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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
Standard deviation
- always goes with mean - (add up all)•(X-Xbar)^2 all over (number of numbers)-1 - or 1.5xIQR
26
5 number summary
Min, Q1, median, Q3, max
27
Time plots
What is the trend of the data, increase or decrease?
28
When adding constant
- center increased by that amount | - the spread does not change
29
Z-scores formula
X-(mue)over O Or X-xbar over s Datum-mean over standard deviation
30
Z-scores
Is how many standard deviations from the mean it is | If z is less than -2 or greater than 2 u are unusual
31
Empirical rule
68%-95%-99.7% 68% fall in 1sd 95% fall in 2sd And the rest in 99.7%
32
Normal model steps
1. z-score 2. draw man diagram with mean and a-score 3. normalcdf and label 4. answer to 4 decimal places
33
DUFUS
- direction(positive or neg slope) - form(linear,curve, quadratic) - unusual features(outliers,gaps) - strength(strong, moderate, weak)
34
Correlation coefficient
Shown with r
35
Y=ax+b or y-intercept
A-the intercept B-is the slope R^2-coefficient of determination R-correlation coefficient
36
Y in context
When y hat = zero what is a
37
Slope in context
For every one y-hat b in predicted to increase by “n” amount
38
R^2 in context
- always start with “according to the model” | - what percent can be explained by the model
39
R in context
- start with “according to the model” | - for every one standard deviation you expect an approximate increase in “n” SD
40
Residual
Actual-predicted | Y Y-hat
41
Negative residual
The point is below the line | Also an over estimate
42
Subsets
Breaking the data into manageable parts
43
Extrapolation
When making a prediction outside the data collected
44
Influential points
Outlier with leverage that is not near line of best fit, it does not change the slope
45
Conclusion in context
- start with according to my simulation | - I️ expect an average of “n” before something happens
46
Undercoverage
Some ppl arnt included in the sample ( ppl that could have been included )
47
Population
Everyone you want to be in your sample
48
Non-response bias
Ppl just don’t answer/respond
49
Response bias
When the response is not the real answer | -could be lying, question may be worded to bring in bias
50
Convenience sample
- Easy to get data - easy to be misrepresentative - bad
51
Voluntary response
- respond if u want - only ppl that feel strongly with respond - bad
52
Simple random sample
- Everyone is assigned a number randomly - use rnt/rng to select ppl - everyone has same chance of being selected - good
53
Stratified sample
- seperate into groups based off some characteristics | - then randomly sample in each group
54
Cluster sample
- randomly selecting one whole group | - often done geographically
55
Systematic sample
Every nth person
56
Single blind experiment
-participants don’t know which group is which
57
Double blind experiment
-participants & assessor don’t know which group in which
58
Placebo
Fake treatment
59
Control group
No treatment, for comparison
60
Random phenomena
We don’t have an amount
61
Trail
EX roll of dice
62
Outcome
What number comes up
63
Event
An outcome or a combination of outcomes
64
Sample space
A list of all possible outcomes
65
Law of large numbers
As the number of trials grows, the outcomes become closer to theoretical probabilities
66
Disjoint
Events are disjoint if they cannot happen at the same time
67
Addition rule
- or | - add probabilities together
68
Event
- and | - multiply them together
69
Complement
Probability of event not happening | P(A) vs. P(notA)
70
Disjoint
If there is a probability of having both then it can’t be disjoint
71
P(x/given)
P(both/given)
72
A random variable
Has a variety of numerical outcomes and we cannot predict those outcomes
73
Expected amount/value
Just the mean
74
Z scores
``` X-m O X is value they are talking about M is the mean O is sd ```
75
How to find an outlier
Calculate IQR 1.5xIQR Q3+IQR upper fence Q1-IQR lower fence
76
Leverage
On scatter plot a point that is in line with other points but either far right or far left
77
Influential
Point is far left or right but also not in line with other points
78
Confounding
Something that may have influenced results that was not an anticipated variable

Ap Stats (1 decks)

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