Chapter 1 Notes

©2008 by S. Gramlich

Updated 3/2/2022

Definitions and Experimental Design

! = Important Note

! These Notes are not meant to replace Reading. Read Chapter first.

1-1

Differentiate between Population and Sample?

Population represents ALL of what you intend to study

Sample represents a portion of the Population

1-2

Read “Stat Thinking” and pitfalls

To convert a fraction to a %:

Divide the Numerator by the Denominator then move the decimal 2 places to the Right (add % symbol).

1-3

Differentiate between Parameter and Statistic?

Parameter = # describing Population

Statistic = # describing Sample

Differentiate between Discrete and Continuous data?

Discrete = counts

Continuous = measurements

Levels of Measurement

Nominal = names

Ordinal = names with order

Interval = #'s without a starting point

Ratio = #'s with a starting point

1-4

Differentiate between Observational and Experimental Studies?

Observational = observe but don't modify

Experiment = modify with treatment

Simple Random Sample (SRS) = sample of subjects selected in a way where sample of same size has same chance of being chosen

Types of Observational Studies

Cross-Sectional = 1 point in the past

Retrospective (Case-Control) = past period

Prospective (Longitudinal or Cohort) = track subjects in future

Types of Sampling

Random = randomly generated (ie computer)

Systematic = every k^th member

Convenience = readily available

Stratified = subdivide into at least 2 subgroups (strata) then sample from each group

Cluster = subdivide into at least 2 subgroups (clusters) then sample ALL from 1 or more of the groups

Sampling Error = unusual data by chance

Nonsampling Error = unusual data from wrong entry, computing error, bias, falsification, or inappropriate stat methods