Psychology as a Science

In this lecture we will discuss: science - a method for understanding limits of common sense methods of science

descriptioncorrelationexperimentation

evaluating data with statistics sources of error and bias in research

Science vs. Common Sense

Common sense and intuition often tell us about psychology e.g., suppose a study tells us that ‘separation

weakens romantic attraction’ common sense may tell us - “out of sight, out

of mind” or common sense may say the opposite -

“absence makes the heart grow fonder”

Common sense can be inconsistent and based on hindsight

Science vs. Common Sense

Science helps build explanations that are consistent and predictive rather than conflicting and postdictive (hindsight)

Science is based on knowledge of facts developing theories testing hypotheses public and repeatable procedures

Scientific Inquiry

Facts are what need to be explained objective - viewable by others based on direct observation reasonable observers agree are true

Theory is a set of ideas that explains facts makes predictions about new facts

Hypothesis prediction about new facts can be verified or falsified

Methods in Psychology

Setting - field vs. laboratoryMethods of data collection

self-report vs. observationalResearch plan or design

descriptive correlational experimental

Descriptive Study

Describes a set of factsDoes not look for relationships between

factsDoes not predict what may influence the

factsMay or may not include numerical dataExample: measure the % of new students

from out-of-state each year since 1980

Correlational StudyCollects a set of facts organized into two

or more categories measure parents disciplinary style measure children’s behavior

Examine the relation between categoriesCorrelation reveals relationships among

facts e.g., more democratic parents have children

who behave better

Correlational Study

Correlation cannot prove causation Do democratic parents produce better

behaved children? Do better behaved children encourage parents

to be democratic?May be an unmeasured common factor

e.g., good neighborhoods produce democratic adults and well behaved children

Experiments

Direct way to test a hypothesis about a cause-effect relationship between factors

Factors are called variables One variable is controlled by the experimenter

e.g., democratic vs. authoritarian classroom

The other is observed and measured e.g., cooperative behavior among students

Experimental Variables

Independent variable the controlled factor in an experiment hypothesized to cause an effect on another

variable

Dependent variable the measured facts hypothesized to be affected

Independent Variable

Must have at least two levels categories - male vs. female numeric - ages 10, 12, 14

Simplest is experimental vs. control experimental gets treatment control does not

Experimental Design

Levels may differ between or within people Within-subject experiment - different levels of

the independent variable are applied to the same subject

Between-groups experiment - different levels of the independent variable are applied to different groups of subjects

Experimental Design

Random sample - every member of the population being studied should have an equal chance of being selected for the study

Random assignment - every subject in the study should have an equal chance of being placed in either the experimental or control group

Randomization helps avoid false results

Research SettingsLaboratory

a setting designed for research provide uniform conditions for all subjects permits elimination of irrelevant factors may seem artificial

Field research behavior observed in real-world setting poor control over conditions measures may be more representative of reality

Data-Collection Methods

Self-report - procedures in which people rate or describe their own behavior or mental state questionnaires rating scales

on a scale from 1 to 7 rate your opinion of …

judgements about perceptionson a scale from 1 to 100 how hot is ...

Data-Collection Methods

Observational methods - researchers directly observe and record behavior rather than relying on subject descriptions naturalistic observation - researcher records

behavior as it occurs naturally tests - researcher presents stimuli or problems

and records responses

Descriptive Statistics

Variable - something that can vary or change

Dependent variable - something we measure

Data - a collection of measurementsStatistics - summary descriptions of data

(i.e., mean, medium, range)

Descriptive Statistics

Used to describe or summarize sets of data to make them more understandable measures of central tendency

mean, median, mode

measures of variabilityrange, standard deviation

measures of associationcorrelation coefficient

Measures of Central Tendency

What is the average family income above?

Mean - the arithmetic averageMedian - the center scoreMode - the score that occurs the

most

Measures of Variability

Range - the difference between the highest and lowest score in a set of data

Standard deviation - reflects the average distance between every score and the mean

Correlation Coefficient

Often we measure more than one variable

Grade point and SAT scoreAre they related? Correlation statistic is a way to find

out

Correlation Coefficient

Measures whether two variables change in a related way Can be positive (max +1.00)

Negative (min -1.00)

Or not related! (~ 0.0)

Inferential StatisticsDescriptive statistics summarize a data

setWe often want to go beyond the dataIs the world at large like my sample?Are my descriptive statistics misleading?Inferential statistics give probability that

the sample is like the world at large

Statistics and Probability

Probability means how likely something isHow likely are results like mine to occur

by chance? Statistical inferences

significant result - reflects the real world rather than chance, with high probability (e.g., > .95 )

not significant - results reflect chance

Measurement Errors

Why is inference based on probability instead of certainty?

Data can be misleading because of variability

low variability

high variability

Measurement Errors

Why is inference based on probability instead of certainty?

low bias

high bias

Data can be misleading because of bias

Measurement Error

Variability and bias can combine

Variability &Bias

Variability Bias

Sources of Bias

Biased sample - when the members of a sample differ in a systematic way from the larger population the researcher is interested in

Example interested in all voters contact by telephone biased sample - lower economic groups may not own

telephones

Sources of Bias

Observer-expectancy effect researcher has expectations that influence

measurements

Subject-expectancy effect subject knows design and tries to produce

expected resultBlinding

minimize expectancy by removing knowledge about experimental conditions

Blinding

Single-blind study - when subjects are kept uninformed as to the treatment they are receiving

Double-blind study - when both subjects and experimenter are kept uninformed about aspects of the study that could lead to differential expectations

Ethical Issues in Psychological Research

Right to privacyInformed consent

use of deception

Animal rights Is there justification for discomfort or harm a

research procedure may produce?

APA publishes ethical guidelines