# Biostatistics & Epidemiology Lect. 1 Part 1

version from 2016-08-15 21:24

## Section

What is Biostatistics? (1)(1) Numerical descriptions of events or phenomena
What is Biostatistics? (2)(2) A set of mathematical tools to quantitatively assess clinical and laboratory experiences
What is Biostatistics? (3)(3) Contemporary biostatistical analysis uses a smaller, representative group to make inferences about a larger group.
What is Biostatistics? (4)(4) Sample used to infer about the larger population

Why study Statistics? (1)(1) Making sense of numerical information
Why study Statistics? (2)(2) Dealing with uncertainty
Why study Statistics? (3)(3) Sampling instead of direct count entire population.
Why study Statistics? (4)(4) Association and relationships
Why study Statistics? (5)(5) Forecasting and prediction
Why study Statistics? (6)(6) Decison-making in and uncertain environment

Why is biostatistical analysis important? (1)(1) Medical literature uses biostatistics regularly.
Why is biostatistical analysis important? (2)(2) Choosing a statistical test depends on duty design and the scale of measurement of the variables
Why is biostatistical analysis important? (3)(3) Data may be analyzed using more than one statistical test
Why is biostatistical analysis important? (4)(4) As a clinician, you need to be able to evaluate appropriateness of statistical methods used in literature

T or F? Statistics help to interprete and evaluate the use of statistical analysis and methodology to be able to read the medical and pharmaceutical literature appropriatelyTrue
T or F? Data may be analyzed using more than one statistical test and may lead to manipulation of data to enhance resultsTrue
T or F? Data may be analyzed using more than one statistical test and may produce unreliable resultsTrue
T or F? Correlation is when there is a real cause-effects relationship in statistical or data analysisFalse, Correlation means there is no direct of an event and result
When statistics or numbers indicates something is highly related to another, and does not necessarily mean one cause the other to happen, this is an example of ------- ?Correlation