Statistics and Biostatistics Overview

Study Notes

Summarizes data and provides insights.
Simplifies data, but may omit valuable information.
Descriptive statistics: focuses on collecting, organizing, and analyzing data.
Inferential statistics: uses data to draw conclusions about populations.

Data are often organized in terms of variables, which are characteristics that change between individuals within a population.
Grouped data is organized into categories (e.g., age ranges).
Ungrouped data is presented as individual numerical values (e.g., specific ages).
Continuous data can be measured and have any value within a range (e.g., height, weight, temperature).
Discrete data is counted and has separate values (e.g., number of pregnancies).

Ordinal data can be ranked in order (e.g., satisfaction levels, academic grades). Limited mathematical operations are possible.
Nominal data cannot be ranked and represent qualitative differences (e.g., gender, educational programs). No mathematical operations are possible.

Independent variables (IV) are not modified in a study and typically are represented on the x-axis of a graph.
Examples:
- Age
- Gender
- Race
- Ethnicity
Dependent variables (DV) are affected by the IV and are usually represented on the y-axis of a graph.
The DV is tested and its value is determined by the IV.

Primary data is collected directly by the researcher.
Secondary data is collected by others, such as government agencies or international organizations.

Pie chart displays proportions of categories in a circle.
Bar graph compares frequencies of categories using rectangles.
Stacked bar graph shows proportions within categories using stacked bars.
Statistical map displays geographical variations in variables.
Histogram shows frequencies of numerical data using contiguous bars.
Frequency polygon connects points representing frequencies of data categories.
Time series chart displays changes in variables over time.