Randomness, Samples Surveys, and Observations

Question 1

Pick numbers for lottery

Answer 1

Random

Question 2

Start with seed value and build with algorithm
Random integer table
-Appendix F
-Start at top left
-Read 1 digit, 2, 3 ect.
-If not in range, then skip

Answer 2

Pseudo random

Question 3

Math
Prob
rand is [0,1]
randInt(min, max, number of answers)
-Can store into list
-Not equal probability

Answer 3

Random integer

Question 4

Dice Rolling (2)

• 6 options for one dice
• 6 options to pair it with
• 36 combinations

Answer 4

Calculating possibilities

Question 5

Math

Remainder (x,y)

Answer 5

Remainder

Question 6

Apps

ProbSim

Answer 6

Simulate dice

Question 7

Assign random integers
Produce random integers
Sort
Store into list

Answer 7

Comparing

Question 8

Sample should be _ and represent whole population which can be obtained by _.

Answer 8

Diverse, randomizing

Question 9

_ rather than choice in sampling.

Answer 9

Random

Question 10

Key numbers in mathematical models

Answer 10

Population parameters

Question 11

Means that the statistics reflect the parameters

Answer 11

Representative

Question 12

What sample size in drawn from

Answer 12

Sampling frame

Question 13

If sample is different, then data will be different

Benefits stratified

Answer 13

Sampling Variability

Question 14

Simple Random Sample

• Has to be equivalent of drawing names out of a hat
• Every subset of size n has _ chance of being chosen
• Not every individual has an equal chance (only _) because any sampling method has an equal chance for the individual

Answer 14

Equal, subset

Question 15

Stratified (like a layered cake)

• Choose the separation
• Layers are as thick as that group is _ in the population
• Predefine groups (_) and perform an SRS on each strata, then put them apart and back together
• Better than SRS because more representative of population

Answer 15

Represented, strata

Question 16

Systematic

-Choose every _ term

Answer 16

nth

Question 17

Cluster Sampling

• Population is already split up into _
• Choose a cluster(s) by SRS
  
  • Ex. School, zip code, street
• Perform a _ of that cluster
  
  • A census is asking or measuring everything
  • Questioning the whole population
• Good when _ separated

Answer 17

Clusters, census, physically

Question 18

Convenience Sample

• Voluntary response survey
• Usually a lot of _

Answer 18

Bias

Question 19

Combine several sampling methods

Answer 19

Multilayer samples

Question 20

Trail run of survey

Answer 20

Pilot

Question 21

Only people with strong opinions respond

Answer 21

Voluntary response bias

Question 22

Those who don’t care don’t respond

Answer 22

Nonresponse bias

Question 23

Not proportionally representative

Answer 23

Under coverage

Question 24

Something is done to influence people’s responses or they give incorrect answers

Answer 24

Response bias

Question 25

Characterized by giving treatment and random assignment and see cause and effect

Answer 25

Experiments

Question 26

Stratified: _

Answer 26

Blocking

Question 27

Only block if there is a _ in the results based on the separation

Answer 27

Difference

Question 28

Completely Randomized (Good) - Treatments assigned randomly to all _ - Compare effects of treatment

Answer 28

Subjects

Question 29

Block Design (Better) - Splitting subjects into heterogeneous groups (blocks) - Assign treatments randomly in each _ - Compare effects across blocks

Answer 29

Block

Question 30

``` Match Pairs (Best) -Every subject receives _ treatment or treatment and placebo ```

Answer 30

Both

Question 31

Factor

Answer 31

Broader

Question 32

Level

Answer 32

Extra division of factor

Question 33

Attributes to effect

Answer 33

Response

Question 34

Subjects

Answer 34

Experimental units

Question 35

Designing Experiments - Assign random _ on call list - Block if necessary - Generate random integers - Skip _ - Skip numbers not in _ - Associate back to names - Call them - Try to have at least 5 trials - Should have a _

Answer 35

Integers, repeats, range, control

Question 36

Subject doesn’t know what treatment

Answer 36

Blind (Good)

Question 37

Subject and evaluator don’t know which treatment | Only head scientist knows

Answer 37

Double Blind (Better)

Question 38

Levels of one factor are associated with another factor in such a way that the effects cannot be separated

Answer 38

Confounding

Question 39

Pairing people who are similar to see results of different variables

Answer 39

Matching

Question 40

No treatments or manipulations just study records No cause and effect Only correlation and association

Answer 40

Observational studies

Question 41

_ - Past - Find relationships - No need to be randomized

Answer 41

Retrospective

Question 42

_ - Future - Find relationships - Estimate differences

Answer 42

Prospective