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AP Statistics > Randomness, Samples Surveys, and Observations > Flashcards

Randomness, Samples Surveys, and Observations Flashcards

1
Q

Pick numbers for lottery

A

Random

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2
Q 
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
A

Pseudo random

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3
Q 
Math
Prob
rand is [0,1]
randInt(min, max, number of answers)
-Can store into list
-Not equal probability
A

Random integer

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4
Q

Dice Rolling (2)

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

Calculating possibilities

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5
Q

Math

Remainder (x,y)

A

Remainder

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6
Q

Apps

ProbSim

A

Simulate dice

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7
Q

Assign random integers
Produce random integers
Sort
Store into list

A

Comparing

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8
Q

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

A

Diverse, randomizing

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9
Q

_ rather than choice in sampling.

A

Random

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10
Q

Key numbers in mathematical models

A

Population parameters

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11
Q

Means that the statistics reflect the parameters

A

Representative

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12
Q

What sample size in drawn from

A

Sampling frame

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13
Q

If sample is different, then data will be different

Benefits stratified

A

Sampling Variability

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14
Q

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
A

Equal, subset

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15
Q

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
A

Represented, strata

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16
Q

Systematic

-Choose every _ term

A

nth

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17
Q

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
A

Clusters, census, physically

18
Q

Convenience Sample

  • Voluntary response survey
  • Usually a lot of _
A

Bias

19
Q

Combine several sampling methods

A

Multilayer samples

20
Q

Trail run of survey

A

Pilot

21
Q

Only people with strong opinions respond

A

Voluntary response bias

22
Q

Those who don’t care don’t respond

A

Nonresponse bias

23
Q

Not proportionally representative

A

Under coverage

24
Q

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

A

Response bias

25
Q

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

A

Experiments

26
Q

Stratified: _

A

Blocking

27
Q

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

A

Difference

28
Q

Completely Randomized (Good)

  • Treatments assigned randomly to all _
  • Compare effects of treatment
A

Subjects

29
Q

Block Design (Better)

  • Splitting subjects into heterogeneous groups (blocks)
  • Assign treatments randomly in each _
  • Compare effects across blocks
A

Block

30
Q 
Match Pairs (Best)
-Every subject receives _ treatment or treatment and placebo
A

Both

31
Q

Factor

A

Broader

32
Q

Level

A

Extra division of factor

33
Q

Attributes to effect

A

Response

34
Q

Subjects

A

Experimental units

35
Q

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 _
A

Integers, repeats, range, control

36
Q

Subject doesn’t know what treatment

A

Blind (Good)

37
Q

Subject and evaluator don’t know which treatment

Only head scientist knows

A

Double Blind (Better)

38
Q

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

A

Confounding

39
Q

Pairing people who are similar to see results of different variables

A

Matching

40
Q

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

A

Observational studies

41
Q

_

  • Past
  • Find relationships
  • No need to be randomized
A

Retrospective

42
Q

_

  • Future
  • Find relationships
  • Estimate differences
A

Prospective

AP Statistics (7 decks)

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