## Review

- Modeling – turning the research question into researchable form
- Selecting the attributes of interest
- Determining the causal paths
- Dependent vs independent variables
- Time order
- Logic/theory

- Moving towards a researchable hypothesis
- Specifying the unit of analysis
- Specifying the concepts
- More and less abstract concepts
- Conceptual and operational definitions
- Multi-dimensional concepts

- More and less abstract concepts

- Permitting the ability to show association
- If there is a causal relationship then people who differ on the independent variable will differ, on the average, on the dependent variable
- If a person’s score on the independent variable changes, then their score on the dependent variable will change
- Over time – panel studies
- Across cases – cross-sectional studies

- Why correlation does not equal causation
- Spurious relationships (Sometimes called confounds)

- Variables and Values
- Level of measurement
- Nominal – just categories with no order to them
- Ordinal – the values have order but do simply rank from low to high, they are not counting something
- Interval/ ratio – the values are counting real things
- Dichotomous – the variable only has two values

- Level of measurement
- The purpose of statistics
- Describing how cases vary on a single variable (descriptive statistics)
- Describing the nature of association/correlation/the relationship between two or more variables (descriptive statistics)
- Generalizing from a sample to a population (inferential statistics

## Links Offered With No Explanation

## Vocab

- Concept – a word that represents the similarities in otherwise diverse phenomena: classification by definition
- Variable – a measurable concept that takes on two or more values that are mutually exclusive and exhaustive. By mutually exclusive, I mean that each case (i.e. entity that is being measured) can be assigned to only one of the available values. By exhaustive, I mean that every case can be assigned to a value.
- Independent variable — the variable or variables that effect changes (that is “cause” or explain) in the dependent variable. The x’s
- Dependent variable — the variable that is affected by (is explained or “caused” ) by the independent variables. The y’s.
- Hypothesis — a testable statement predicting a relationship between two or more variables
- Case – one unit as defined by the unit of analysis
- Unit of analysis — the entity, generally described, about which data are gathered

## Homework

For each of the following examples, indicate whether it involves the use of descriptive or inferential statistics. Justify your answer

- The number of unemployed people in the United States
- Inferential statistics: these numbers are estimates based on data about changes in initial unemployment claims and other data.

- Determining students’ opinion about the quality of cafeteria food based on a sample of 100 students
- Sampling part of a population to make conclusions about the larger population is an inferential method.

- The national incidence of breast cancer among Asian women
- This is another inferential statistic based on data about a sample of the population.

- Conducting a study to determine the rating of the quality of a new smartphone gathered from 1000 new buyers.
- This is another inferential statistic based on data about a sample of the population.

- The average GPA of various majors (e.g. sociology, psychology, English) at your university
- This is a descriptive statistic since all the data is available for analysis.

- The change in the number of immigrants coming to the United States from Southeast Asian countries between 2010 and 2015
- This is a descriptive statistic since all the data is available for analysis.

Construct measures of political participation at the nominal, ordinal and interval/ratio levels

- Nominal: Party affiliation
- Ordinal: Political right/left spectrum alignment
- Interval/Ratio: Voter turnout