Week 1 Flashcards
(29 cards)
What is Epidemiology
The study of the distribution & determinants of disease in specific populations
AKA
Study of how often diseases occur in different groups of people and why
Name the 3-D’s of Epidemiology
Disease, Distribution, and Determinants
Describe Biostatistics
Collecting, summarising, analysing, and drawing conclusions from data
Refers to the statistics in health and biological fields
What is a statistical test
Used to exclude the likelihood of random chance or luck
Population vs Samples
population: all curtin students
samples: 20 random curtin students
Parameters vs Statistics
Parameters: the descriptive measure of population
Statistics: a descriptive measure of sample
Exposure and Outcome
predictor or independent variable
Exposure: Smoking
Outcome: Lung cancer
Random Sample
How you recruit your samples
Sampling frame
everyone in the population who has the potential to be recruited
Sampling variation
Dispersion/spread of your data
Sampling error
difference expected from sample vs population
Variable
Something measurable
gender, smoker vs non smoker, blood pressure
What are the 2 types of data
Categorical data: nominal and ordinal data. Assigns data into groups (smokers/non-smokers, gender, favourite colour, age)
Continuous data: Interval and ratio data. Can take any value within a range (the number of students in a class, you could not find an average as there cannot be half a student)
What are the four scales of measurement
Nominal, Ordinal, Interval, Ratio
Nominal scale
-Names/categories
-No info regarding magnitude/size
EXAMPLE: religion, nationality, favourite colour
Binary = only 2 catergories
A nominal scale of measurement with only 2 categories is known as
Binary
Ordinal scale (organsied)
-Categories
-Relationship between the categories
-Can be arranged in order/magnitude
-Gaps/intervals between categories are not numerically equal
EXAMPLE:
-1st, 2nd, 3rd
-severity of disease: mild, moderate, severe
-non-smoker, light-smoker, moderate smoker, etc
Interval Scale
-Information expressed as (actual values/numerical values)
-categories
-relationship between categories
-can be arranged in magnitude/order
-gaps/intervals are equal eg. 10-15 & 25-30
-No true 0 (eg. 0 degrees does not mean there is no temp)
EXAMPLES:
-IQ test
-Temperature
Ratio Scale
-Categories
-Relationship between categories
-Can arrange in order/magnitude
-Gaps/intervals are equal (10-15 & 25-30)
-Has a true 0 (0=the absence of that variable or characteristic)
EXAMPLE:
-money
-heartbeat
-weight
Which 2 Scales use categorical data
Nominal & Ordinal
Which 2 scaled use continuous data
Interval & Ratio
Define cases
Individual
What are descriptive statistics
Describe and summarise data
Define Inferential data
Make ‘inferences’ about the population (unknown), based on our sample (known)
Distribution of probability
