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Midterm

test one notes


Department
Sociology
Course Code
SOC202H1
Professor
Brent Berry
Study Guide
Midterm

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SOC 202 TEST 1
CHAPTER ONE
Stats is about obtaining an accurate sense of proportion in regard to reality
Statistical imagination : an appreciation of how usual or unusual an event , circumstance, or
behaviour is in relation to a larger set of familiar events, and an appreciation of an events
cause and consequences
Sociological imagination : an awareness of the relationship of the individual to the wider
society and history
Any statistic is culturally bound or normative (its interpretation depends on the place time
and culture in which it is observed)statistical norms are measurement of social norms/
statistical ideals often reflect social values (it is a socially desired rate of occurrence of a
phenomenon)
The statistical imagination, with its awareness of the linkages between statistical
measurement and social facts, requires a degree of scepticism.
Purpose of statistical analysis Descriptive statistics: used to tell us how many observation
were recorded and how frequently each score or category occurred/ inferential statistics: used
to show cause and effect relationship and to test hypotheses and theories
A good scientific theory accomplishes two thing it provides a sense of understanding
about a phenomenon/ it allows us to make empirical predictions to answer the question of
under what condition and to what degree a phenomenon will occur
Science has limitation, restricted to examining empirical phenomena/ many sound factually
based scientific arguments lack political or taxpayer support/ ethical dilemmas often arise
creating resistance to its application
Variable: measurable phenomena that vary or change over time, or that differ form place or
from individual to individual (features of the object or subject under study) variation: refers
to how much the measurement of a variable differ among study subjects. Constant:
characteristics of study subjects that don't vary.
The research process: involves organizing ideas into a theory, making empirical predictions
that support the theory, and then gathering data to test these predictions/ this is a cumulative
process (a continual process of accumulation of knowledge)
oSpecify the research question ( raise a question/identify the dependent variable)
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oReview the scientific literature (not waste time and money collecting data that already
exist)
oPropose a theory and state hypotheses (organizing ideas that can explain variation of
the dependant variable/ identify independent variable and state hypothesis)
oSelect a research design ( how data is to be measured, sampled and gathered)
oCollect the data (going into the field, and getting the information)
oAnalyze the data and draw conclusions (involves statistical analysis/ hypothesis is
tested)
oDisseminate the results (share the findings with the public and the scientific
community)
Proportional thinking: placing an observation into a larger context/ weighing the part against
the whole and calculating the like hood of the phenomenon to occur over the long run.
A rate: is the frequency of occurrence of a phenomenon per a specified, useful “base”
number of subjects in a population
CHAPTER TWO
Statistical errors are imprecision in the procedures used to gather and process information.
Two main source of statistical error: 1)sampling error- we do not observe every subject in the
population/ 2)measurement error- imprecise measures, difficulties in classification of
observations and the need to round numbers
A Population : A large group of people of particular interest that we desire to study and
understand. Sample: a small subgroup of the population/ its used to draw conclusion about
the population/ with samples we compute statistic rather than parameters
Statistic: a summary calculation of measurement made on a sample to estimate a parameter of
the population
A Parameter: A summary calculation of measurements made on all subjects in a population
(usually not calculated and, therefore, unknown)
1) Sampling error comes from sample size (the number of cases or observation in a
sample/ the larger the sample the smaller the range of error/ probability theory allows us to
say exactly how often a sample statistic will correctly predict a parameter) and
representativeness of the sample (the extent to which all segments of a population actually
land in a sample
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Simple random sample: one in which every person has the same chance of being selected for
the sample
2)measurement errors inaccuracy in research that derives from imprecise measurement
instrument, difficulties in the classification of observations and the need to round numbers.
To limit the measurement error we use operational definitions. We use levels of
measurement for a variable (this identifies its measurement properties, which determine the
kind of mathematical operations that can be appropriately used with it and the statistical
formulas that can be used with it in testing theoretical hypotheses)
Four level of measurements:
oNominal : indicate a difference in category, class, quality or kind/ name categories/ do
not allow for numerical scores/ there is no sense of degree/ many have two categories-
called dichotomous variable
oOrdinal : name categories but have the additional categories to be ranked from highest
to lowest, best or worst, or first to last
oInterval: have the characteristic of nominal and ordinal variable plus a defined
numerical unit or interval of measure/ identify differences in amount, quantity, degree
or distance/ we think in terms of distance between scores on a straight line/ the
interval or distance between scores are the same between any two points on the
measurement scale
oRatio: have the characteristics of interval variable plus a true zero point, where a score
of zero means none/ we can compute ratio- the amount of one observation in relation
to another
level of measurement applies to the entire variable and provides information on the strengths
and weaknesses of a variables measurement/ the unit of measurement is a term used only
with interval/ratio variables- it fixes the set interval for the numerical values used as scores
for an interval/ratio variable
increasing the level of measurements indexing: researcher soften create an index or a
survey scale to transform nominal/ordinal data into an interval/ratio variable
coding: a concise description of the symbols that signify each score of each variable/ basic
principles of coding Inclusiveness: states that for a given variable there must be a score or
code for every observation made (include a response category for every possible answer).
Exclusiveness: every observation can be assigned one and only one score for a given variable.
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