Week 1

Question 1

1. Define ‘Biostatistics’ and ‘Epidemiology’ and how the two are related.

Answer 1

Epidemiology – Study of distribution and determinants of disease so that further study may be conducted or interventions can be created
Biostatistics – Collecting, summarising, analysing and drawing conclustions from the data.
Epidemiology allows us to collect information, Biostatistics allows us to analyse the data from Epidemiological studies and draw valid conclusions

Question 2

2. Understand why we need to learn Statistical & Epidemiological methods for practicing Evidence Based Health care.

Answer 2

Stastical & Epidemiological methods allow us to collect valid and accurate statistical information surrounding disease. The validity of this information creates the foundation for quality and reliable Health care practice based on true and accurate information

Question 3

3. Distinguish between Population & Sample, Statistics & Parameters, Qualitative & Quantitative data, Continuous & Categorical variables, Null & Alternative hypotheses (& few others).

Answer 3

Population & Sample – population is the total number of persons from which data can be collected, Sample is a subset of the population selected for the study
Statistics & Parameters -
Qualitative & Quantitative data -
Continuous & categorical values - Categorical data has variables which can be categorized. Consists of Nominal & Ordinal variables. Continuous data has characteristics in data that are measurabile. Consists of Interval & ratio variables
Null & Alternative hypothesis –

Question 4

4. Describe data types and how scales of measurement differ in precision & depth of information.

Answer 4

Categorical data has variables which can be categorized. Consists of Nominal & Ordinal variables. Continuous data has characteristics in data that are measurabile. Consists of Interval & ratio variables
The different type of variables ie Nominal, ordinal, interval, ratio determine the type of testing
4 scales of measurement - describe the level of precision required to answer the question
Nominal- Least amount of detail
-Names and categories only (Binary = two categories)
-No meaningful relationship between categories
-No info regarding magnitude or size
Ordinal- More detail than ordinal
- No mathematical scale
-Categories based on ranking
-relationship between categories
-Intervals between categories are not numerically equidistant
-examples: 1st, 2nd, 3rd ; non-smoker, light smoker, moderate smoker, heavy smoker; Mild, moderate, severe
Interval- More precise detail than nominal and ordinal
-Numerically equal, eg. Difference between 10 & 15 same as 25 & 30
-No true 0 point
-examples: Temperature, depression rantings, risk assessment scores, IQ scores
Ratio- More precise detail than nominal and ordinal
-same criteria as interval
-There is a true 0 point
-examples: money, heartbeat, income, crime rate, unemployment rate

Question 5

7. How is a study designed?

Answer 5

Come up with an unanswered but answerable question.
Search published literature – has the question been answered already?
Plan & conduct a study – If the question has yet to be answered
-choose a design to answer the question – design is dictated by research question and resources ie financing and time
-Obtain a sample & participants – should represent target population, and give a variety of information so that the question can be answered
-Decide what information (or data) are required, decide how to collect
-Collect relevant data
Data entry, cleaning, screen for errors, screen for outliers
Summarise with frequencies, graphs… make sense of the data
Choose suitable statistical test/analysis relevant to they type of data you are analysing (to answer the research questions)
Draw objective & valid conclusions
Share & publish

Question 6

What is this: µ

Answer 6

named ‘mu’ –it is the symbol for mean. important to remember as when working with inferencial statistics and making estimations or conclusions beyond the sample the hypothesis will be made using this letter