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Statistics for the Behavioral Sciences by Frederick J. Gravetter, Larry B. Wallnau ISBN 10: 1305504917 ISBN 13: 9781305504912

Statistics is one of the most practical and essential courses that you will take, and a primary goal of this popular text is to make the task of learning statistics as simple as possible. Straightforward instruction, built-in learning aids, and real-world examples have made STATISTICS FOR THE BEHAVIORAL SCIENCES, 10th Edition the text selected most often by instructors for their students in the behavioral and social sciences. The authors provide a conceptual context that makes it easier to learn formulas and procedures, explaining why procedures were developed and when they should be used. This text will also instill the basic principles of objectivity and logic that are essential for science and valuable in everyday life, making it a useful reference long after you complete the course.

Statistics is one of the most practical and essential courses that you will take, and a primary goal of this popular text is to make the task of learning statistics as simple as possible. Straightforward instruction, built-in learning aids, and real-world examples have made STATISTICS FOR THE BEHAVIORAL SCIENCES, 10th Edition the text selected most often by instructors for their students in the behavioral and social sciences. The authors provide a conceptual context that makes it easier to learn formulas and procedures, explaining why procedures were developed and when they should be used. This text will also instill the basic principles of objectivity and logic that are essential for science and valuable in everyday life, making it a useful reference long after you complete the course.

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SECTION 4.3 | Measuring Variance and Standard Deviation for a Population 109

You need to know two formulas to compute SS. These formulas are algebraically equivalent

(they always produce the same answer), but they look different and are used in different

situations.

The first of these formulas is called the definitional formula because the symbols in the

formula literally define the process of adding up the squared deviations:

Definitional formula: SS 5 S(X 2 µ) 2 (4.1)

To find the sum of the squared deviations, the formula instructs you to perform the following

sequence of calculations:

1. Find each deviation score (X 2 m).

2. Square each deviation score, (X 2 m) 2 .

3. Add the squared deviations.

The result is SS, the sum of the squared deviations. The following example demonstrates

using this formula.

EXAMPLE 4.4

We will compute SS for the following set of N 5 4 scores. These scores have a sum of

SX 5 8, so the mean is m 5 8 4 5 2. The following table shows the deviation and the squared

deviation for each score. The sum of the squared deviation is SS 5 22.

Score

X

Deviation

X 2 m

Squared

Deviation

(X 2 m) 2

1 21 1 S X 5 8

0 22 4 m 5 2

6 14 16

1 21 1

22 S(X 2 m) 2 5 22

Although the definitional formula is the most direct method for computing SS, it can

be awkward to use. In particular, when the mean is not a whole number, the deviations all

contain decimals or fractions, and the calculations become difficult. In addition, calculations

with decimal values introduce the opportunity for rounding error, which can make the result

less accurate. For these reasons, an alternative formula has been developed for computing SS.

The alternative, known as the computational formula, performs calculations with the scores

(not the deviations) and therefore minimizes the complications of decimals and fractions.

Computational formula: SS 5SX 2 2 sSXd2

N

(4.2)

The first part of this formula directs you to square each score and then add the squared

values, SX 2 . In the second part of the formula, you find the sum of the scores, SX, then

square this total and divide the result by N. Finally, subtract the second part from the first.

The use of this formula is shown in Example 4.5 with the same scores that we used to demonstrate

the definitional formula.

EXAMPLE 4.5

The computational formula is used to calculate SS for the same set of N 5 4 scores we used

in Example 4.4. Note that the formula requires the calculation of two sums: first, compute

SX, and then square each score and compute SX 2 . These calculations are shown in the

following table. The two sums are used in the formula to compute SS.

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