Test One - Chapters 1-6 Flashcards
Variability
The degree to which scores in a distribution are spread out
How much distance to expect between one score and another
Standard Deviation
The distance between each score and the mean
The average distance from the mean
Most commonly used measure of variability
Standard Deviation for Samples
Samples are consistently less variable than their population
Sample variability is a biased estimate of population variability
Consistently underestimates the population value
Descriptive Statistics
Organizes and summarizes info from a research study
Inferential Statistics
Determines what conclusions can be drawn from a research study
- use the sample data as the basis for answering questions about the population
> to accomplish this, typically built around the concept of probability
Statistics
A set of mathematical procedures for organizing, summarizing and interpreting info
Parameter
A value that describes a population
i.e. 65% are female
Statistic
A value that describes a sample
Sampling Error
Discrepancy between the sample and the population
Unpredictable, random differences that exist between samples
Operational Definition
A statement of procedures (operations) used to define research variables
Discrete Variable
Variable with separate, indivisible categories
Continuous Variable
Infinite number of value between two observed values
Deviation Score
x-u
u= mew
Sum of deviation scores should always be 0
Nominal Scale
classify individuals into categories that have different names
eg. gender, university, etc.
direction of difference = no
magnitude of difference = no
Ordinal Scale
set of categories organised in an ordered sequence
eg. t-shirt size, ranked place in a race, class, etc.
direction of difference = yes
magnitude of difference = no
Interval Scale
categories form a series of intervals all of the exact same size
eg. temperature or golf scores
- arbitrary zero point -> zero represents the presence of something