POL 280 Review Quiz

Quantitative Research

research that collects & reports data primarily in numerical form

Qualitative Research

research that relies on what's seen in field or naturalistic settings more than on statistical data

Scientific Research

series of experiments on one topic

Data

facts & statistics collected together for reference/analysis

Correlation/Covariation

extent to which 2 variables are related

Causation

cause & effect relationship in which 1 variable controls the changes in another variable

Hypothesis

testable prediction, often implied by a theory

independent Variable (IV)

• experimental factor that is manipulated

• variable whose effect is being studied

Dependent Variable (DV)

• outcome factor

• variable that may change in response to manipulations of the IV

Empirical Research

research that operates from the ideological position that questions about human behavior can be answered only through controlled, systematic observations in the real world

Normative Research

descriptive research approach designed to determine standard values for specific variables within a population

Variable

factor that can change in an experiment

Positive Relationship

association between 2 variables in which they increase or decrease together

Negative Relationship

relationship between variables characterized by an increase in 1 variable that occurs with a decrease in the other variable

Cross-Sectional Study

study in which a representative cross section of the population is tested or surveyed at one specific time

Time-Series Study

longitudinal research in which a researcher gathers the same type of information across two or more time periods

Confounding Variable

factor other than the IV that might produce an effect in an experiment

Probabilistic Relationship

increases in X are associated with increases (or decreases) in the probability of Y occurring, but those probabilities are not certainties

Spurious

not genuine, not true, not valid

Null Hypothesis

hypothesis that there is no significant difference between specified populations; any observed difference being due to sampling or experimental error

Alternative Research Hypothesis

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

Non-Directional Hypothesis

predicts the existence of a relationship, not its direction

Directional Hypothesis

hypothesis that makes specific prediction about the direction of the relationship between 2 variables

Selection Bias

unintended differences between the participants in different groups

Control Group

group in an experiment that isn't exposed to the treatment

Experimental Group

group in an experiment that's exposed to the treatment

Field Experiment

experiment conducted in the participants' natural environment

External Validity

extent to which we can generalize findings to real-world settings

Internal Validity

extent to which we can draw cause-and-effect inferences from a study

Observational Studies

studies in which the researcher observes and statistically analyzes certain phenomena in order to assist in establishing new principles/discoveries

Random Assignment

assigning participants to experimental and control conditions by chance, thus minimizing preexisting differences between those assigned to the different groups

Random Sampling

sample that fairly represents a population because each member has an equal chance of inclusion

Research Design

specifies which research questions must be answered, how and when the data will be gathered, and how the data will be analyzed

Replication

repeating the essence of a research study, usually with different participants in different situations, to see whether the basic finding extends to other participants and circumstances

Replicability

degree to which a study can be repeated with similar results

Sample of Convenience

collection of individuals that are easily available to the researcher

Survey Experiment

survey research technique in which the interviewing process includes experimental randomization in the survey stimulus

Categorical Variable

variable that names categories (whether with words or numerals)

Central Tendency

mean, median, mode

Continuous Variable

quantitative variable that has an infinite number of possible values that are not countable

Dispersion

range, standard deviation, variance

Histogram

graph of vertical bars representing the frequency distribution of a set of data

Mean

numerical average of the data

Measurement Metric

type of values that the variable takes on

Median

value of the case that sits at the exact center of our cases when we rank the values of a single variable from the smallest to the largest observed values

Mode

most frequently occurring score(s) in a distribution

Interval Variable

• variable used for observations that have numbers as their values

• the distance between pairs of consecutive numbers is assumed to be equal

Nominal Variable

variable used for observations that have categories, or names, as their values

Ordinal Variable

qualitative variable that incorporates an ordered position, or ranking

Outlier

value much greater or much less than the others in a data set

Skewness

extent to which cases are clustered more at one or the other end of the distribution of a quantitative variable rather than in a symmetric pattern around its center

Standard Deviation

computed measure of how much scores vary around the mean score

Variance

standard deviation squared

68-95-99.7 rule

in a normal model, about 68% of values fall within 1 standard deviation of the mean, about 95% fall within 2 standard deviations of the mean, and about 99.7% fall within 3 standard deviations of the mean

Central Limit Theorem

as sample size increases, the distribution of sample means of size n, randomly selected, approaches a normal distribution

Confidence Interval

range of values within which a population parameter is estimated to lie

Frequency Distribution

arrangement of data that indicates how often a particular score or observation occurs

Normal Distribution

bell-shaped curve, describing the spread of a characteristic throughout a population

Population

group that researchers want to make statistical inferences about

Sample

• subset of the population

• unit that is measured in experiments

Sampling Distribution

distribution of values taken by the statistic in all possible samples of the same size from the same population

Standard Error of the Mean

standard deviation of a sampling distribution

Statistical Inference

process of using data obtained from a sample to make estimates or test hypotheses about the characteristics of a population

Chi Squared

• used to determine if there are significant differences in the distribution of two data sets

• used to determine if two populations are homogeneous when compared to each other.

Correlation Coefficient

statistical index of the relationship between two things (from -1 to +1)

Critical Value

value that the test statistic must exceed in order to reject the null hypothesis

Pearson's R

statistic that measures the direction and strength of the linear relation between two variables that have been measured on an interval or ratio scale

P-Value

probability level which forms basis for deciding if results are statistically significant

Statistical Significance

statistical statement of how likely it is that an obtained result occurred by chance

Statistically Significant Relationship

a conclusion, based on the observed data, that the relationship between two variables is not due to random chance, and therefore exists in the broader population

Type 1 Error

rejecting a true null hypothesis

Type 2 Error

failing to reject a false null hypothesis

Alpha Level

probability level used by researchers to indicate the cutoff probability level (highest value) that allows them to reject the null hypothesis

Critical Region

area in the tails of the comparison distribution in which the null hypothesis can be rejected

Bivariate Regression

means only two variables are being analyzed, and researchers sometimes refer to this case as "simple regression".

Multivariate Regression

uses the values of several variables to explain variability in another variable

Unstandardized B Coefficient

• slope of the regression

• for every 1 increase in IV. the DV increases by B

A (constant)

• y-intercept of the regression

• when the IV is 0, the DV is A

R Squared Statistic

amount of variation in Y explained by X

Adjusted R Squared Statistic

amount of variation in Y explained by X, adjusted for the number of independent variables used to make the estimate

Dummy Variable

variable for which all cases falling into a specific category assume the value of 1, and all cases not falling into that category assume a value of 0.

Ordinary Least Squares (OLS)

• method for estimating the parameters of a multiple linear regression model

• estimates are obtained by minimizing the sum of squared residuals

Residual

observed - expected

Reverse Causality

situation in which the researcher believes that A results in a change in B, but B, in fact, is causing A

Correlation =/=

causation

Omitted Variable Bias

bias that arises in the OLS estimators when a relevant variable is omitted from the regression

Perfect Multicollinearity

when there is an exact linear relationship between any two or more of a regression model's IVs

Extrapolation

• the act of estimation by projecting known information

• invalid because it is outside the scope of the data

Data Mining

process of analyzing data to extract information not offered by the raw data alone