HP 35s, Руководство пользователя

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Statistics Programs
16-11
Example 2:
Repeat example 1 (using the same data) for logarithmic, exponential, and power
curve fits. The table below gives you the starting execution label and the results (the
correlation and regression coefficients and the
x – and y – estimates) for each type of
curve. You will need to reenter the data values each time you run the program for a
different curve fit.
Normal and Inverse–Normal Distributions
Normal distribution is frequently used to model the behavior of random variation
about a mean. This model assumes that the sample distribution is symmetric about
the mean,
M, with a standard deviation, S , and approximates the shape of the bell–
shaped curve shown below. Given a value x , this program calculates the probability
that a random selection from the sample data will have a higher value. This is
known as the upper tail area,
Q(x) . This program also provides the inverse: given a
value Q(x) , the program calculates the corresponding value x .
 

Calculates regression coefficient B .
 

Calculates regression coefficient M.
 

Prompts for hypothetical x –value.
 

Stores 37 in X and calculates .
 

Stores 101 in Y and calculates .
Logarithmic Exponential Power
To start:
 L   E   P 
R 0.9965 0.9945 0.9959
B –139.0088 51.1312 8.9730
M 65.8446 0.0177 0.6640
Y ( when X =37)
98.7508 98.5870 98.6845
X ( when Y =101)
38.2857 38.3628 38.3151
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