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Ap Stats > Ap Stats Midterm > Flashcards

Ap Stats Midterm Flashcards

1
Q

Population

A

Who you are trying to learn about as a whole

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2
Q

Parameter

A

Numerical value that describes a population

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3
Q

Sample

A

A smaller group of population that is hopefully representative

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4
Q

Statistic

A

Numerical value that describes the sample

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5
Q

Qualitative/categorical data

A

Mostly non-numerical

Ex:color of car, jersey number, brand of shoe

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6
Q

Quantitative data

A

All numeric, calculations and not percentages

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7
Q 
Who
What
Where
When
Why
How
A
  • who is the study about(population)
  • variables, quantity
  • date it happened, if given
  • location study or experiment took place
  • what’s the purpose
  • how did they get the data;
    - survey
    - experiment
    - record keeping
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8
Q

Pie chart

A

For percentage categories

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9
Q

Bar chart

A

Bars decrease in height from left to right

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10
Q

Contingency table

A

Each cell of the table gives the count for a combination of values of the two variables

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11
Q

Independence

A

Tells us weather there is an association btw these variables

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12
Q

Distribution

A

How are the numbers spread out? Where is the center?

Any repetition?

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13
Q

Histogram

A

The bars touch and the height shows frequency.

Bin width is how thick one of the bars is

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14
Q

Stem and leaf plot

A
  • Good for small data sets
  • still shows relative shape
  • maintains data
  • always make a key
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15
Q

Dot plots

A

Good for integer data and small data sets

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16
Q

Describing the distribution using CUSS

A

C-center
U-unusual:any outliers or gaps
S-shape
S-spread (I️f all you have is the graph say the range)

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17
Q

Unimodal and symmetric

A

One tallest bar, generally symmetric shape

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18
Q

Skewed

A

Bars stretch out on to the side that is skewed

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19
Q

Uniform

A

All bars are generally the same height

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20
Q

Median

A
  • middle number
  • numbers need to be in order when finding median
  • 1 center number or average of two center numbers
  • not affected by outliers
  • good for skewed data
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21
Q

Mean

A
  • sum of #s divided my # of #s
  • affected by outliers
  • only use for unimodal and symmetric distributions
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22
Q

Mode

A

Most frequent number

Use term loosely

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23
Q

Range

A

Max#-min#

Very very biased

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24
Q

Interquartile range(IQR)

A

Q3-Q1

Unbiased

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25
Q

Standard deviation

A
  • always goes with mean
  • (add up all)•(X-Xbar)^2 all over (number of numbers)-1
  • or 1.5xIQR
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26
Q

5 number summary

A

Min, Q1, median, Q3, max

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27
Q

Time plots

A

What is the trend of the data, increase or decrease?

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28
Q

When adding constant

A
  • center increased by that amount

- the spread does not change

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29
Q

Z-scores formula

A

X-(mue)over O

Or X-xbar over s

Datum-mean over standard deviation

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30
Q

Z-scores

A

Is how many standard deviations from the mean it is

If z is less than -2 or greater than 2 u are unusual

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31
Q

Empirical rule

A

68%-95%-99.7%

68% fall in 1sd

95% fall in 2sd

And the rest in 99.7%

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32
Q

Normal model steps

A
  1. z-score
  2. draw man diagram with mean and a-score
  3. normalcdf and label
  4. answer to 4 decimal places
33
Q

DUFUS

A
  • direction(positive or neg slope)
  • form(linear,curve, quadratic)
  • unusual features(outliers,gaps)
  • strength(strong, moderate, weak)
34
Q

Correlation coefficient

A

Shown with r

35
Q

Y=ax+b or y-intercept

A

A-the intercept
B-is the slope
R^2-coefficient of determination
R-correlation coefficient

36
Q

Y in context

A

When y hat = zero what is a

37
Q

Slope in context

A

For every one y-hat b in predicted to increase by “n” amount

38
Q

R^2 in context

A
  • always start with “according to the model”

- what percent can be explained by the model

39
Q

R in context

A
  • start with “according to the model”

- for every one standard deviation you expect an approximate increase in “n” SD

40
Q

Residual

A

Actual-predicted

Y Y-hat

41
Q

Negative residual

A

The point is below the line

Also an over estimate

42
Q

Subsets

A

Breaking the data into manageable parts

43
Q

Extrapolation

A

When making a prediction outside the data collected

44
Q

Influential points

A

Outlier with leverage that is not near line of best fit, it does not change the slope

45
Q

Conclusion in context

A
  • start with according to my simulation

- I️ expect an average of “n” before something happens

46
Q

Undercoverage

A

Some ppl arnt included in the sample ( ppl that could have been included )

47
Q

Population

A

Everyone you want to be in your sample

48
Q

Non-response bias

A

Ppl just don’t answer/respond

49
Q

Response bias

A

When the response is not the real answer

-could be lying, question may be worded to bring in bias

50
Q

Convenience sample

A
  • Easy to get data
  • easy to be misrepresentative
  • bad
51
Q

Voluntary response

A
  • respond if u want
  • only ppl that feel strongly with respond
  • bad
52
Q

Simple random sample

A
  • Everyone is assigned a number randomly
  • use rnt/rng to select ppl
  • everyone has same chance of being selected
  • good
53
Q

Stratified sample

A
  • seperate into groups based off some characteristics

- then randomly sample in each group

54
Q

Cluster sample

A
  • randomly selecting one whole group

- often done geographically

55
Q

Systematic sample

A

Every nth person

56
Q

Single blind experiment

A

-participants don’t know which group is which

57
Q

Double blind experiment

A

-participants & assessor don’t know which group in which

58
Q

Placebo

A

Fake treatment

59
Q

Control group

A

No treatment, for comparison

60
Q

Random phenomena

A

We don’t have an amount

61
Q

Trail

A

EX roll of dice

62
Q

Outcome

A

What number comes up

63
Q

Event

A

An outcome or a combination of outcomes

64
Q

Sample space

A

A list of all possible outcomes

65
Q

Law of large numbers

A

As the number of trials grows, the outcomes become closer to theoretical probabilities

66
Q

Disjoint

A

Events are disjoint if they cannot happen at the same time

67
Q

Addition rule

A
  • or

- add probabilities together

68
Q

Event

A
  • and

- multiply them together

69
Q

Complement

A

Probability of event not happening

P(A) vs. P(notA)

70
Q

Disjoint

A

If there is a probability of having both then it can’t be disjoint

71
Q

P(x/given)

A

P(both/given)

72
Q

A random variable

A

Has a variety of numerical outcomes and we cannot predict those outcomes

73
Q

Expected amount/value

A

Just the mean

74
Q

Z scores

A 
X-m
  O 
X is value they are talking about
M is the mean 
O is sd
75
Q

How to find an outlier

A

Calculate IQR
1.5xIQR
Q3+IQR upper fence
Q1-IQR lower fence

76
Q

Leverage

A

On scatter plot a point that is in line with other points but either far right or far left

77
Q

Influential

A

Point is far left or right but also not in line with other points

78
Q

Confounding

A

Something that may have influenced results that was not an anticipated variable

Ap Stats (1 decks)

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