Terms in this set (91)
A set of mathematical procedures.
The entire set of the individuals of interest for a particular research question.
A set of individuals selected from a population usually intended to represent the population in a study.
A characteristic or condition that changes or has different values for different individuals.
Measurements or observations.
A collection of measurements or observations.
A single measurement or observation; is usually called a score or a raw score.
A value, usually numerical, that describes a population.
Statistical procedures used to summarize, organize, and simplify data.
Consists of techniques that allow us to study samples and then make generalizations about the population from which they were selected.
The naturally occurring discrepancy, or error, that exists between a sample statistic and the corresponding population parameter. [a.k.a. Margin of Error]
2 different variables are observed to determine whether there is a relationship between them.
One variable is manipulated while another variable is observed and measured.
These are characteristics such as age, gender, and intelligence that vary from one individual to another.
Characteristics of the environment such as lighting, time of day, weather conditions, etc.
The variable that is manipulated by the researcher.
The variable that is observed to assess the effect of the treatment.
Do not receive the experimental treatment. Provides a baseline.
Do receive the experimental treatment.
In a nonexperimental study, the IV that is used to create the different groups of scores is called...
Internal attributes or characteristics that cannot be directly observed but are useful for describing and explaining behavior.
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.
Consists of separate, indivisible categories. No values can exist between 2 neighboring categories.
There are an infinite number of possible values that fall between any 2 observed values.
The boundaries of intervals for scores that are represented on a continuous number line.
Consists of a set of categories that have different names. Measurements label and categorize observations, but do not make any quantitative distinctions between observations.
Consists of a set of categories that are organized in an ordered sequence. Measurements rank observations in terms of size or magnitude.
Consists of ordered categories that are all intervals of exactly the same size.
An interval scale with the additional feature of an absolute zero point.
Science based on observation.
Definition of what is to be observed. MUST be give/provided.
Formal statement of what you believe to be true among 2+ variables.
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.
Variable 1 ⇾ Variable 2
- Variation in V2 is caused by V1.
- Confounding variables exist.
An organized tabulation of the number of individuals located in each categories.
Measures the fraction of the total group that is associated with each score.
[ Proportion = P = f/N ]
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.
Class intervals of a grouped frequency distributing table - it appears that they form the upper and lower boundaries for the class interval.
It is possible to draw a vertical line through the middle so that one side of the distribution is a mirror image.
The scores tend to pile up toward one end of the scale and taper off gradually at the other end.
Where the scores taper off.
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.
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.
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.
The distance covered by the scores in a distribution, from the smallest score to the largest score.
Distance from the mean.
[ X - μ ]
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 ]
If the average value of the statistic is equal to the population parameter.
If the average value of the statistic either underestimates or overestimates the corresponding population parameter.
Indicates that the sample variance represents unexplained and uncontrolled differences between scores.
Pertaining to theory.
Based on direct observations and measurements of reality.
Based on probabilities.
Pertaining to a cause-effect relationship, hypothesis, or relationship.
A cause-effect relationship.
A study that documents what is going on or what exists.
A study that investigates the connection between two variables.
A study that investigates a causal relationship between two variables.
Takes place at a single point in time.
A study that takes place over time.
Many waves of measurement over time.
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.
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.
A relationship between variables in which high values for one variable are associated with low values on another variable.
A specific statement of prediction that usually states what you expect will happen in your study.
Describes the possible outcomes other than the alternative hypothesis.
Prediction that specifies a direction.
Prediction that does not specify a direction.
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.
Numerical representation of some object.
A specific value of a variable.
The property of a variable that occurs when you include all possible answerable responses.
Property of a variable that ensures that the respondent is not able to assign two attributes simultaneously.
The best available approximation of the truth of a given proposition, inference, or conclusion.
The abstract idea or theory of what the cause is in a cause-effect relationship you are investigating.
The degree to which conclusions you reach about relationships in your data are reasonable.
The approximate truth about inferences regarding cause-effect or causal relationship.
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.
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.
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.
A threat to internal validity that occurs in a study that uses only a single program or treatment group and no comparison or control.
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.