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39 Cards in this Set

  • Front
  • Back
Frequency Distribution
A record of the frequence of scores located in each response category of what's being measured
Interval Scale
Ordered equidistant categories having an infinite # of intermediate values and an arbitrary zero point
Correlation Method
Observing the naturally occuring relationship b/w two or more variables (as one variable changes, how does the other change?) ex: shoe size and height
Hypothetical concepts (abstract ideas)
Experimental Method
Cause and effect relationship; requires manipulation of at least one variable & measuring another variable
Specific testable prediction about the relationship b/w 2 or more variables.
Nominal Scale (Categorical)
Category with different names. No quantitative distinctions; numbers may serve as labels
Ordinal Scale (ordered)
Category names (or #'s) are represented in an ordered sequence of magnitude; numbers have very limited quantitative properties
ex: attractiveness, job performance
Ratio Scale
Interval scale with an absolute zero point (absence of construct) ex: Kelvin, time
Cumulative Frequency
Add the frequency at and below each score.

Scientific Method
1. Describe the question/problem.
2. Design study->collect data.
3. Analyze data, draw conclusions.
4. Revise theories.
Operational definition
Defining a construct by the manner in which the variable is used and measured.
ex: What does intelligence look like (IQ)
Key elements in any distribution
1. Set of possible scores
2. The frequency of scores at each category
characteristic that changes or is different from one individual to the next (something that is measured)
Grouping Guidelines
1. Have about 10 intervals
2. Interval widths must be equals
3. Use simple numbers for interval widths
4. The lower limit of the interval should be a multiple of the interval widths (ex: 2,4,5,10)
5. Highest &/or lowest interval should not have a zero frequency
Experimental Group
Receives the treatment level of the Ind. Var.
Apparent Limit
The actual limits of each interval (w/ gaps)
ex: 6.5-6.9
Real (Exact) Limit
Limits of the entire interval (closing the gaps)
-always represented with one more place past the decimal that the apparent limit
Confounding Variable
Uncontrolled variable that can systematically vary with the ind. var.
In the exact middle of the interval
Nonmanipulated Ind. Var.
Random Assignment
For each participant, equal chance for assignment to each condition (Holds extraneous variables constant)
A set of methods and rules for organizing summarizing and interpreting information.
Control Group
Does not receive the treatment level of the Ind. Var.;gets treatment or gets placebo treatment
Independant Variable
The variable that is manipulated (or controlled)
ex: different groups; positive vs. negative words
Dependent Variable
The variable that is observed/measured.
Inferential Statistic
Procedures used to generalize the characteristic of a sample of a population (Infer to the population)
Integrated set of principles that explain all the facts and predicts observed events.
Qualitative Difference
Change in kind/quality ex: eye color, different drugs
Continuous Variable
Variable with an infinite # of possible intermediate values b/w any two values, qualitative differences.
ex: time, distance, weight
Quantitative Difference
Change of amount
ex: different amounts of drugs
Discrete Variable
A)Represents seperate categories for each level of the variable with no intermediate values
B) Qualitative differences
ex:gender, # of students
Numerical value that describes a characteristic of a population.
Set of individual of interest in a particular study.
Random Sampling
Process of obtaining a sample that requires every individual in the population has equal chance of selection (representatives of whole population)
Numerical value that describes a characteristic of a sample
Set of individuals selected from a population who are intended to represent the population in research study.
Sampling Error
The numeric difference that usually exists b/w the sample statistic & population parameter ex) voting prediction, (aka: margin of error)
Descriptive Statistics
Procedures used to summarize, organize, and simplify data (describe)