# USP493 Session 1 Notes

## 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
• 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
• 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

## 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

1. 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.
2. 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.
3. The national incidence of breast cancer among Asian women
• This is another inferential statistic based on data about a sample of the population.
4. 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.
5. 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.
6. 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