Statistics Terms: Unit 1

Front 1

random sampling

Back 1

process of selecting a sample such that the selection of one observation is independent of the selection of any other observation

Front 2

parameters

Back 2

characteristics of populations

Front 3

inferential statistics

Back 3

statistical procedures used to make decisions about a population based from a sample

Front 4

sampling distribution

Back 4

hypothetical distribution of the values of a statistic if it were computed repeatedly with similar samples

Front 5

absolute research

Back 5

research with the purpose of measuring some phenomenon

Front 6

comparative research

Back 6

research that compares the results from two or more groups

Front 7

scientific method
(steps according to stats)

Back 7

1. encounter and identify the problem
2. formulate the hypotheses and define variables
3. think through the consequences of the hypotheses
4. design and run the study, collect data, compute stats, test hypotheses
5. draw conclusions

Front 8

continuous variable

Back 8

can take on an INFINITE number of values between 2 lengths

Front 9

discreet variable

Back 9

finite number of values between two sites

Front 10

independent variable

Back 10

values manipulated by the researcher

Front 11

dependent variable

Back 11

values measured by the researcher

Front 12

extraneous variable

Back 12

not manipulated or measured but they are affecting what you're measuring

Front 13

Three ways to control the extraneous variables (EV)

Back 13

1. hold the participants constant on the EV
2. include EV in your design
3. randomize participants to groups

Front 14

subject bias

Back 14

subjects change their behavior based on what group they're in

Front 15

observer bias

Back 15

researcher changes how they treat participants based on what group they're in

Front 16

single-blind experiment

Back 16

subjects do not know what group they're in

Front 17

double-blind experiment

Back 17

both the researcher and the subjects do not know which group they're in

Front 18

causal relationship

Back 18

studied when there is manipulated variables and controlled EV

*manipulation of the IV is key!
IV -> DV

Front 19

predictive relationship

Back 19

a relationship that exists when a researcher can assert only that a change in one variable predicts a change in another variable

PV -> CV

Front 20

predictor variable

Back 20

variable in a predictive relationship that is analogous to the independent variable; the researcher predicts from this variable

Front 21

criterion variable

Back 21

variable in a predictive relationship that is analogous to the dependent variable; the researcher predicts to this variable

Front 22

true experiment

Back 22

research that uses an IV and a DV and controls EV by randomization; causal relationships can be asserted when a true experiment is conducted

Front 23

observational research

Back 23

research that can assert only predictive relationships because of the absence of manipulation and randomization

Front 24

Quasi experimental designs

Back 24

designs in which the researcher can manipulate the IV but cannot randomly assign participants to groups

Front 25

Property of measurement:
Identity

Back 25

your data is named and has meaning

Front 26

Property of measurement:
Order

Back 26

a meaningful order in the values

ex. 1st place and 2nd place

Front 27

Property of measurement:
Distance

Back 27

a positive, consistent difference between values

Front 28

Property of measurement:
true zero

Back 28

it lacks that variable
ex. temperature does not have this... children - do have this

Front 29

internal validity

external validity

Back 29

In a QED:
how valid are your results

generalizability of your results to other groups

Front 30

Scales of Measurement

Back 30

1. Nominal
2. Ordinal
3. Interval
4. Ratio

Front 31

nominal

Back 31

has the characteristic of identity

Front 32

ordinal

Back 32

has identity and order

Front 33

interval

Back 33

has identity, order, and distance

Front 34

ratio

Back 34

has identity, order, distance, and a true-zero

Front 35

Characteristics of a bar graph

Back 35

use with qualitative data
bars DON'T touch
categories on X-axis
frequency on Y-axis

Front 36

Characteristics of a histogram

Back 36

use with QUANTITATIVE data
bars do touch
intervals on X-axis
frequency on Y-axis

Front 37

kurtosis

Back 37

deals with the peak of the distribution: mesokurtic
patykurtic
leptokurtic

Front 38

characteristics of median

Back 38

depends on frequency of scores and not their actual value
recommended for skewed data
not affected by outliers

Front 39

characteristics of the mean

Back 39

balance point in the distribution
sum of the deviations = 0
sum of the squared deviations is a minimum
the sample mean gives you the smallest amount of deviation

Front 40

sample standard deviation

Back 40

in original units
as variability increases, st.dev. increases
= 0 if no variance
indicates relative standing

Front 41

sample variance

Back 41

a positive number
= 0 if no variability
as variability inc., st.dev. inc
in squared units

Front 42

Least Squares Criterion

Back 42

E(x - mean)^2 is a minimum

Front 43

Z-score

Back 43

something minus its mean divided by the st. dev.

expressed in terms of st. dev. units
variance of the z scores is 1
st. dev. of z-scores is 1
Z is undefined
the shape of the z-score distribution = x distribution