Stats Chapter 2 Flashcards Preview

Nutrition 207 - Stats > Stats Chapter 2 > Flashcards

Flashcards in Stats Chapter 2 Deck (22)
Loading flashcards...
1
Q

What is a variable?

A

characteristic that can vary in value among subjects - measurable

2
Q

What is the measurement scale?

A

the values the variable can take

3
Q

What are the two main types of variables?

A

quantitative and categorical (qualitative)

4
Q

What are nominal variables?

A

categorical variable that is unordered, has a quality not a magnitude

5
Q

What are interval variables?

A

quantitative variables that have levels of scale/magnitude with defined distances

6
Q

What are ordinal variables?

A

variables that have a natural order, but no defined distance. levels have a greater than or less than magnitude

7
Q

What is a discrete variable?

A

variable with possible values that form a set of separate numbers, finite number of possible values

8
Q

What is a continuous variable?

A

variable that can take an infinite continuum of possible real number values (can’t list all the possible values)

9
Q

What is randomization?

A

a method for achieving good sample representation

10
Q

What is a (simple) random sample?

A

each possible sample has the same chance of being selected

11
Q

What is a sampling frame?

A

List of all subjects in the population

12
Q

What are some ways to collect data?

A

sample survey, experiment, observational study

13
Q

What is sampling error?

A

how much the statistic differs from the parameter that it predicts

14
Q

What are 3 types of bias?

A

sampling, response and non-response

15
Q

What is sampling bias?

A

using nonprobablity sampling (volunteer sampling), having undercoverage

16
Q

What is response bias?

A

incorrect responses, misleading or confusing questions, question wording, interview leading

17
Q

What is non-response bias?

A

sampled subjects can’t be reached or refuse to participate, fail to answer some questions

18
Q

What is systematic random sampling?

A

selecting samples using a skip number (N/n = k), selects every kth subject

19
Q

What is stratified random sampling?

A

divides the population into separate groups (strata) and then selects a simple random sample from each stratum (can be proportional or disproportional to population)

20
Q

What is cluster sampling?

A

divides the population into a large number of clusters and selects a simple random sample from each cluster, use the subjects in those clusters for the sample

21
Q

What is the difference between stratified and cluster sampling?

A

a stratified sample uses every stratum, a cluster sample uses a sample of the clusters (not all of them)

22
Q

What is multistage sampling?

A

uses a combination of sampling methods