Research Methods in Psychology

CorrelationA statistical value of the relationship between two variables

Positive Correlation

As one number increases, the other increases.

Ex: Study time to GPA

Negative Correlation

As one number increases, the other decreases.

Ex: Absences to GPA

No Correlation

Variables do not affect one another in a significant way

Ex: Height to GPA

Correlation Coefficient

• Ranges from -1.00 to 1.00

• Zero is no relationship

• -0.85 is a stronger relationship than .34

• CORRELATION IS NOT CAUSATION!!(i.e. Just because two variables have a correlation

does not mean one causes the other)

CORRELATION IS NOT CAUSATION!!!• People that floss everyday live 3 years longer than those that do not.

• Red wine drinkers live longer than those that do not drink red wine.

• As speed limits increased on America’s highways, the death rate went down.

• Women with breast implants commit suicide 3 times as often as those without breast implants.

• Children who are played Mozart in the womb have higher IQ’s.

• Marijuana users in youth are more likely to have mental illness as adults.

• As ice cream sales increased, so did shark attacks.

• More TV’s per person in a country, the longer people live.

Illusory Correlation

The Experiment• Only research method capable

of showing cause and effect

Experimental Method• Review Literature of Past Research

• Formulate Hypothesis• Design Research/Study Method

(naturalistic observation, case studies, surveys, experiments, etc)

• Collect the Data• Analyze the Data • Report the Findings (journal,

critique, replicate)• Draw Conclusion or Theory on

Explanation of Findings

Hypothesis• A statement about the relationship between two or more

variables• Must be testable and refutable• Instead of proving the hypothesis, science usually tries to

disprove a null hypothesis.

Null Hypothesis (H0): opposite of hypothesis

Statistical Significance : 95% not due to chance

Hypothesis Example:

H1: Gender has an effect on spatial ability

H0: Gender does not have an effect on spatial ability

Variables• Independent Variable (I.V.): manipulated by

experimenter

• Dependent Variable (D.V.): MEASURED variable influenced by independent

• Operational definition

• Confounding/extraneous variables

Control Group

• No treatment or placebo

• Serves as basis for comparison

• Serves to eliminate alternative explanations

Population – The larger group of people from which a sample is drawn

Sample: Representative of the population

Two ways to get sample

Random: Every member of the pop has = chance

Stratified: Sample is put together by picking a

group statistically equal to the population

Control Measures• Counterbalance: controls for order effects

• Single-Blind: subject unaware of assignment

• Double-Blind: subject and experimenter unaware of placement

• Randomization– From population (sample)– From assignment to groups (assignment)

Other Research MethodsEx Post Facto (after the fact)

- Independent variable already present

- Not a true independent variable, no cause and effect

- Often used due to ethical concerns

Naturalistic Observation

- Natural setting: behavior is not interfered with or altered

Survey Method

- Gathers data on attitudes and behaviors.

Case Study

- Intense study of an individual

Flaws in Research

• Sampling Bias

• Overgeneralization

• Placebo effect

• Hawthorne/Barnum effect

• Demand Characteristics

• Experimenter Bias

Evaluating Research

STRENGTHS AND WEAKNESSES OF

Experiment

Correlation

Surveys

Naturalistic Observation

Case Studies

Ethics in Research• Participants are free to withdraw at any time

• No undo stress

• Subjects informed of significant factors that may influence their willingness to participate

• Subjects should be debriefed

• Ethical treatment of animals

• Generally research goes before a review board for approval

StatisticsDescriptive Statistics

Organize and summarize data

Central Tendency: mean, median, mode

Standard deviation: variation in data

Range: distance from smallest to largest

Inferential Statistics

Interpret data and draw conclusions

Used to test validity of hypothesis (t-test)

Standard Deviation

Statistical Significance• Probability results are due to chance • Inferential stats (t-test) are used to

check for either a 5% (p<.05) or 1% (p<.01) level of significance.

Lottery tickets 14, 3, 27, 41, 18

1, 2, 3, 4, 5

Coin flips HHHHHHH or HHTHTHT

More likely?

68% are within One standard deviation from mean

95% are within Two standard deviations from mean

Bell or Normal Curve

Measures of Central Tendency

A Skewed Distribution

Skews