Class 29: Biostats (Don't Screw This Up, This'll Be Weird)

Question 1

What are study/data measurements?

Answer 1

• • It’s all blue.
• Data’ will be collected on desired ‘variables’
• Dependent variable(s) [outcome variables]
• Independent variables
• Comparisons are commonly made (statistical analyses)
• Inferences will be made about the sample-derived ‘data’ and their comparisons (Null Hypothesis)

Question 2

What is null hypothesis?

Answer 2

• Null Hypothesis (H0)
• ** Researchers either ACCEPT or REJECT this perspective, based on STATISTICAL ANALYSIS
• A research perspective which states there will be no (true) difference between the groups being compared
• Most conservative and commonly utilized
• Various statistical-perspectives can be taken by the researcher:
• • Superiority
• • Noninferiority
• • Equivalency
• Alternative Hypothesis (H1)
• A research perspective which states there Will Be a (true) difference between the groups being compared

Question 3

Name the three primary levels (groupings) for variables based on answers to 2 key attributes

Answer 3

• NOMINAL
• ORDINAL
• INTERVAL

Question 4

What are the 2 key attributes of data management

Answer 4

1. Magnitude (or Dimensionality)
2. Consistency of scale (Fixed Interval)
   - Equal, measurable spacing between UNITS of scale

Unofficial third: 3. Rational/Absolute Zero (Ratio group)

Each attribute can be assessed with a “YES” or “NO” response to the inquiry of ‘Does it have IT’

Question 5

Describe the Nominal Level

Answer 5

• NOMINAL (Dichotomous/Binary; Non-Ranked Named Categories)
• NO Magnitude / NO Consistency of scale
• NOMINAL VARIABLES ARE SIMPLY LABELED-VARIABLES WITHOUT QUANTITATIVE CHARACTERISTICS (OR DICHOTOMOUS)
• Example:
• Male/Female, Democrat/Rebpublican, Truck Driver/Lawyer

Non-example: Being a second year med student means suggests you’ve been in med school longer so that can’t count. No numerical magnitude allowed. (Correction: Turns out this last paragraph/sentence is totally not true)

Question 6

Describe the ordinal level

Answer 6

• ORDINAL (Ranked Categories; Non-Equal-Distance)
• YES Magnitude / NO Consistency of scale
• This one is like nominal, but has to be ranked or ordered. One thing is larger than another.
• Examples include Satisfaction surveys (From 1 being hated it to 5 being worshiped it)

Question 7

Describe the interval/ration Level

Answer 7

• INTERVAL/RATIO (Order & Magnitude & Equal Intervals-of-scale (UNITS))
• YES Magnitude / YES Consistency of scale
• Living Siblings (number) & Personal Age (in years)
• Can you describe others?

(These have to be exact, consistent across everyone, and measurable. You’ll probably screw this up somehow.)

• See Slides 12-13 for breakdown.

Question 8

What is the hierarchy for changing levels of measurement data

Answer 8

• Nominal - Attributes are only named; weakest level
• Ordinal - Attributes can be ordered
• Interval - Distance is meaningful
• Ratio - Absolute Zero
• After data is collected, we can appropriately go down in specificity/detail of data measurement (levels), but never up!
• We can change glucose numbers to (prediabetic, diabetic as fuck, etc…), but we can’t change the categories into numbers without knowing said numbers.