Chapter 1 Flashcards
(29 cards)
1
Q
statistics
A
- set of mathematical procedures for organizing, summarizing, and interpreting information.
- helps researchers make sense of information, communicate findings, and assure it is accurate.
2
Q
population
A
- all individuals of interest.
- vary in size; often large.
- ex: first year students.
3
Q
sample
A
- individuals selected from the population.
- intended to represent population.
- ex: 500 first year students at KSU.
4
Q
variable
A
- characteristic that has different values for different individuals.
- ex: hair color, weather.
5
Q
data
A
- measurements/observations.
- data set and datum (score and raw score).
6
Q
parameter
A
- value that describes a population.
7
Q
statistic
A
- value that describes a sample.
8
Q
descriptive statistics
A
- describe data; summarize, organize, and simplify.
- average score/range.
- shown with tables and graphs.
9
Q
inferential statistics
A
- uses samples to generalize about the population.
- uses experiments (observed outcome due to chance or an effect?)
10
Q
sampling error
A
- discrepancy between sample statistic and corresponding population parameter.
- samples are never identical to the population.
11
Q
discrete variable
A
- separate, indivisible categories.
- no values exist between two categories.
- ex: number of children, grade in class, ice cream flavors.
12
Q
continuous variable
A
- infinite number of possible values between two observed values.
- every interval is divisible into an infinite number of fractional parts.
- ex: weight, miles.
13
Q
measurement
A
- involves assigning individuals to events or categories.
14
Q
nominal scale
A
- categories with names.
- no quantitative differences.
- ex: care make/model.
15
Q
ordinal scale
A
- categories in an ordered sequence.
- ranked in terms of magnitude or size.
- no indication of the size of the differences.
- ex: french fry size (S/M/L)
16
Q
interval scale
A
- ordered values.
- intervals between categories are the same size.
- no meaningful zero point.
- ex: year, temperature.
17
Q
ratio scale
A
- interval scale with a meaningful or true zero value.
- ex: speed.
18
Q
descriptive research
A
- one or more variables measured per individual.
- statistics describe the observed variable.
19
Q
correlational method
A
- non experimental.
- one group of subjects; measure two variables per subject.
- goal is to describe type and magnitude of relationship.
- ex: time spent watching TV and GPA.
20
Q
limitations of correlational method
A
- can demonstrate the existence of a relationship but can’t explain the relationship.
- can’t demonstrate a cause and effect relationship between two variables (correlation doesn’t equal causation).
21
Q
experimental method
A
- goal is to demonstrate cause and effect.
- experimenter determines level of manipulation of one variable.
- there’s control; it rules out the influence of other variables.
- participant variables (ex: gender).
- environmental variables (ex: time of day).
22
Q
independent variable (IV)
A
- manipulated by the researcher.
- no other variables influence its value.
23
Q
dependent variable (DV)
A
- observed to assess the effect of treatment.
- thought to depend on the value of the IV.
24
Q
experimental condition
A
- receives experimental treatment.
25
control condition
- receives either no treatment or a natural placebo treatment.
- provides baseline comparison.
26
x and y
- individual scores for a particular variable.
27
N
- number of scores in a population.
28
n
- number of scores in a sample.
29
where does summation go in the order of operations?
p e m d S a s
