LEARNING OBJECTIVES
1. Big picture of Statistics
2. Data
3. Collecting data
4. Mechanistic and Empirical models
## Why is Statistics? - Statistics allows you to understand a subject much more deeply.
- Statistics helps us to make discoveries in science, make decisions based on data, and make predictions.
- Statisticians and statistical methods are important part of pharmaceutical industry, social scientists, business practice,…
## What is Statistics? - Statistics is the science of collecting, organizing, analyzing, and interpreting
**DATA** in order to make decisions
**Descriptive Statistics:**
Involves organizing, summarizing, and displaying data.
e.g. Tables, charts, averages
**Inferential Statistics:**
Involves using sample data to draw conclusions about a population.
## Statistical concepts - Population: the complete collection of all individuals to be studied.
- Sample:
*Sub-collection* of members selected from a population. - Data: consist of information coming from observations, counts, measurements, or responses.
- Parameter: a numerical measurement describing some characteristic of a population.
- Statistic: a numerical measurement describing some characteristic of a sample
**.** ## Type of data
Quantitative data
Age
Temperature
Qualitative data
Place of birth
Major
Continuous
Discrete
## Collecting data - Retrospective study: using historical data.
- Observational study: A researcher observes and measures characteristics of interest of part of a population.
- Designed experiment: A treatment is applied to part of a population and responses are observed
## Statistical model - Mechanistic model: built from our underlying knowledge.
*Example:* Current = Voltage/Resistance, or I = U / R - Empirical model: uses our engineering and scientific knowledge of the phenomenon:
## Response = deterministic function + random error *Example: *I = U / R + ε ## Remark: ε is a term added to the model to account for the fact that the observed values of current flow do not perfectly conform to the mechanistic model.
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