment:– # beers given to subjects & spacing of cones-

Independent variables– # of orange cones hit- Dependent variable

Steps in an Experiment• Form a hypothesis

– Beer and hitting cones

• Operationalize Variables– Brand of beer, drive through cones, type of car, etc.

• Develop a standard procedure– Control Group (near beer)– Experimental Group (real beer)– Demand Characteristics (same person talks to subjects)– Blind Studies (Subjects won’t know if real or near beer)

• Select and Assign Participants

Experimental Research

• Apply Statistical Analyses of Data– Descriptive

– Inferential • Probability Theory

• Draw Conclusions– Be very conservative

– In this study beer consumption appears to impact driving ability

– Suggest further research efforts

Correlational Research

• Explores the degree to which two variables are related

• Correlational Coefficient= – The statistic used to compare to variables

– Range: -1.0---1.0

• Correlation does not equal Causation– Even if two variables have a causative relationship,

correlational research doesn’t check for it

Correlational Research

• Positive Correlation– Two variables move in same direction

• Caloric intake and body weight

• Negative Correlation– Two variables move in opposite directions

• Exercise and body fat

• No correlation– Two variables demonstrate no pattern of predictable

movement• Height and SAT scores

Evaluation a Research Study

• Does the theoretical framework make sense?

• Is the sample adequate and appropriate?

• Are the measure and procedures adequate?

• Are the data conclusive?

• Are the broader conclusions warranted?

• Does the study say anything meaningful?

• Is the study ethical?

The Conference

• Josh eventually finished his research study that involved:– 200 subjects– 100 male & 100 female subjects– Budweiser beer in cans and near bear– Beer was transferred to unmarked glasses– The person handing out the beers didn’t know

if it was real beer or near beer– Controlled for subjects weights– Used a common access Ford Mustang

The Conference

• Josh wrote his research paper, ran it past his professor and then got accepted at an academic conference on substance abuse

• Academic conferences serve as an opportunity for colleagues to review one’s research before you attempt to get in published in a journal

• Here is a sample of the kind of questions Josh might expect

Conference Questions

• Bob Wright:

– As Budweiser beer is brewed in numerous locations across the country, with each location being a different age, different (more or less modern) brewing equipment, and having different water sources, did you check the beer cans to ensure they came from the same brewery?

• Jan Smith:

– Did you use a medical scale or some inexpensive discount house scale to measure the students weights? If the later, how much variance between the recorded weights and the subjects actual weights might exist?

Conference Questions

• Jacque LeSeur:– You stated that you used a Ford Mustang? Was

this the new model Mustang or one of the original Mustangs? This is important as the two models have very different wheel bases.

What else did Josh miss???????