# Stat Lecture 1

## 21 terms

### Statistics

Branch of mathematics dealing with the collection, analysis, interpretation, and presentation of masses of numerical data

### Biostatistics

Application of statistics to a wide range of topics in biology.

### Need for Statistics

- To deal with the variability
in nature.
- To describe, explain, and
interpret the given
information or data.

### Data Types

The raw material of statistics. Numbers.
Types
1. Discrete: Values that can assume only whole numbers
2. Continuous: May take any value within a defined range

### Variable

What is being observed or measured.

### Types of Data Data Type

- Nominal: Named category without order
- Ordinal: Category with order, without equal interval
- Interval: Category with equal interval without meaningful zero
- Ratio: Category with meaningful zero

### Descriptive & Inferential Statistics

- Descriptive: Presentation, organization & Summarization of data
- Inferential: Generalize from sample of data to a larger group of subject

### Summarizing Data

Raw data summarized using:
- Central tendency
- Dispersion

- Mean
- Geometric mean
- Harmonic mean
- Median
- Mode
- Quartiles

### Measure of Dispersion

- Very different distributions can have the same mean value
- Range
- Interquartile range
- Variance
- Sample Variance
- Sample Standard deviation

### Skewness

- Skew right: positive skew
- Skewed left: negative skew
- Not too much skewed: Mean is better
- Highly skewed: Median is better

### Presentation of data Type of variable - Summary measures to be presented

- Continuous variables: mean + Std deviation
- Continuous variables: Median (interquartile range)
- Ordinal Variables: Median (range)
- Nominal Variables: Frequency (percentage)

### Graphical Presentation of Data

- Relationship and comparisons are visual
- Not as daunting as table of numbers
- Allows some artistry and creativity

### Graphical Presentation- Pie Chart

- For nominal (categorical) variables
- Each slice is proportional to the percentage of the category it represents

### Graphical Presentation- Bar Graph

- For discrete variables
- Each value is represented by a bar
- The height of each bar denotes the frequency of occurrence of that value

### Graphical Presentation- Histogram

- For continuous variables
- Each bar corresponds to a particular class interva
- The height of the bar denotes the total frequency of occurrence of the values falling within those respective intervals

### Graphical Presentation- Line Graph

- Line graphs are used to display trend or pattern of one variable over the other, especially time trends
- Difficult to use histograms for two or more variables

### Graphical Presentation- Scatter graph

- To display values for two variables for a set of data
- Frequently used in regression

- Tables
- Graph