stats vocab sampling

Question 1

stratified

Answer 1

sampling where population is divided into groups based on some characteristic, then within each group a probability sample (likely srs) is selected (groups= strata), not all individuals within sample strata used

Question 2

cluster

Answer 2

every member of the population is assigned to 1 and only 1 group (cluster) and then a sample of clusters is chosen with likely srs and all individuals within sample clusters are surveyed
- often economical, not as precise as strata

Question 3

multistage sampling

Answer 3

• select sample with different sampling methods

Question 4

systematic random sampling

Answer 4

1) list every member in pop
2) randomly select first sample element from first “k” elements
3) select every kth element in set

Question 5

voluntary

Answer 5

people who SELF SELECT, often strong negative opinions

Question 6

SRS

Answer 6

give each individual an equal chance of being selected (avoiding bias) and gives every possible sample an equal chance to be chosen)

Question 7

convienience sample

Answer 7

made up of easy to reach people

Question 8

census

Answer 8

actually obtaining data from every member in population but isn’t pratical because of cost and time required, is a parameter

Question 9

setting up srs

Answer 9

• label each of kids and give them a unique # from 1-whatever parameter
  use a rng and produce __ # s, ignoring repeats, and the kids with those numbers are the samples

Question 10

srs response

Answer 10

this is not srs because not every group of n (Name) because not every group of (name and sample size) is equally likely to be chosen. for example, you could not have ___ (one type) and ____ (other type) in a group

Question 11

stratified vs cluster

Answer 11

stratified sample is internally homogenous and externally heterogenous and cluster sample is externally homogenous and internally heterogenous

Question 12

%

Answer 12

think: probability, relative frequency, data is probably categorical

Question 13

of people selected

Answer 13

statistic

Question 14

definitely quantitative and univariate

Answer 14

histogram

Question 15

suppose we have 300 kids, we want to select 2 0kids but we want them to be 10 boys and 10 girls

Answer 15

this is not srs because not every group of 20 kids is equally chosen. for example, you could never get all girls in a sample.

Question 16

when labeling people in sample for srs, do 01-15 for example, not 1-15

Question 17

this is most likely a voluntary sample situation, so my sample is made up of mostly strong and negative opinions. Thus, I am not convinced that the majority of people disagree and the sample result most likely overestimates the number of people in opposition

Answer 17

voluntary response sample response