POLS 7000X Statistics in political science Class 1 Brooklyn College – CUNY Shang E. Ha

POLS 7000XSTATISTICS IN POLITICAL SCIENCE

CLASS 1BROOKLYN COLLEGE – CUNYSHANG E. HA

Leon-Guerrero and Frankfort-Nachmias, Essentials of Statistics for a Diverse Society, Chapter 1

Leon-Guerrero/Frankfort-Nachmias: Essentials of Social Statistics for a Diverse Society© 2012 SAGE Publications

Empirical Research What is Empirical Research? Research based on information that can be verified by

using our direct experience.

A research… That poses a question That constructs hypotheses (i.e., potential answers) That creates, gathers, and analyzes data That tests hypotheses – correct or wrong? That cumulates knowledge

Not only in political science but also in any other social science disciplines


Asking a Research Question

To answer research questions we cannot rely on speculation, moral judgment, or subjective preference

Instead, we create a set of potential answers (i.e., hypotheses) and see whether data support our hypotheses by carefully analyzing them

Empirical (a “Why” question): Why do some people commit suicide (and others don’t)? Why are some individuals favorable to homosexuality (and

others are not)? Why do some people vote in the mayoral elections (and

others don’t)?

Not Empirical: Is racial equality good for society? Should death penalty be abolished?


Units of AnalysisThe level of social life on which social

scientists focus (individuals, groups). Examples:

Individual as unit of analysis: Why are some people politically liberal

while others are conservative? City as unit of analysis:

Why is crime rate higher in some cities than others?

Country as unit of analysis: What determines income inequality across

different countries?


Formulating the Hypotheses

Hypotheses: Tentative answers to research questions

(subject to empirical verification) A statement of a relationship between

characteristics that vary (variables)

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


Types of Variables Dependent

The variable to be explained (the “effect”). Should be identified in our research question

Why are some people favorable to homosexuality? Dependent variable – attitudes toward homosexuality

Independent The variable expected to account for (the “cause”

of) the dependent variable. Should be identified in our hypothesis

The more educated are more likely to harbor favorable attitudes toward homosexuality

Independent variable – level of education


The Role of Theory A theory is an explanation of the

relationship between two or more observable attributes of individuals or groups.

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 in a particular way.


Hypothesis: An Example Research Question: What determines white Americans’

attitudes toward immigrants from Latin American countries?

Hypothesis: White Americans who live in an area populated by a significant proportion of immigrants are more likely to harbor favorable attitudes toward them than those who live in another area where few immigrants reside

Theory: Contact Theory (contact makes friends)

Dependent variable: attitudes toward immigrants (favorable – hostile)

Independent variable: residential segregation (high: no immigrants – low: many immigrants)


Cause and Effect Relationships

Cause and effect relationships between variables are not easy to infer in the social sciences. Causal relationships must meet three criteria:

1. The cause has to precede the effect in time

2. There has to be an empirical relationship between the cause and effect

3. This relationship cannot be explained by other factors


Guidelines for Independent and Dependent Variables

1. The dependent variable is always the property you are trying to explain; it is always the object of the research.

2. The independent variable usually occurs earlier in time than the dependent variables.

3. The independent variable is often seen as influencing, directly or indirectly, the dependent variable.


One Hypothesis, Many Hypotheses Social phenomena are complex

Most of the social phenomena require researchers to assess the effects of several independent variables on one dependent variable

One independent variable usually explains only a certain amount of the change in the values observed in the dependent variable; hence, additional independent variables have to be introduced in order to explain more of that variation.


Hypothesis: People who attend church regularly are more likely to oppose abortion than people who do not attend church regularly.

• Identify the IV and DV

– Independent variable:– Dependent variable:

• Identify other independent variables

Gender

• Are the causal arguments sound?

– e.g. Does party id affect abortion views or vice versa?

Church attendance

Age

Attitudes toward abortion

Religious affiliation (Catholic, Jewish, Methodist, Islamic…)Political party identification

Example 1


Hypothesis: The number of books read to a child per day positively affects a child’s word recognition.

• Identify the IV and DV

• Identify other independent variables

• Are the causal arguments sound?

– independent variable:

– dependent variable:

Gender

– Most likely. It is hard to construct an argument where a 36 month old child affects the number of books her/his parent reads to her/him.

Number of books read

Older siblings

Word recognition

Health status Birth order

Example 2


Collecting Data

Asking the Research Question

Formulating the

Hypotheses

Evaluating the

Hypotheses

Analyzing Data

Develop a research design

Contribute new evidence to literature and begin again

THEORY

Examine a social relationship, study the relevant literature

Collecting Data


Collecting DataResearchers must decide three things:

How to measure the variables of interest

How to select the cases for the research

What kind of data collection techniques to use


Levels of MeasurementNot every statistical operation can be used with every variable. The type of statistical operations we employ will depend on how our variables are measured.

Variables are measured in three ways:

NominalOrdinalInterval-Ratio


Nominal Level of Measurement

Numbers or other symbols are assigned to a set of categories for the purpose of naming, labeling, or classifying the observations.

Examples:Political Party (Democrat, Republican,

Independent)Religion (Catholic, Jewish, Muslim,

Protestant)Race (African American, Latino, Native

American)


Ordinal Level of Measurement

Nominal variables that can be ranked from low to high.

Example: Social ClassUpper ClassMiddle ClassWorking Class


Interval-Ratio Level of Measurement

Variables where measurements for all cases are expressed in the same units. (Variables with a natural zero point, such as height and weight, are called ratio variables.)

Examples: AgeIncomeSAT scores


Cumulative Property of Levels of Measurement

Variables that can be measured at the interval-ratio level of measurement can also be measured at the ordinal and nominal levels.

However, variables that are measured at the nominal and ordinal levels can’t be measured at higher levels.Level Different or

Equivalent Higher or

Lower How Much

Higher

Nominal Yes No No Ordinal Yes Yes No Interval-ratio Yes Yes Yes


Discrete and Continuous Variables

Discrete variables: variables that have a minimum-sized unit of measurement, which cannot be sub-divided

Example: the number children per family

Continuous variables: variables that, in theory, can take on all possible numerical values in a given interval

Example: length


Analyzing Data: Descriptive and Inferential

Statistics• Population: The total set of

individuals, objects, groups, or events in which the researcher is interested.

• Sample: A relatively small subset selected from a population.

• Descriptive statistics: Procedures that help us organize and describe data collected from either a sample or a population.

• Inferential statistics: The logic and procedures concerned with making predictions or inferences about a population from observations and analyses of a sample.

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POLS 7000X Statistics in political science Class 1 Brooklyn College – CUNY Shang E. Ha