Bioinformatics and Statistics Quiz 1

Statistics

branch of mathematics that involves collecting, analyzing, interpreting, presenting, and organizing data

tool for understanding and communicating info in datasets

for data driven decision making, variability understanding, id trends & patterns, ensure reliability

Statistics Purpose

1. summarize and meaningfully describe data

2. infer insights & make prediction on populations from sample data

3. guide decision making from evidence

Descriptive Stats

summarize data and describe main features, central tendency & variation, histograms, box plots

purpose: simplify large datasets into understandable metrics, id trends, patterns, variability

Inferential Stats

use sample data to make generalizations about a population

Data Types

1. Nominal - qualitative, non-hierarchical (blood type)

2. Ordinal - qualitative, hierarchical (pain on 1-10 scale)

3. Discrete - quantitative, discontinuous numbers (heart rate)

4. Continuous - quantitative, numerical, can be measured infinitely (weight)

Measures of Central Tendency

mean, median, mode

Measures of Dispersion

range, variance, standard deviation, quantiles, coefficient of variation

Biostatistics

application of stat principles to biology, specifically in medical and health studies. essential for experiment design, data analysis, drawing valid conclusions

roles: quantify & interpret variability in data; ensure reliable, reproducible, scientifically valid findings; guide decision making in clinical trials, epidemiology, & public health

Biostats Answering Scientific Questions

1. Formulate Question - define problem/hypothesis

2. Design Study - study type, sample size and randomization

3. Collect data - accurate & reliable data

4. Interpret Results - determine implications of findings

5. Communicate Findings - present results, graphs, tables, reports

Stats Ethical Considerations

• Integrity & Accuracy: remove bias

• Transparency: clearly report methods and limits

• Informed Consent: ensure participants are fully informed and agree to data collection

Weighted Mean

assigns dif weights to dif values, applicable when some data points contribute more than others

Mean

• used for normally distributed continuous data, comparing overall trends

• Adv. easy to calculate & understand uses all data and best for symmetrical

• Disadv. sensitive to outliers, not useful for skewed

Median

• used for skewed or ordinal data, income/housing prices

• Adv. not effected by outliers, more representative for skewed distributions, good for ordinal

• Disadv. ignores exact values, less useful for normal distributions

Mode

• used for categorical data, id common values, multimodal data

• adv. categorical data, simple and easy to understand, multimodal

• disadv. may not exist or be unique, not useful for continuous

Quantiles

the pth percentile is the value Vp such that p percent of the sample points are less than or equal to Vp

req ordered data sets

Coefficient of Variation

CV = standard deviation / mean * 100%

comparing variability of several different samples with different means

Visualization Tools

• Box/Whisker plots - range, median, IQR, highlights outliers

• Scatter plots - displays relationship btwn two cont. variables

• Bar charts - rep categorical data with rectangular bars proportional to their frequency

• Histogram - graphical rep of the frequency distribution of a dataset

Descriptive Stats Applications

• Clinical Trials: demographics, data analysis

• Epidemiology: analyze disease incidence rates

• Public Health: assess impact of health interventions

• Medical Device Testing: ensure reliability through variance measurements

Type Set vs. Plain Text

typeset - uses special symbols, 2D structure, what you would write

plain text - single line, typed characters only