1. Introduction (1.1)
Data - Information collected by individuals and/or organizations to gain knowledge regarding a field or question of interest.
Data Sources:
Surveys (Mail, Telephone, Internet)
Content Analysis (Newspaper, Magazine, Television)
Natural Experiments/Field Studies
Controlled Experiments
Statistics- Set of methods for collecting/analyzing data

2. Uses of Statistical Methods (1.1)
Design - Planning/Implementing a study
Constructing a survey and deciding who to sample
Determining methods to be compared
Deciding which groups of units to be analyzed
Description - Summarizing data
Typical outcomes and distributions of outcomes
Tables and/or Graphs
Inference - Using sample data to predict or make statements regarding unobserved data

3. Description and Inference (1.2)
Population - Full set of subjects of interest to researcher
Sample - Subset of population that is observed and measured in a data collection study
Descriptive Statistics - Summary of the information in a sample of data
Inferential Statistics - Statements regarding a population, based on a sample

4. Parameters and Statistics (1.2)
Parameter - Numeric summary of a population
Population Mean - Average of a numeric measure
Population Proportion - Fraction having a particular characteristic
Statistic - Numeric summary of a sample
Populations can be well defined or conceptual
Inferences depend on the sample being representative of the general population

5. Statistical Computing (1.3)
Statistical computer packages have become widespread over recent years, and their methods and ease of use have improved drastically in recent years (SPSS, SAS, Minitab, STATA, etc)
Data must be entered into a data file:
Rows typically represent individuals
Columns typically represent variables