Lectures 29-34: Intro to Biostatistics

Question 1

Population

Answer 1

ALL individuals that represent variable of interest. It is usually not realistic to study the entire POPULATION

Question 2

Sample

Answer 2

A subset or portion of the full population; “representatives” of population. More often used as studying the complete population is not feasible; random processes commonly used to draw sample

Question 3

Null Hypothesis

Answer 3

A research perspective which states that there will be NO true difference between compared groups; most conservative/commonly utilized perspective. Researchers either accept or reject at study’s end.

Question 4

Superiority statistical perspective

Answer 4

Studies framed from the mindset that treatment/outcome is probably BETTER than others, but can not answer if it is equal or worse.

Question 5

Noninferiority statistical perspective

Answer 5

The outcome is “NOT WORSE” than in other studies.

Question 6

Equivalency statistical perspective

Answer 6

The outcome is “JUST AS GOOD” as everything else on the market/other outcomes

Question 7

Magnitude

Answer 7

One key attribute of data measurement; asks if data has “dimensionality.” Must be assessed Y/N

Question 8

Consistency of Scale/Fixed Interval

Answer 8

Second key attribute of data measurement; asks if data has units and if the scale of units is equal and measureable. Must be assessed Y/N

Question 9

Rational/Absolute Zero

Answer 9

Third key attribute of data measurement; not studied in detail here as it does NOT affect what statistical test is used

Question 10

Nominal variable

Answer 10

A variable that has NO magnitude and NO consistency of scale; in other words, answers NO to both key data attributes. Example: gender, hair color; just named categories that are not ranked.