lecture 1 biostats

Nature is full of ______

vartiation

time to time, person to person , replicate to replicate

Systemic variation

“Real represents differences that are systemic

Noise variation

Natural or random variation

Population

Entire collection of some sort of individuals

Parameters

Numerical facts about a population

census

Study population examining each and every member

Sample

Selected subset of a population

Statistics

Numerical facts about a sample

Inference

Values of sample stats are often used as guesses about the population

observation and ___ may not be the same

Data

Variable

Characteristic or attribute

ex: color is variable red is data value

Relationship exist between

Two variables if they co-vary

ex- increasing (excessive) sun exposure accompanied by increasing numbers of events of skin cancer

Statistical modeling

Discover relationships

example of analysis/synthesis

a couple had a baby with a genetic defect. They are considering having another baby. What’s the chances(likelihood) their second child will have a genetic defect too

Description

Values of stats from sample to make estimate about corresponding parameter values that characterize a population

Inference making

Fitting and comparison of competing models of the data , obtain comparison (hypothesis test) of competing explanations (hypotheses) of the phenomena we have observed

signal to noise ratio

Signal-treatment effect , expire effect, secular trend

noise- natural variation, random error

In summarizing data relevant aspects

Ask urself “what’s relevant”

goal- aim for summaries that are simple clear and thorough

tip- avoid misleading summaries

variable vs data : variable

Variable something whose value can vary

ex: age sex blood type

variable vs data : data

Value of a variable

ex: 54 years, female

two types of datat types

categorical(qualitative)(attributes)

numerical (quantitative) (numbers)

Two categories of caterogorical(qualitative)

nominal and ordinal

Nominal

Values are names that are unordered categories

ex : gender : male, female

ex2: cause of deaths : cancer, heart attack

Ordinal

Values are names that are ordered categories

ex- pain level : mild moderate severe

size of container: small medium large

Two categories of mumerical(quantitative)

Discrete and continuous

Discrete

values are integer values 0,1,2… on a proper numeric scale

ex: number of visits 0,1,2 etc.

Values are a measured number of units including possible decimal values on a continuous scale

Weight

123.6 ins

Catergories that make up qualitative variables are called ___ of the variable

Catergories that make up qualitative variables are called levels of the variable

Numerical>continous>interval

No true zero

measured on a continuum and differences btwn any two numbers on the scale are known size

Numerical>continous>ratio

Meaningful zero

Ratio data have meaningful zero point