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Midterm

# Exam 1 Notes.docx

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Michigan State University

Sociology

SOC 282

Dr.Mullan

Spring

Description

1/8/14
Chapter 1: the What and the Why of Statistics
• The research process
• Asking a research question
• The role of theory
• Formulating the hypotheses
o Independent and dependent variables: causality
o Independent and dependent variables: guidelines
• Collecting data
o Levels of measurement
o Discrete and continuous variable
• Analyzing data and evaluating hypotheses
o Descriptive and inferential statistics
• Looking at social differences
The Research Process
• Theory ←→ asking the research question (examine a social relationship, study the
relevant literature) → formulating the hypotheses (develop a research design) →
collecting data → analyzing data → evaluating the hypotheses
Asking the research question (examine a social Formulating the hypotheses
→ relationship, study the
relevant literature)
(contribute new evidence in Theory (develop a research design)
literature and begin again)
Evaluating the hypotheses ← Analyzing data ←Collecting data 1/13/14
Asking a research question
• What is empirical research?
o Research based on information that can be verified by using our direct
experience
o To answer research questions we cannot rely on reasoning, speculation, moral
judgment, or subjective preference
o Empirical:
“Are women paid less than men for the same types of work?”
• The role of theory
o A theory is an explanation of the relationship between two or more observable
attributes of individuals or groups
o Social scientists use theory to attempt to establish a link between what we
observe (the data) and our understanding of why certain phenomena are related
to each other is a particular way.
• Formulating the hypothesis
o Hypotheses:
Tentative answers to research questions (subject to empirical verification)
A statement of a relationship between characteristics that vary (variables)
o Variable:
A property of people or objects that takes on two or more values
Must include categories that are both exhaustive and mutually exclusive
Examples: social class, age, gender, income
• Units of analysis
o The level of social life on which social scientists focus (individuals, groups, family,
organizations, cities) • Types of variables
o Dependent: the variable to be explained (the effect)
o Independent: the variable expected to account for (the cause of) the dependent
variable
• Cause and effect relationships
o Cause and effect relationships between variables are not easy to infer in the
social sciences. Causal relationships must meet three criteria:
The cause has to precede the effect in time
There has to be an empirical relationship between the cause and effect
This relationship cannot be explained by other factors 1/14/14
Chapter 2 Frequency Distributions
Outline
• Frequency distributions
• Proportions and percentages
• Percentage distributions
• Comparisons
• The construction of frequency distributions
o Frequency distributions for nominal variables
o Frequency distributions for ordinal cariables
o Frequency distributions for interval-ration variables
• Cumulative distributions
• Rates
• Reading the research literature
o Basic principles
o Tables with a different format
• Frequency distributions
o A table reporting the number of observations falling into each category of the
variable
Example: death penalty statutes
• Proportions and percentages
o Proportion (P): a relative frequency obtained by dividing the frequency in each
category by the total number of cases o Percentage (%): a relative frequency obtained by dividing the frequency in each
category by the total number of cases and multiplying by 100.
o Proportions and percentages are relative frequencies
• Percentage distribution
• If you percentage in one direction, read the table in the other direction (percentage
down, read across the table) 1/15/14
Cumulative Distributions
• Sometimes we are interested n locating the relative position of a given score in a
distribution
• Cumulative frequency distribution: a distribution showing the frequency at or below
each category (class interval or score) of the variable
• Cumulative percentage distribution: a distribution showing the percentage at or below
each category (class interval or score) of the variable
• Rates: a number obtained by dividing the number of actual occurrences in a given time
period by the number of possible occurrences
• Reading statistical tables: be skeptical and critical
o Basic principles for understanding what the researched is trying to tell you:
What is the source of the table?
How many variables are presented? What are their names?
What is represented by the numbers presented in the first column? In the
second column?
Chapter 3: Graphic Presentation
• Outline
o The pie chart
o The bar graph
o The statistical map
o The histogram
o Statistics in practice
o The line graph
o Times series charts o Distortions in graphs
It is important to choose the appropriate graphs to make statistical
information coherent
• Pie chart: a graph showing the differences in frequencies or percentages among
categories of a nominal or an ordinal variable. The categories are displayed as
segments of a circle whole pieces add up to 100
• Bar graph: a graph showing the differences
• The statistical map: we can di

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