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AP STATS EXAM REVIEW
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Chapter 2Chapter 6Chapter 5Chapter 3 and
Chapter 4Chapter 1
These are the three terms
you should always discuss
when describing a set of
dataCategories
Categories
Shape, center, spread
These four graphs may only be used
for quantitative data
Categories
Categories
Stemplot, boxplot, histogram, and
dotplot
This distribution shape has the mean
greater than the median
Categories
Categories
Skewed right
This is the formula for finding outliers
in a set of data
Categories
Chapter 1 400 Points
Categories
Q1 -1.5IQR and Q3 + 1.5IQR
Chapter 1 400 Points
the formula for this measurement that is used to
describe a set of data is to subtract the mean from
each of the numbers in the data set, square that
difference, find the sum of the differences, and
then take the square root of the sums
Categories
Chapter 1 500 Points
Categories
Standard deviation
Chapter 1 500 Points
This is what the 95 means in the 68-
95-99.7 rule
Categories
Chapter 2 100 Points
Chapter 2 100 Points
Categories
95% of the data is within 2 standard
deviations
Chapter 2 200 Points
this is the formula for the z score of a
mean
Categories
Categories
(x-bar – mean)/standard devation
Chapter 2 200 Points
Chapter 2 300 Points
This is the area to the left of a z-score
of 2.34
Categories
Chapter 2 300 Points
Categories
Probability for a two sided Z-score is
13.1%, this is the z-score
Categories
Chapter 2 400 Points
Categories
1.52
Chapter 2 400 Points
In 2000, the scores of men on the math
SAT followed a normal distribution with
mean 533 and standard deviation 115.
This is the percentage of men who scored
750 or betterCategories
Chapter 2 500 Points
Categories
2.94%
Chapter 2 500 Points
This is the equation for the LSRL
Categories
Chapter 3/4 100 Points
Chapter ¾ 100 Points
Categories
Yhat = a + bx
Chapter 3/4 200 Points
This point is on all LSRL
Categories
Categories
(xbar, ybar)
Chapter 3/4 200 Points
Chapter 3/4 300 Points
This is the formula for slope
Categories
Chapter 3/4 300 Points
Categories
B = r(sy/sx)
Formula for a residual
Categories
Chapter 3/4 400 Points
Categories
Observed – predicated (y – yhat)
Chapter 3/4 400 Points
This transformation uses the log of the
y’s
Categories
Chapter 3/4500 Points
Categories
exponential
Chapter 3/4 500 Points
A deliberate grouping of subjects in an
experiment based on a characteristic
that you suspect will affect responses
to treatments in a systematic wayCategories
Chapter 5 100 Points
Chapter 5 100 Points
Categories
blocking
Chapter 5 200 Points
Term that refers to the fact that neither
the subjects nor experimenters know
who is receiving what treatment
Categories
Categories
double blind
Chapter 5 200 Points
Chapter 5 300 Points
A variable that is not able to be
separated from the two variables being
studied
Categories
Chapter 5 300 Points
Categories
confounding
Term that has same meaning as
blocking, but is used in a survey, not
an experiment
Categories
Chapter 5 400 Points
Categories
Stratifying
Chapter 5 400 Points
Well-designed experiments have these
three principles
Categories
Chapter 5 500 Points
Categories
Control, randomization, replication
Chapter 5 500 Points
P(A intersection B) = 0 is this property
Categories
Chapter 6 100 Points
Chapter 6 100 Points
Categories
Mutually exclusive
Chapter 6 200 Points
This means that the occurrence or non-
occurrence of one event does not
effect the probability that the other
event occursCategories
Categories
Independent
Chapter 6 200 Points
Chapter 6 300 Points
Formula for the union of two events
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Chapter 6 300 Points
Categories
p(A B) = P(A) + P(B) – P(AB)
Two alternate approaches to finding
probability
Categories
Chapter 6 400 Points
Categories
Tree Diagrams or Venn Diagrams
Chapter 6 400 Points
An event A will occur with probability
0.5. An event B will occur with
probability 0.6. The probability that
both A and B will occur is 0.1. This is
the probability of A given BCategories
Chapter 6 500 Points
Categories
1/6 or 16.7%
Chapter 6 500 Points
The Daily Double
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