HP 12C Platinum Owner's Handbook Manual page 78

80 Section 6: Statistics Functions
Example: Using the accumulated statistics from the preceding problem,
estimate the amount of sales delivered by a new salesperson working 48 hours
per week.
Keystrokes
48gQ
The reliability of a linear estimate depends upon how closely the data pairs
would, if plotted on a graph, lie in a straight line. The usual measure of this
reliability is the correlation coefficient, r. This quantity is automatically
calculated whenever or
y ˆ
coefficient close to 1 or –1 indicates that the data pairs lie very close to a straight
line. On the other hand, a correlation coefficient close to 0 indicates that the data
pairs do not lie closely to a straight line; and a linear estimate using this data
would not be very reliable.
Example: Check the reliability of the linear estimate in the preceding example
by displaying the correlation coefficient.
Keystrokes
~
To graph the regression line, calculate the coefficients of the linear equation
y = A + Bx.
1. Press 0gR to compute the y-intercept (A).
2. Press 1gR~d~- to compute the slope of the line (B).
Example: Compute the slope and intercept of the regression line in the
preceding example.
Keystrokes (RPN mode) Display
0gR
1 gR~d~-
The equation that describes the regression line is:
Display
Estimated sales for a 48 hour
28,818.93
workweek.
is calculated; to display it, press ~. A correlation
x ˆ
Display
The correlation coefficient is close
0.90
to 1, so the sales calculated in the
preceding example is a good
estimate.
y-intercept (A); projected value for
15.55
x = 0.
Slope of the line (B); indicates the
0.001
change in the projected values
caused by an incremental change in
the x value.
y = 15.55 + 0.001x