Mary Jones. Psychology: The Science of Behavior and Mental Processes Psychologists attempt to understand Observable behavior: Such as speech and physical

Mar

y Jo

nes

Psychology: The Science of Behavior and Mental Processes

Psychologists attempt to understand

• Observable behavior: Such as speech and physical movement

• Mental processes: Such as remembering and thinking, which cannot be directly observed

In This Chapter

The Four Major Research Perspectives

Research Methods Used by Psychologists

How to Understand Research Results


Perspectives Emphasizing

Internal Factors

Perspectives Emphasizing

External Factors


Perspectives Emphasizing Internal Factors

• Views physiological hardware (especially the brain and nervous system) as the major determinants of behavior and mental processing

Biological perspective


• Depression: An Example- Perspective focuses on a deficiency of activity of

certain chemicals in the nervous system as the cause of depression and the use of anti-depressant drugs

- Demonstrates that mood is partly a function of brain chemistry


• Emphasizes how mental processes, such as perception, memory, and problem solving, work and impact behavior

• Addresses how memory retrieval is facilitated

Cognitive perspective

Perspectives Emphasizing External Factors

• Posits that behavior is a result of past history of conditioning within the environment

• Involves two major types of conditioning, classical and operant

Behavioral perspective

Behavioral Perspective

Classical Conditioning• Can explain how we

learn fear and other emotional responses, taste aversions, and certain other behaviors

Operant Conditioning• Involves the relationship

between our behavior and its environmental consequences

Classical Conditioning

Can you think of an example of classical conditioning?

Operant Conditioning

Can you think of an example of operant conditioning?


Descriptive Methods

Correlational Studies

Experimental Research

Beware…the Hindsight Bias May Be Lurking!

What is this bias?

• Tendency after learning an outcome to be overconfident in the ability to predict it

• Belief that findings are more obvious and easier than they actually are

Which Perspective Is Best?

No perspective is better than the

others; all perspectives are complementary

Psychologists use all four

perspectives to get a more complete

explanation of behavior and

mental processing


Descriptive methods

Observational techniques

Case studies

Survey research


Correlational studies

Correlation coefficient

Descriptive Methods: Types

• Three types - Observational techniques- Case studies- Survey research

• Each method seeks to provide objective and detailed descriptions of behavior and/or mental processes

Descriptive Methods: Observational Techniques

Observational techniques

Behavior of interest is directly observed

Naturalistic observation

Behavior being observed occurs in its natural setting, without researcher

intervention

Participant observation

Observer becomes part of the group being observed

Descriptive Methods: Case Studies

Case studies

Individual is studied in depth over

extended period of time

Results of case studies cannot be

generalized

Cause–effect statements based on the findings of a case study cannot

be made

Descriptive Methods: Survey Research

Survey research

Uses questionnaires and interviews to collect information about the behavior, beliefs, and attitudes of particular groups of

people

Wording, order, and structure of survey questions may lead the participants to biased answers

Descriptive Methods: Survey Research

Survey research

Population: Entire group of people to

be studied

Sample: Subset of a population that

actually participates in a research study

Random sampling: Ensures that each

individual in a population has an

equal opportunity to be in the sample

Correlational Methods

Correlational study• Two variables

measured to determine if they are related or how well either one predicts the other

Variable• Any factor that can

take on more than one value

The Correlation Coefficient

Correlation coefficient• Demonstrates the type and the strength

of the relationship between two variables• Ranges in value from -1.0 to +1.0• Uses a plus (+) or minus (-) sign to

convey the type of relationship

Let’s look more closely at each of these relationships

Types: Positive Correlation

• Positive correlation• Indicates a direct relationship

between two variables• Low scores on one variable

tend to be paired with low scores on the other variable

• High scores on one variable tend to be paired with high scores on the other variable

Types: Negative Correlation

• Negative correlation• Shows an inverse

relationship between two variables

• Low scores on one variable tend to be paired with high scores on the other variable

Strength of Relationship

Absolute value• Second part of the correlation coefficient

which ranges from 0 to 1• Zero and absolute values near zero

indicate no relationship

Remember: The sign of the coefficient conveys nothing about the strength of the relationship

Understanding Predictability: Scatterplots

Scatterplots

• Visual depiction of correlational data

• Each data point in the scatterplot is a person's scores on each of the two variables


• Indicates maximal predictability• Shows increasing (a) and decreasing (b) trends


• No relationship between variables

• Minimal or no predictability


• Fairly strong because not much scatter• Indicates correlations with strengths between 0 and 1.0

The Third-Variable Problem

Third-variable problem• Occurs when a third, unmeasured variable

is responsible for the relationship observed between the two measured variables

• Is not controlled in a correlation study

• Cause for observed relationship cannot be determined

Experimental Research

Res

earc

her

con

tro

lIs key aspect of experimental

research

Allows the researcher to make cause-and-effect statements

about the experimental results

Experimental Research: Experimenter Control

Exp

erim

ente

r co

ntr

ol

For influence of possible third-variables

For any possible influence due to individual

characteristics of the participants

What is Random?

Experimental Research: Designing an Experiment

Experiment • Researcher manipulates

one or more independent variables and measures their effect on one or more dependent variables while controlling other potentially relevant variables


Experiment

Hypothesis is made• The hypothesis determines the

prediction to be tested about the cause-and-effect between two variables• Independent variable:

Hypothesized cause; Manipulated by experimenter

• Dependent variable: Hypothesized variable; Measured by the experimenter


Hypothesis is made.

Variables are operationally defined • Description of the operations

or procedures that a researcher uses to manipulate or measure a variable are delineated

• This facilitates replication of the experiment


Hypothesis is made

Variables are operationally defined

Groups are determined• Experimental

group: Exposed to the independent variable

• Control group: Not exposed to the independent variable

• Placebo group: Believes they are receiving treatment but are not• Nocebo effect

Experimental Research: Statistical Analyses

Double-blind procedure may be used

• Control measure in which neither the experimenter nor the participants know which participants are in the experimental and control groups

• Measure controls for experimenter expectations

Design of Aerobic Exercise and Anxiety Experiment


• Indicate the probability that results of a study are due to random variation (chance)

Inferential statistical analyses

• Significant finding is one that has a probability less than 0.05 (1/20) that it is due to chance

• Significant finding does not insure that the result has practical significance or value in our everyday world

Statistical significance


• Significant finding that has a probability less than 0.05 (1/20) that it is due to chance

• Significant finding does not insure that the result has practical significance or value in our everyday world

Statistical significance

Do you know why?


• Statistical technique that combines the results of a large number of studies on one experimental question into one analysis to arrive at an overall conclusion

• Conclusion is considered much stronger evidence than the results of an individual study in answering an experimental question

Meta-analysis

Summary of Research Methods


Descriptive Statistics

Frequency Distributions


Descriptive statistics• Used to describe the data of a research study

in a concise fashion

Frequency distributions• Indicate the probability that the results of the

study are due to random variation

How to Understand Research Results: Descriptive Statistics

Types of descriptive statistics• Measures of central tendency• Measures of variability

Frequency distribution• Depicts the number of participants receiving each score for

a variable in a table or graph

How to Understand Research Results: Measures of Central Tendency

Central tendency• Designed to summarize a set of data with a single

score

Three measures of central tendency• Mean: Numerical average for a distribution of score• Median: Score that is positioned in the middle of the

distribution of scores when scores are listed from lowest to highest

• Mode: Most frequently-occurring score in a distribution of scores

That’s One Mean Statistic!

Mean

• Is most commonly used measure of central tendency

• Used to analyze data in many inferential statistical tests

• Can be distorted by extremely high or extremely low scores because it uses all scores in its computation

How to Understand Research Results: Measures of Variability

Measures of variability• Designed to provide an idea of how scattered a set of

scores tends to be

Two measures of variability• Range: Difference between the highest and lowest scores in

a distribution of scores• Standard deviation: Average extent to which the scores vary

from the mean of the distribution

Summary of Descriptive Statistics

How to Understand Research Results: Frequency Distributions

Frequency distributions

• Organizes the data in a score distribution so that the frequency of each score can be determined

Types of distributions

• Normal distributions

• Skewed distributions

How to Understand Research Results: Normal Distributions

Main aspects of normal

distribution

Mean, median, and mode are all equal because the

normal distribution is symmetric about its center

Percentage of scores falling within a certain number of standard deviations of the

mean is set

How to Understand Research Results: The Normal Distribution

How to Understand Research Results: Normal Distributions with Different Standard Deviations

How to Understand Research Results: Percentile Rank

Remember: The percentages of scores and the number of

standard deviations from the mean always have the same relationship

in a normal distribution

Percentile rank: Percentage of scores below a specific score in a

distribution of scores

How to Understand Research Results: Skewed Distributions

Skewed distributions

Asymmetric frequency distribution in which some unusually high

scores distort the mean to be greater

than the median

• Right-skewed (also called positively skewed) distribution

• Left-skewed (also called negatively skewed) distribution

Sample Skewed Distributions

Skewed Distributions

Distortions

Distortion occurs for the means of skewed

distributions, because unusually high or low scores distort the mean

Consequently, with a skewed distribution, median should be

used because atypical scores in the

distribution do not distort the median

An Example of a Right-Skewed Distribution

Documents

Mary Jones. Psychology: The Science of Behavior and Mental Processes Psychologists attempt to understand Observable behavior: Such as speech and physical