Search
Create
Log in
Sign up
Log in
Sign up
Exam 1
STUDY
Flashcards
Learn
Write
Spell
Test
PLAY
Match
Gravity
Terms in this set (91)
Statistics
A set of mathematical procedures.
Population
The entire set of the individuals of interest for a particular research question.
Sample
A set of individuals selected from a population usually intended to represent the population in a study.
Variable
A characteristic or condition that changes or has different values for different individuals.
Data
Measurements or observations.
Data Set
A collection of measurements or observations.
Datum
A single measurement or observation; is usually called a score or a raw score.
Parameter
A value, usually numerical, that describes a population.
Descriptive Statistics
Statistical procedures used to summarize, organize, and simplify data.
Inferential Statistics
Consists of techniques that allow us to study samples and then make generalizations about the population from which they were selected.
Sampling Error
The naturally occurring discrepancy, or error, that exists between a sample statistic and the corresponding population parameter. [a.k.a. Margin of Error]
Correlational Method
2 different variables are observed to determine whether there is a relationship between them.
Experimental Method
One variable is manipulated while another variable is observed and measured.
Participant Variables
These are characteristics such as age, gender, and intelligence that vary from one individual to another.
Environmental Variables
Characteristics of the environment such as lighting, time of day, weather conditions, etc.
Independent Variable
The variable that is manipulated by the researcher.
Dependent Variable
The variable that is observed to assess the effect of the treatment.
Control Condition
Do not receive the experimental treatment. Provides a baseline.
Experimental Condition
Do receive the experimental treatment.
Quasi-Independent Variable
In a nonexperimental study, the IV that is used to create the different groups of scores is called...
Hypothetical Constructs
Internal attributes or characteristics that cannot be directly observed but are useful for describing and explaining behavior.
Operational Definition
Identifies a measurement procedure (a set of operations) for measuring an external behavior and used the resulting measurements as a measurement of an internal construct.
Discrete Variable
Consists of separate, indivisible categories. No values can exist between 2 neighboring categories.
Continuous Variable
There are an infinite number of possible values that fall between any 2 observed values.
Real Limits
The boundaries of intervals for scores that are represented on a continuous number line.
Nominal Scale
Consists of a set of categories that have different names. Measurements label and categorize observations, but do not make any quantitative distinctions between observations.
Ordinal Scale
Consists of a set of categories that are organized in an ordered sequence. Measurements rank observations in terms of size or magnitude.
Interval Scale
Consists of ordered categories that are all intervals of exactly the same size.
Ratio Scale
An interval scale with the additional feature of an absolute zero point.
Empirical Science
Science based on observation.
Construct
Definition of what is to be observed. MUST be give/provided.
Hypothesis
Formal statement of what you believe to be true among 2+ variables.
Simple Covariation
Variable 1 ⇿ Variable 2
- The two or more variables are RELATED but do not have a specific one-way cause and effect relationship.
- No confounding variables.
Ordered Covariation
Variable 1 ⇾ Variable 2
- Variation in V2 is caused by V1.
- Confounding variables exist.
Frequency Distributions
An organized tabulation of the number of individuals located in each categories.
Proportion
Measures the fraction of the total group that is associated with each score.
[ Proportion = P = f/N ]
Percentage
P = f/N(100)
Grouped Frequency Distribution Table
Grouping scores into intervals and then listing the intervals in the table instead of listing each individual score. These groups/intervals are called class intervals.
Apparent Limits
Class intervals of a grouped frequency distributing table - it appears that they form the upper and lower boundaries for the class interval.
Symmetrical Distribution
It is possible to draw a vertical line through the middle so that one side of the distribution is a mirror image.
Skewed Distribution
The scores tend to pile up toward one end of the scale and taper off gradually at the other end.
Tail
Where the scores taper off.
Central Tendency
A statistical measure that attempts to determine the single value, usually located in the center of a distribution, that is most typical or most representative of the entire set of scores.
Number Crunching
Take a distribution consisting of many scores and "crunch" them down to a single value that describes them all.
3 Measures of Central Tendency
Mean, mean, and mode.
Variability
Provides a quantitative measure of the differences between scores in a distribution and describes the degree to which the scores in a distribution and describes the degree to which the scores are spread out or clustered together.
Range
The distance covered by the scores in a distribution, from the smallest score to the largest score.
Deviation
Distance from the mean.
[ X - μ ]
Population Variance
Equals the mean squared deviation.
Sum of Squares
The sum of the squared deviation scores.
Degrees of Freedom
Determine the number of scores in the sample that are independent and free to vary.
[ n - 1 ]
Unbiased
If the average value of the statistic is equal to the population parameter.
Biased
If the average value of the statistic either underestimates or overestimates the corresponding population parameter.
Error Variance
Indicates that the sample variance represents unexplained and uncontrolled differences between scores.
Theoretical
Pertaining to theory.
Empirical
Based on direct observations and measurements of reality.
Probabilistic
Based on probabilities.
Causal
Pertaining to a cause-effect relationship, hypothesis, or relationship.
Causal Relationship
A cause-effect relationship.
Descriptive Studies
A study that documents what is going on or what exists.
Relational Studies
A study that investigates the connection between two variables.
Causal Studies
A study that investigates a causal relationship between two variables.
Cross-Sectional Study
Takes place at a single point in time.
Longitudinal
A study that takes place over time.
Time Series
Many waves of measurement over time.
Relationship
An association between two variables such that, in general, the level on one variable is related to the level on the other.
Third Variable/Missing Variable Problem
An unobserved variable that accounts for a correlation between two variables.
Positive Relationship
A relationship between variables in which high values for one variable are associated with high values on another variable, and low values are associated with low values on an another variable.
Negative Relationship
A relationship between variables in which high values for one variable are associated with low values on another variable.
Alternative Hypothesis
A specific statement of prediction that usually states what you expect will happen in your study.
Null Hypothesis
Describes the possible outcomes other than the alternative hypothesis.
One-Tailed Hypothesis
Prediction that specifies a direction.
Two-Tailed Hypothesis
Prediction that does not specify a direction.
Hypothetico-Deductive Model
A model in which two mutually exclusive hypotheses that together exhaust all possible outcomes are tested, such that if one hypothesis is accepted, the second must therefore be rejected.
Quantitative
Numerical representation of some object.
Attribute
A specific value of a variable.
Exhaustive
The property of a variable that occurs when you include all possible answerable responses.
Mutually Exclusive
Property of a variable that ensures that the respondent is not able to assign two attributes simultaneously.
Validity
The best available approximation of the truth of a given proposition, inference, or conclusion.
Cause Construct
The abstract idea or theory of what the cause is in a cause-effect relationship you are investigating.
Conclusion Validity
The degree to which conclusions you reach about relationships in your data are reasonable.
Internal Validity
The approximate truth about inferences regarding cause-effect or causal relationship.
Construct Validity
The degree to which inferences can legitimately be made from the operationalizations in your study to the theoretical constructs on which those operationalizations are based.
External Validity
The degree to which the conclusions of your study would hold for other persons in the other places and at other times.
Threats to Validity
Reasons your conclusion or inference might be wrong.
Threats to External Validity
Any factors that can lead you to make an incorrect generalization from the results of your study to other persons, places, times, or settings.
Replication
A study that is repeated in a different place, time, or setting.
Threats to Internal Validity
Any factors that can lead you to draw an incorrect conclusion that your treatment or program causes the outcome.
Single-Group Threats
A threat to internal validity that occurs in a study that uses only a single program or treatment group and no comparison or control.
Multiple-Group Threats
An internal validity threat that occurs in studies that use multiple groups, for instance, a program and a comparison group.
Social Threats to Internal Validity
Threats to interval validity that arise because social research is conducted in real-world human contexts where people will react to not only what affects them, but also what is happening to others around them.
;