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43 Cards in this Set
 Front
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random sampling

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


parameters

characteristics of populations


inferential statistics

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


sampling distribution

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


absolute research

research with the purpose of measuring some phenomenon


comparative research

research that compares the results from two or more groups


scientific method
(steps according to stats) 
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 

continuous variable

can take on an INFINITE number of values between 2 lengths


discreet variable

finite number of values between two sites


independent variable

values manipulated by the researcher


dependent variable

values measured by the researcher


extraneous variable

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


Three ways to control the extraneous variables (EV)

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

subject bias

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


observer bias

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


singleblind experiment

subjects do not know what group they're in


doubleblind experiment

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


causal relationship

studied when there is manipulated variables and controlled EV
*manipulation of the IV is key! IV > DV 

predictive relationship

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

predictor variable

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


criterion variable

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


true experiment

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


observational research

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


Quasi experimental designs

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


Property of measurement:
Identity 
your data is named and has meaning


Property of measurement:
Order 
a meaningful order in the values
ex. 1st place and 2nd place 

Property of measurement:
Distance 
a positive, consistent difference between values


Property of measurement:
true zero 
it lacks that variable
ex. temperature does not have this... children  do have this 

internal validity
external validity 
In a QED:
how valid are your results generalizability of your results to other groups 

Scales of Measurement

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

nominal

has the characteristic of identity


ordinal

has identity and order


interval

has identity, order, and distance


ratio

has identity, order, distance, and a truezero


Characteristics of a bar graph

use with qualitative data
bars DON'T touch categories on Xaxis frequency on Yaxis 

Characteristics of a histogram

use with QUANTITATIVE data
bars do touch intervals on Xaxis frequency on Yaxis 

kurtosis

deals with the peak of the distribution: mesokurtic
patykurtic leptokurtic 

characteristics of median

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

characteristics of the mean

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 

sample standard deviation

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

sample variance

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

Least Squares Criterion

E(x  mean)^2 is a minimum


Zscore

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 zscores is 1 Z is undefined the shape of the zscore distribution = x distribution 