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# Statistics Lecture 1

CJ3347-256 Spring 2013
by

## Dustin Melbardis

on 27 January 2015

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#### Transcript of Statistics Lecture 1

Practice
race
We use numbers everyday.
Why Study Statistics?
Numbers help us with arguments.
Stages of Social Research
1) We've got a problem
Levels of Measurement
Nominal
Data
Variables
The Functions of Statistics
Description
Numbers allow comparisons.
Numbers allow prediction.
Professional Literature
Behavioral Science Rationale
What are we trying to do when we conduct research?
Explain
Predict
Control
We want to arrive at conclusions about the existence and strength of relationships.
2) Reduce the problem to a testable hypothesis
Hypotheses
an idea about the nature of social reality that is testable through systematic research.
statement
Dogs shed more than cats.
Do dogs or cats shed more?
Research Question
3) Measure the key concepts
4) Data Collection
5) Observations are quantified for analysis
6) Results are interpreted and communicated
Data Collection
Anything we can observe and measure with attributes that change between cases
Variables
A characteristic that has an unchanging value
Constant
Independent Variable
Dependent Variable
our presumed "cause" - the variable that occurs first in our hypothesis
our presumed "effect" - the variable that changes based on how the independent variable changes
Latent
Manifest - readily observable
cannot be observed through traditional means
Data Collection
constructing primary data records for a given sample or population of observations
Population
Sample
the complete set of individuals of interest in a particular study
one set of individuals from the population, intended to represent the population
Population Parameters
a value that describes the population
Sample Statistics
a value that describes the sample
Sampling Error
the difference that exists between the statistic and the parameter
Ordinal
Interval
Ratio
Naming
Labeling
Cases sorted into categories
"mutually exclusive"
"exhaustive"
we seek
order
maybe we rank by degree
does not indicate magnitude
ex: colors, flavors, prisons, gender
ex: officer rank, race finishes, shirt sizes, class rank, fast food drink sizes
order, plus the exact distance between categories
order, plus the exact distance between categories
"all intervals are the same size"
"all intervals are the same size"
arbitrary zero
absolute zero
zero represents an absence of value
ex: ºF or ºC, rushing yards, dress size, IQ
ex: quantities, age, exam scores, weight
Inference
Prediction
we can just look at the numbers and identify patterns, we will use
frequency distributions, measures of central tendency and variability
make generalizations about the population based on the sample -
hypothesis testing
based on presence and strength of relationships
correlation and regression
height
classroom number
military rank
prior offenses
Do single-parent households produce more delinquency than two-parent households?
Full transcript