Research Methods Flashcards by CARLY PERALES

Type of research that contributes to a theory

Basic Research

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Type of research that helps answer the question of whether or not a theory helps solve real world problems

Applied Research

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Whether or not a study can be replicated to get the same results

Reliability

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Idea that a findings should be explained in the simplest way possible.

Parsimony

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When unknown influences on the results make the study inaccurate

Confounding

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The variable that an experimenter manipulates

Independent Variable

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The outcome of the experiment (type of variable)

Dependent Variable

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This variable is always some form of human response

Dependent Variable

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The group that does not receive the IV

Control Group

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The group that does receive the IV

Experimental Group

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Question you’re trying to find out in an experiment

What is the impact of IV on DV?

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Avoids sampling bias and keeps the researcher honest

Random Sampling

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Random Sampling AND ______ are necessary.

Random Assignment to Experimental and Control Groups

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When subjects cannot be randomly assigned or the experiments lacks in the control group this is called…

Quasi-Experimental Research

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All intact group studies are considered ______

Quasi-experimental

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When the people from subgroups are selected this is called

Stratified Sampling

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When people are selected from subgroups to mimic the ratios of the general population

Proportional stratified sampling

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When you use naturally existing groups and randomly select participants from the cluster

Cluster Sampling

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“nth” sampling or “k-ith” sampling when, for example, every 10 person is chosen for the study

Systematic Sampling

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The ______ of the sample is more important than the procedure used to pick the subjects

representativeness

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Judgment sample, convenience sampling, and quota sampling are all…

Non-probability Methods

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Sampling that is thought to be representative of the population by the researcher

Judgment Sampling

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An existing group is used with no random sampling

Convenience Sampling

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Pre-specified characteristics are used that mimic what is likely to be representative of the population in the future.

Quota Sample

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The hunch a researcher has

Experimental Hypothesis

The experimental hypothesis is written as

Capital H with a small 1 next to it. It could also be written with a tiny a.

the short version of additional hypotheses

H2, H3, etc.

When the researcher predicts no significant difference between the control or experimental groups, this is called

Null Hypothesis

Null Hypothesis can be written as

H with a tiny 0

The tense used to write a hypothesis in the modern form

Present Tense

Describes how likely it is that the difference between control and experimental groups occurred by chance

Level of Significance (AKA Confidence Level or Alpha Level)

Short form to describe that there's a 5% chance that difference between groups occurred by chance

p=.05

Type of error in which you reject null when it is true- REBT helped with alcoholism, but really it didn't

Type 1 Error

Type of error in which you accept null when it is false- REBT did not help alcoholics, but it did

Type 2 Error

Tells if the experiment measures what it is supposed to measure

Validity

Tells if the results can be generalized to other groups in the real world

External Validity

When people perform better because they know they are being observed

Hawthorne Effect

Tells if the study forms a valid cause/effect

Internal Validity

Instrumentation, measurement methods, observer judgment, maturation, statistical regression, selection of groups, attrition, and demoralization are all threats to

Internal Validity

When time impacts the results this is called

Maturation

When re-administering a test affects the results it is called

Statistical Regression

Two terms used to talk about whether or not test subjects stay in the study for the duration

Attrition or Experimental Mortality

To test the significance of a study, this tests the hypothesis between two normally distributed samples

T-Test (appropriate for 30 or more subjects)

Conducting a T-Test on two separate occasions

Dependent or Correlated T-Test

Needs to be used to analyze variants if there are more than two groups in an experiment

an ANOVA

A ratio of two variances (how far the data are scattered from the mean)

F Statistic F-Tests Named after Fisher

Needed if there is more than one Dependent Variable

Multi-Variant Analysis of Variants MANOVA

Needing to adjust groups so that a variable that might correlate with the DV will not throw off the study - for example if you find out one of the groups has read a book on REBT before the REBT study

ANCOVA - allows the researcher to statistically remove the effect of extraneous variables

Type of research that looks at whether a relationship between two variables exist, and if so, what is the magnitude and direction

Correlational Research

Correlation of choice is called

Pearson Product Moment Correlation

The range of correlations is

-1 through +1

When the correlation means that one goes up and the other goes down

Negative Correlation

When the correlation means both go either up or down

Positive Correlation

The mean, median, and mode all fall in the middle of this

Bell Curve or Gauzean Curve

Mean Median and Mode are all

Measures of Central Tendency

In a bell curve, when there are extreme values and the curve leans to one side or the other

Skewed Population

Bar Graphs are all called

Histograms

A measure of variability that shows the difference between highest and lowest values

Range

The measure of dispersion is called

Variance

Square root of the variants, useful in discussing spread of scores

Standard Deviation (SD)

This is not experimental and just describes a group (i.e. average, range, etc.)

Descriptive Statistics

Uses numbers to classify, but is qualitative, not quantitative

Nominal (Scale of Measurement)

Describes variables that can be rank ordered (high, medium, low)

Ordinal Scale

Scaled at equal distances, but no zero point (you can receive a zero on a test, but you don't have zero knowledge)

Interval Scale

Does have a true zero point and each number is measured from zero (weight/height)

Ratio Scale

The simplest approach to research

Survey

When using a questionnaire, 30-50% return rate is typical, but you can't make generalizations under

75% return

looks at overall dynamics of culture or situation rather than a single factor- holistic and inductive (case studies)

Ethnographic Research

generalize based on observations

inductive reasoning

when hypotheses derived from general principles

Deductive Reasoning

Rate an individual on one characteristic but really you’re influenced by another

Halo Effect

Experimenters expectations influence subjects

Rosenthal Effect

In testing or experimentation - refers to typical person who was tested

Norms

The letter N is used to represent

the number of subjects in a study

Untransformed scores

Raw scores

follow same people over a period of time (trend studies)

Longitudinal Research

just says there will be a difference but doesn’t say how

Non-directional Hypothesis

asserts how things will be different

Directional Hypothesis

The probability of committing a type 1 error equals

The significance level set for the experiment. If the significance level is .05, you are accepting a 5% chance that you are wrong when you reject the null hypothesis.

What is stanine score?

Standard 9- divides into 9 and 5 is the mean. There is also T-scale where 50 is the mean.