Week 1 Flashcards
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
Define central tendency
The typical score (median, mean, mode)
Define dispersion
How much variety is scored
How is the mean measured
AVERAGE
add all numbers together, and divide by the number of values
How is mode measured/used for
The number that occurs most often
Used for: Gender, attendance
How is Median measured
When all the numbers are listed least to greatest, the middle number
