Ap Stat Midterm

Front 1

barchart vs. histogram

Back 1

barchart- categorical
histogram- quantitative

Front 2

relative

Back 2

comparison
(frequency)

Front 3

median

Back 3

goes with IQR and Range

Front 4

mean

Back 4

goes with standard deviation

Front 5

£(x-xbar)=

Back 5

0
in mean problem, all deviations from the mean added together equals 0

Front 6

Sx

Back 6

the average distance from the average

Front 7

what happens to the standard deviation depending on normalicy?

Back 7

Sx is smaller

Front 8

stem and leaf

Back 8

MAKE A KEY

Front 9

wealel words

Back 9

all other things being equal

Front 10

resistant

Back 10

data is resistand if they are not dramatically affected by outliers

Front 11

non resistant things

Back 11

the mean
standard deviation
range

Front 12

resistant things

Back 12

median
IQR

Front 13

Cheby Chev

Back 13

rule of thumb for determining the minimum % of data within K standard deviations
0%
75%
89%
RANGE/6

Front 14

normal percentage with in three standard deviations

Back 14

68
96
99.8

Front 15

uniform % within in 3 standard deviations

Back 15

58
100
100

Front 16

what happens to mean and median when each data point is added to or subtracted to by the same number

Back 16

both go up or down by that specific number

Front 17

what happens to spread when each number is added or subtracted

Back 17

stays the same

Front 18

every data value is multiplied/divided what happens to mean/median?

Back 18

multiplied or divided by same number

Front 19

what happens to spread when each value is multiplied/divided?

Back 19

spread multiplied/divided too

Front 20

normal model is useful for distributions whose shapes are...

Back 20

unimodal and rougly symetric

Front 21

empiracal rule

Back 21

68
95
99.7

Front 22

to standardize sample: equation

Back 22

z=x-x(bar)
----------------
s

Front 23

to standardize population formula?

Back 23

z=x-u
-----------
o-

Front 24

roll 2 daice 120 times and make a histogram of the sums

Back 24

L1 RandInt (1,6,120)
L2 RandInt(1,6,120)
L3=L1+L2

Front 25

what to describe about scatter plots

Back 25

direction
form
strength

Front 26

correlation

Back 26

-r is a number that measures how strong of a LINEAR relationship exists between the variables
-strenghts and direction
-proximity of points to a line
-non resistant
-no units
-sane if x and y are swapped

Front 27

residual

Back 27

-y-yhat
-positive if above LSLR
-negative if below LSLR
-tells how far away a point is in the y direction

Front 28

how to interpret slope

Back 28

the model suggests that for each increase of one hour studied grade increases by 10 points

Front 29

how to interpret y intercept

Back 29

the model suggests that if you do not study at all you will get a 59

Front 30

how to interpret y intercept

Back 30

the model suggests that if you do not study at all you will get a 59

Front 31

E(y-ybar)

Back 31

residuals
equals 0

Front 32

what are you looking for in residual?

Back 32

random scattering of points around LSRL

Front 33

coefficient of determimation

Back 33

r^2
the percent of variation in y that is explained by x

Front 34

if the residual plot has increased spread?

Back 34

the model appears to be more accurate for smaller values of x

Front 35

mean of residuals

Back 35

0

Front 36

when to use three equations in left side of green sheet

Back 36

when no data is given
print out given

Front 37

test to know if exponential is approriate

Back 37

first check residuals
then yn
----
yn-1