Research Methods Test 3

Ch. 7-12

Hypothesis Testing

The process of determining whether a hypothesis is

supported by the results of a research project.

Intuitive approach

Hypothesis testing method that looks at whether the data appears to support the hypothesis

Statistical approach

Hypothesis testing that focuses on mean differences, variability, and statistical significance

Null hypothesis

The hypothesis predicting that no difference exists between the groups being compared

Alternative hypothesis

The hypothesis that the researcher wants to support, predicting that a significant difference exists between the groups being compared

Two-tailed hypothesis

An alternative hypothesis in which the researcher predicts that the groups being compared differ, but does not predict the direction of the difference

One-tailed hypothesis

An alternative hypothesis in which the researcher predicts the direction of the expected difference between the groups

Type 1 error

An error in hypothesis testing in which the null hypothesis is rejected when it is true

Type 2 error

An error in hypothesis testing in which there is a failure to reject the null hypothesis when it is false

Single-group design

A research study in which there is only one group of participants

Inferential statistics

Procedures for drawing conclusions about a population based on data collected from a sample

Parametric tests

A statistical test that involves making assumptions about estimates of population characteristics, or parameters

Z-Test

A parametric statistical test that allows us to test the null hypothesis for a single sample when the population variance is known

Sampling distribution

A distribution of sample means based on random samples of a fixed size from a population

Standard error of the mean

The standard deviation of the sampling distribution

Central limit theorem

For any population with a mean m and standard deviation s, the distribution of sample means for sample size N will have a mean of m, a standard deviation of s/square root of N, and will approach a normal distribution as N approaches infinity

Critical value

The value of a test statistic that marks the edge of the region of rejection in a sampling distribution, where values equal to it or beyond it fall in the region of rejection

Region of rejection

The area of a sampling distribution that lies beyond the test statistic’s critical value; when a score falls within this region, Ho is rejected

Statistical power

The probability of correctly rejecting a false Ho

Confidence interval

An interval of a certain width that we fee confident will contain m

T test

A parametric inferential statistical test of the null hypothesis for a single sample where the population variance is not known

Degrees of freedom

The number of scores in a sample that are free to vary

Between-subjects design

An experiment in which different subjects are assigned to each group

Nonequivalent control group/biased assignment

There are systematic differences between the experimental and control groups that causes a confound

History effect

The DV could be confounded by current events outside of the study

Instrumentation effect

The DV could be confounded by the measuring device (weather it is a human or machine)

Mortality effect

The DV could be confounded by different dropout rates between groups

Diffusion of treatment effect

The DV could be confounded by information about the study being spread

Floor/ceiling effect

The DV is confounded by not having a sensitive enough measurement instrument to detect differences

Maturation effect

In a continuous study, the DV could be confounded by the subjects simply growing older across the study

Testing effect

In a continuous study, the DV could be confounded by practice or fatigue from doing the study repeatedly

Regression to the mean

In a continuous study, subjects that are selected for their extreme scores could be less extreme at later testing

Posttest-only control group design

An experimental design in which the dependent variable is measured after the manipulation of the independent variable

Pretest/posttest control group design

An experimental design in which the dependent variable is measured both before and after manipulation of the independent variable

Solomon four-group design

A design with four groups that is a combination of the post test only control group design and the pretest/posttest control group design

Experimenter effect

Experimenter consciously or unconsciously affects the outcomes of the study through the experimenter characteristics or expectancy effects

Internal validity

The extent to which the results of an experiment can be attributed to the manipulation of the independent variable rather than to some confounding variable

Participant effect

Participants consciously or unconsciously affect the outcomes of a study

Demand characteristics

What your study looks like it studies for, participants may try to help or hurt the study based on this

Single-blind experiment

Participants don’t know what condition they are in, but the researcher does

Double-blind experiment

Participants and researcher does not know what condition the participants are assigned to

Hawthorne effect

A type of reactivity in which subjects improve or change an aspect of their behavior because they know that they are being studied, rather than in response to the experimental manipulation

External validity

The extent to which the results of an experiment can be generalized

College Sophomore Problem

An external validity problem that results from using mainly college sophomores as subjects in research studies

Exact replication

Repeating a study using the same means of manipulating and measuring the variables as in the original study

Conceptual replication

A study based on another study that uses different methods, a different manipulation, or a different measure

Systematic replication

A study that varies from an original study in one systematic way

Independent-groups t test

A parametric inferential test for comparing sample means of two independent groups of scores

Standard error of the difference between means

The standard deviation of the sampling distribution of differences between the means of independent samples in a two-sample experiment

Effect size

The proportion of variance in the dependent variable that is accounted for by the manipulation of the independent variable

Cohen’s d

An inferential statistic for measuring affect size

Correlated-Groups Design

Participants in the experimental and control groups are related in the same way

Within-participants design

A kind of correlated-groups design where the subjects are the same in both conditions, is more powerful statistically

Order effects or carryover effects

A problem for within-subjects designs where the order of conditions the participants go through effect the results, could something from one condition to the other

Counterbalencing

A mechanism for controlling order effects by randomly determining the order of conditions

Latin Square

A system of partial counterbalancing without using all different orders by formally randomizing instead

Matched-subjects design

Different participants are used in each condition and they are put in conditions based on a variable that the researcher thinks in relevant

Correlated groups T test

Test used to compare the means of 2 related samples

Difference scores

Scores that show a difference between participants’ performance in one condition to their other condition

Standard error in difference scores

denominator of Independent t-test