chapter 5 correlational and quasi experimental deisngs

correlational study

is one that is designed to determine the correlation, or degree of relationship, between two traits, behaviors, or events.

correlational study

, selected traits or behaviors of interest are measured first

correlational study

degree of relationship, or correlation, between the numbers is determined through statistical procedures.

simple correlations

Relationships between pairs of scores from each subject are known as .

Product Moment Correlation Coefficient (r)

is the most commonly used pro-cedure for calculating simple correlations

-1.00 and +1.00

Because of the way the statistic is computed, the values of a correlation coefficient can only range between

The sign (plus or minus)

tells us the positive or negative direction of the relationship;

the absolute value of r (the unsigned value)

tells us the strength of the relationship

scatterplots

(also known as scattergraphs or scattergrams),

scatterplots

visual representations of the scores belong-ing to each subject in the study.

scatterplots

streghth and direction

regression lines

The lines drawn on the scatterplots are called

regression lines

The direction of the line corresponds to the direction of the relationship

positive correlation

also called direct relationship

direct relationship

value of r tells us how strong the relationship is

direct relationship

high score or another

negative correlation

also called inverse relationship

inverse relationship

low score on the second and vice versa

inverse relationship

The sign merely tells us whether the relationship is direct or inverse; the absolute value tells us how strong it is.

third possibility

is no relationship between vocabulary and TV viewing time (r is near zero).

outliers

(extreme scores)

outliers

A number of subjects do not fit this pattern at all.

outliers

dramatically reduce the size of the correlation coefficient because it disturbs the general linear trend of the data.

Correlation

does not imply causation.

Correlation

even though a relationship exists between two measures, we cannot say that one causes the other, even when such a statement appears reasonable

coefficient of determination

estimates the amount of variability in scores on one variable that can be explained by the other variable an estimate of the strength of the relationship between them.

coefficient of determination

values range from 0.00-1.00 or 0 to 100%

Linear Regression Analysis

When two behaviors are strongly related, the researcher can estimate a score on one of the measured behaviors from a score on the other.

Linear Regression Analysis

predictive analysis

Linear Regression Analysis

method of estimate a score on one measured behavior

regression equation

To predict someone's score on one variable

regression equation

predictor for variables

regression equation

in what way do

regression equation

we would need to know the value of r and be able to calculate subjects' average scores (called means)

Factor analysis

allows us to see the degree of relationship among many traits or behaviors at the same time.

Multivariate analysis

examines the relationships among more than 2 variables

Multivariate analysis

two and more dependent variable, one independent variable

Multivariate analysis

multiple regression, partial correlation, or path analysis

multiple correlation

, represented by R, to test the relationship of several predictor variables (X1, X2, X3 ...) with a criterion variable (Y).

partial correlation

. This analysis allows the statistical influence of one mea-sured variable to be held constant while computing the correlation between the other two

multiple regression analysis

When more than two related behaviors are correlated

multiple regression analysis

can be used to predict the score on one behavior from scores on the others.

Quasi-experimental designs

almost experimental

Quasi-experimental designs

can seem like a real experiment, but they lack one or more of its essential elements, such as manipulation of antecedents or ran-dom assignment to treatment conditions.

natural experiment

Researchers who want to compare people exposed to a naturally occur-ring event with a comparison group

Ex Post Facto Studies

systematically examines the effects of subject characteristics but without actually manipulat-ing them.

Ex Post Facto Studies

means "after the fact."

Ex Post Facto Studies

capitalizes on changes in the antecedent conditions that occurred before the study.

Nonequivalent Groups Design

researcher compares the effects of different treatment conditions on preexisting groups of participants.

Nonequivalent Groups Design

most frequently used in social research

Longitudinal Design

behaviors of the same subjects at different points in time and look to see how things have changed.

Longitudinal Design

particularly important for psychologists studying human (and animal) growth and development.

Longitudinal Design

can take place over periods of months, years, or even decades.

Cross-Sectional Studies

different stages are compared at a single point in time using

Cross-Sectional Studies

And using different groups of subjects runs the risk that people in these groups might differ in other characteristics that could influence the behaviors you want to investigate.

Pretest/Posttest Design

people's level of behavior before and after the event and compare these levels

Pretest/Posttest Design

basic premise behind pre-test and post test