HP 10bII+ Financial \h\«, \e\«, JdDÆd:¡, JgGÆgJ¡, JjjÆgD¡, JgVÆjj¡

The standard deviations calculated by \hand \h\«are the sample standard deviations. They assume that the data is a sampling of a larger, complete set of data.

If the data constitutes the entire population, the true population standard deviations can be calculated by pressing \eand \e\«.

Example 3

The coach has four new players on the team with heights of 193, 182, 177, and 185 centimeters and weights of 90, 81, 83, and 77 kilograms. Find the mean and population standard deviation of both their heights and weights, then sum the y-data.

Table 12-8 Example 3

KeysDisplay Description

\t	STAT CLR	Clears statistics memory.
	(message flashes briefly,
	then disappears)
JdDÆd:¡		player 1.
	1.00	Enters height and weight of
JgGÆgJ¡		player 2.
	2.00	Enters height and weight of
JjjÆgD¡		player 3.
	3.00	Enters height and weight of
JgVÆjj¡		player 4.
	4.00	Enters height and weight of
\k	184.25	Calculates mean of heights (x).
\«	82.75	Displays mean of weights (y).
\e	5.80	Calculates population standard
		deviation for heights (x).
\«	4.71	Displays population standard
		deviation for weights (y).
]U	331.00	Displays the total of the y -values.

Linear Regression, Estimation, and Regression Modes

Linear regression is a statistical method for estimation and forecasting. It is used to find a straight line that best fits a set of x,y data. There must be at least two different x,y pairs. The straight line provides a relationship between the x- and y-variables: y = mx + b, where m is the slope and b is the y-intercept.

Statistical Calculations 121