Ap Statistics Caluclator Use

Front 1

binomial cumulative probability

USE: looking for "less than" # of successes
-to model the number of successes in a sample of size n drawn with replacement

Back 1

2ND:DISTR:B:
binomcdf(number of trials,
probability[,successes])

Front 2

binomial probability

USE: computes equal to the # of successes

Back 2

2ND:DISTR:A:
binompdf(number of trials,
probability[,successes])

Front 3

chi-square cumulative distribution
function (area under the curve)

USE: computes the x^2-distribution probability between lowerbound and upperbound
for the specified interval and degrees of freedom.

Back 3

2ND :DISTR:DISTR 7: 
x^2cdf(lower bound,upper
bound,degrees of freedom)

NOTE: use for GOF tests

Front 4

chi-square probability density
function (also used in the Y menu
for graphing)

USE: computes the probability density function for the x^2 distribution at a specified x
with a specified number of degrees of freedom.

Back 4

2ND:DISTR:DISTR 8: 
x^2 pdf(x,degrees of freedom)


NOTE: you will rarely use this one.

Front 5

chi-square test of homogeneity or
independence (not goodness-of-fit)

Back 5

STAT:
TESTS C: 
x^2 -Test(

Front 6

combinations

USE: In combinations, order do not count.

Back 6

MATH:PRB:3: nCr

ex)If you have 30 people in a club and you wish to choose a 4 officers with equal rank, this would
be a combination of 30 things taken 4 at a time.
30 nPr 4 = 657,720

Front 7

confidence interval for a mean, σ known

USE:finds the confidence interval from a sample size n from an unknown population mean μ and known standard deviation σ.

Back 7

STAT:TESTS:7:Zinterval

Example: 150 light bulbs were tested. It was found that the mean life of the bulb was 58.2 hours with a standard deviation of 2.5 hours. If we assume that the population standard deviation is also 2.5 hours, find a 95% confidence interval for the life expectancy of the bulb.

Front 8

confidence interval for a mean, σ unknown

USE: finds the confidence interval from a sample size n from an unknown population mean μ and unknown standard deviation σ.

Back 8

STAT:TESTS:8:Tinterval

Front 9

confidence interval for a proportion

USE: You have a sample size of n and have x successes. You want to predict the proportion of success to an indicated level of confidence. We assume that the data is from an SRS, the population is at least 10 times the sample size, >10.

Back 9

STAT:TESTS A:1-PropZInt

Front 10

confidence interval for the difference
of two means, σ1 and σ2 known

USE:

Back 10

STAT:
TESTS 9:2-SampZInt

Front 11

confidence interval for the difference
of two means, σ1 and σ2 un known

Back 11

STAT:
TESTS 0:2-SampTInt

Front 12

confidence interval for the
difference of two proportions

Back 12

STAT:
TESTS B:2-PropZInt

Front 13

geometric cumulative probability

Back 13

2ND:
DISTR:E:geometcdf(probability,trial
of first success)

Front 14

least squares regression line

Back 14

STAT:
CALC 4:LinReg(a+bx)

Front 15

normal cumulative distribution
function (area under the curve)

Back 15

2ND:
DISTR:2:normalcdf(lower bound,
upper bound,[mean, standard
deviation])

Front 16

normal distribution, draw and
shade

Back 16

2ND:
DISTR:DRAW:1:ShadeNorm(lower bound,
upper bound[,mean, standard
deviation])

Front 17

normal distribution’s x-value or
z-score corresponding to a known area

Back 17

2ND:
DISTR:3:invNorm(area[,mean,
standard deviation]

Front 18

normal probability density function
(also used in the Y= menu for
graphing)

Back 18

2ND:
DISTR:1:normalpdf(x[,mean,
standard deviation])

Front 19

significance test for a mean, σ known

Back 19

STAT:
TESTS:1:Z-Test

Front 20

significance test for a mean, σ unknown

Back 20

STAT:
TESTS:2:T-Test

Front 21

significance test for a proportion

Back 21

STAT:
TESTS:5:1-PropZTest

Front 22

significance test for a slope

Back 22

STAT:
TESTS:E:LinRegTTest

Front 23

significance test for the difference of
two means, σ1 and σ2 known

Back 23

STAT:
TESTS 3:2-SampZTest

Front 24

significance test for the difference of
two means, σ1and σ2 unknown

Back 24

STAT:
TESTS 4:2-SampTTest

Front 25

significance test for the difference of
two proportions

Back 25

STAT:
TESTS 6:2-PropZTest

Front 26

summary statistics of a list or
frequency table

Back 26

STAT:
CALC 1:1-Var Stats

Front 27

The minimum, maximum, mean, median, standard deviation, and variance can also be individually calculated.

Back 27

2ND [LIST] MATH 1:min(list)
2ND [LIST] MATH 2:max(list)
2ND [LIST] MATH 3:mean(list[,frequency list])
2ND [LIST] MATH 4:median(list[,frequency list])
2ND [LIST] MATH 7:stdDev(list[,frequency list])
2ND [LIST] MATH 8:variance(list[,frequency list])

Front 28

summary statistics of two lists or
frequency tables

Back 28

STAT:
CALC:2:2-Var Stats

Front 29

t cumulative distribution function
(area under the curve)

Back 29

2ND:
DISTR5:tcdf(lower bound, upper
bound, degrees of freedom)

Front 30

t probability density function (also
used in the Y menu for graphing)

Back 30

2ND:
DISTR:4:tpdf(