Biostats /sampling

Question 1

How do we describe or quantify something?

Answer 1

Make it into a proportion, %, ratio

Question 2

What is Nominal scale?

Answer 2

Categories
– positive/negative
–sex
–breed

Question 3

What is Ordinal scale?

Answer 3

Ranked

– heart murmurs, BCS, pain, lameness

Question 4

What is Interval scale?

Answer 4

‘True’ numbers
– age, weight, CBC

• Measures of central tendency
• Mean, median, mode
• Measures of Dispersion
• Range, SD, Percentile

Question 5

Population

Answer 5

The ENTIRE COLLECTION of observations or subjects that have something in common and to which conclusions are inferred

Question 6

Sample

Answer 6

A SUBSET of the population, ideally selected so as to be representative of the population

Question 7

Simple random sampling

Answer 7

every subject has equal probability of being selected.

Question 8

Stratified random sampling

Answer 8

population is divided into subgroups, then random sampling applied within each subgroup
** need to know characteristics about the population

Question 9

Systematic random sampling

Answer 9

every x-th subject selected

*Must pre-determine the interval you want to select

Question 10

Cluster random sampling

Answer 10

when sampling unit (e.g., group) is different from study unit (e.g., individual).

Question 11

What is the diff btwn random sampling and randomization?

Answer 11

Random sampling
-Purpose is to select subjects from a population

Randomization
- after you have picked your sample, then you are randomly assigning them to a group (each group has equal chance of being assigned to the groups)

Question 12

What is the difference between:

Descriptive vs Inferential statistics

Answer 12

Descriptive statistics apply to the study

Inferential statistics is generalized the results

• -Estimation (used to estimate dz prevalence)
• -Hypothesis testing!

Question 13

What is Hypothesis testing?

Answer 13

• requires the assumption of a “null hypothesis”

Question 14

What is a null hypothesis?

Answer 14

• assumes NO difference in groups
• ALWAYS assume the null hypothesis is true
• we NEVER ACCEPT
  - Reject or “not reject”

Question 15

What is the Alternative hypothesis?

Answer 15

“parameterization” of the research hypothesis

** difference in values

Question 16

What is a p-value?

Answer 16

the probability of observing the data that we actually had OR the data more extreme assuming the null hypothesis is true.

** Does not measure degree of difference, just the probability of obtaining these results or better if null hypothesis is true.

2 factors that influence it:
- Effect/ difference / association btwn groups
- Sample size (precision)
Doe– increased sample size = decrease p-value

Question 17

How do we decide when a p-value is “high” or “low”?

Answer 17

Alpha level / significance level
= an arbitrarily selected number ** Often 0.05

REJECT null hypoth if p < alpha
FAIL TO REJECT null hypoth if p > alpha
**Not “accept”

Question 18

What does Alpha represent?

Answer 18

the chance one is willing to take in mistakenly rejecting a true null hypothesis (i.e. making a Type 1 error)

Question 19

What are the errors that can occur by making inferences about a hypothesis?
What are terms for accurately ID’ing a hypothesis?

Answer 19

Reject the null hypothesis

• Null is True = TYPE 1 error
  
  • reject when its really true –chance of doing this is < 5%
  • similar to false positive
• Null is False = Power

Fail to reject null hypoth

• Null is true = Confidence
• Null is False = TYPE 2 Error
  
  • the test did not distinguish btwn 2 groups, but there IS a diff!
  • similar to False negative

Question 20

Does a result that is non-significant imply there is no difference btwn the 2 groups?

Answer 20

NO!

Question 21

How is it possible that a smaller effect results in more statistical significance?

Answer 21

p-value is a mixture of:
- effect size
= measure to QUANTIFY how DIFFERENT study groups are
AND
- precision
= measure to QUANTIFY VARIABILITY of an estimate.


Question 22

What is the importance of Confidence intervals?

Answer 22

• a measure of PRECISION!
• deals with the “width” from “Point Estimate”
  - PE= number used in study as cutoff

*** larger confidence with larger sample size