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SOAN 3120
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Michelle Dumas
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Sociology and Anthropology

SOAN 3120

Michelle Dumas

Fall

Description

September 10, 2013 – Quantitative Methods – SOAN 3120*02
Week 1: Chapter 1 – Picturing Distributions
Research – Why conduct research?
- we want to know something
- explore a particular phenomenon
Methods -
Analysis – ask questions, figure out how to get answers, collect data, analyze if you
have quant. Data you use statistical means to analyze and interpretive means for
qualitative.
Theory – can help guide us on way we ask our questions, how, what we are looking
for and our lit. review sets up what has been asked before and research done before
From hypothesis, you collect data, you have observations, could be sending out a
survey, conducting interviews, etc.
From the data, you have empirical generalizations.
General concepts and terminology
- variable
o independent – the cause – causing something
o dependent - the effect, the results, the consequence
- definitions
o conceptual – descriptive in words
o operational – how you are going to measure that variable – eg. how
many groups of different classes are you going to include?
- statistics
o descriptive – giving description to what the numbers are telling us –
describing our data
o inferential - making generalizations for the population
Variables: Quantitative
- quantitative: numerical values
o can do arithmetic, add, subtract them – recorded in units of
measurement (seconds, kilograms, etc.)
- counts
o like the number of individuals registered in this class! They are a
whole number.
- Amounts
o Ratios
Eg. GDP per capita
Non-negative
Don’t need to be whole numbers, can be fractions or have
decimal places
Also called ratio variables
Meaningful to have a ratio which is essentially two values
divided by one value into the other value
- relative frequencies September 10, 2013 – Quantitative Methods – SOAN 3120*02
o proportions, percents and rates – they have a minimum and maximum
value – we look at, for example, the rate of crime – the number of
times something happens as a portion of a population set
o eg. infant mortality:
1000x number of children dying in first year divided by the
number of live births
- interval scales – arbitrary unit of measurement and have arbitrary zero point
– temperature – degrees Celsius – essentially we can compare differences in
temperature, how they differ from one place or season to another – 0 on a
Celsius scale does not represent no heat
Variables: Categorical
- qualitative or nominal variables
o categories that usually are mutually exclusive – only fit into one
category and make it fairly exhaustive that you have to fit into at least
one category – other, none of the above or decline to answer – region
ethnicity, race, gender – no intrinsic order to these categories on
surbey or way we use them – one is not better then the other – we just
happen to have different categories – marital status as well.
- ordinal variables
o categories that have a natural order
o rate our satisfaction on a particular service or product and they ask us
to rate our satisfaction levels – does have natural order in that some
things are different then the others – strongly agreed versus strongly
disagree or neutral – may be assigned a number but only for analysis
Question: Variables
If we asked people to report their weight, would that variable be considered a
categorical or quantitative variable? – QUANTITATIVE
We ask people whether their weight is underweight, normal, overweight or obese. IS
this variable categorical or quantitative? – CATEGORICAL
Aspects of Statistics
- data analysis: patterns
o describing data – use visual representation – graphs, charts –
sometimes that doesn’t make sense – can still have tables where you
have numerical representations of your data – look for patterns in
data – what does it look like – more females then males? – more
people who finished university than did not? – what is happening and
being able to describe that – most interesting looks at patterns
happening that you wouldn’t expect – the relationship between
variables

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