AP Statistics / Mr. Hansen
5/17/1999 (rev. 9/22/2000, 2/3/2003)
TI-83 Function Summary
You may not need to memorize the syntax shown below, since Bob Jeffrey has written a great program to prompt you for all the inputs, but you still need to know the purpose and assumptions involved in each of these.
|
Function name |
What it gives you |
Arguments [square brackets denote optional arguments] |
Comments |
|
normalpdf |
Height of the probability curve at a data point (x) |
x [, mean , s.d.]If mean and s.d. are omitted, they are assumed to be 0 and 1. |
Note that s.d. does not necessarily mean s. For a sampling distribution of xbar (a very common situation), you’d punch in s/Ön for s.d. For the normal approx. to a binomially distributed variable, you’d punch in Ö(npq) for s.d. |
|
normalcdf |
Cumulative area between two points |
start, end [, mean , s.d. ] |
Same comments as for normalpdf. |
|
invNorm |
The z score (or, if you specify mean and s.d., any data value) that has the area you specify to the left of it. The area starts from –¥ and ends at the answer that this function returns. |
area [, mean , s.d. ] |
For example, enter invNorm(.975) to find the upper z critical value for a 95% confidence interval. |
|
tpdf |
Height of the t distribution at a data point (x) |
x , df |
Rarely used. |
|
tcdf |
Cumulative area under the t distribution |
start , end , df |
Since we are usually computing tail probabilities, "end" is nearly always 99999. |
|
PRGM INVT |
The t score required to give a certain cumulative area (starting from –¥ ) |
Menu-driven (this is a program we wrote in class). |
WARNING: Some versions of this program only display the result without storing it into Ans, so if you immediately start doing computations without retyping, you will get wrong results. |
|
c2pdf |
Height of the chi-square distribution at a data point (x) |
x , df |
Rarely used. |
|
c2cdf |
Cumulative area under the chi-square distribution |
start , end , df |
Since we are usually computing tail probabilities, "end" is nearly always 99999. |
|
binompdf |
Height of the binomial distribution at a point (i.e., the probability of getting exactly k successes in n trials) |
n , p , k(think of as n, p, "IS") |
|
|
binomcdf |
Cumulative binomial probability of getting 0 through "goesthrough" successes in n trials |
n , p , goesthrough |
TI-83 always calculates inclusive left-tail probability. If this is not what you need, draw a picture and figure out how to adjust to get what you need. |
|
geometpdf |
Probability of having first success on trial #k (where trials are binomial-style, indep.) |
p , k |
|
|
geometcdf |
Probability of having first success on or before trial #k |
p , k |
This is inclusive left-tail probability. Because of the shortcut formula (see p.442, or better yet, make a simple tree diagram) that gives P(X > k) = qk, we could also compute geometcdf(p, k) simply by keying in 1 – qk. |