HOW TO USE YOUR TI BA II PLUS CALCULATOR
©2003 Schweser Study Program
8
As a check of the relationship between [LN] and [e
x
], press {-1.0536}→[2
nd
]→[e
x
].
The result is 0.90.
More precisely, e
ln(x)
= x, and, ln(e
x
) = x
D. Your TI-BA II Plus Statistical Functions (use at your own risk).
Understanding the previous sections of this document is critical to your success on the
exam. What follows are some cool short cuts you can take to calculate the mean and
variance of a small data set. Please beware, that in many cases, doing these computations
by brute force is sometimes quicker. If you feel you’ll have a hard time memorizing
these keystrokes for the exam, don’t sweat it – focus on the actual formulas and basic
calculations. In other words, don’t get fancy – it could backfire!
As with the IRR and NPV calculations, to use the data functions in your TI-BA II Plus,
you must first familiarize yourself with the up and down arrows (↑↓) at the top of the
keyboard. These keys will help you navigate your way through the data entry process.
To enter a data series into your BAII Plus, press [2
nd
] →[DATA]. Notice that you can
enter both X and Y coordinates (you can actually perform a simple linear regression on
your calculator!). If you just have one data series (X), you will simply press the down
arrow through the prompts for Y data values. Notice that X and Y both begin at X (01)
and Y (01) respectively, and that [X (01), Y (01)] represents one X, Y coordinate pair.
Example: You have been given the following observations that measure the speed of
randomly selected vehicles as they pass a particular checkpoint.
30, 42, 32, 35, 28
Compute the mean (
), population variance, and sample variance for this data set.
Step 1: Enter the data: [2
nd
]→[DATA]
X (01) {30}→[ENTER]→[↓]→[↓]
X (02) {42}→[ENTER]→[↓]→[↓]
X (03) {32}→[ENTER]→[↓]→[↓]
X (04) {35}→[ENTER]→[↓]→[↓]
X (05) {28}→[ENTER]→
Step 2: Calculate the statistics: [2
nd
]→ [STAT]→ [↓]→[↓]
= 33.4
[↓] = Sx = sample standard deviation = 5.459
[↓] = σ
x
= population standard deviation = 4.883