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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 3.2 | The Mean 73

the distribution in Figure 3.3, for example, what would happen to the mean (balance point)

if a new score were added at X = 10?

■ The Weighted Mean

Often it is necessary to combine two sets of scores and then find the overall mean for the

combined group. Suppose, for example, that we begin with two separate samples. The first

sample has n = 12 scores and a mean of M = 6. The second sample has n = 8 and M = 7.

If the two samples are combined, what is the mean for the total group?

To calculate the overall mean, we need two values:

1. the overall sum of the scores for the combined group (SX), and

2. the total number of scores in the combined group (n).

The total number of scores in the combined group can be found easily by adding the

number of scores in the first sample (n 1

) and the number in the second sample (n 2

). In this

case, there are 12 scores in the first sample and 8 in the second, for a total of 12 1 8 = 20

scores in the combined group. Similarly, the overall sum for the combined group can be

found by adding the sum for the first sample (SX 1

) and the sum for the second sample

(SX 2

). With these two values, we can compute the mean using the basic equation

SX soverall sum for the combined groupd

overall mean 5 M 5

n stotal number in the combined groupd

5 SX 1 1SX 2

n 1

1 n 2

To find the sum of the scores for each sample, remember that the mean can be defined as

the amount each person receives when the total (SX) is distributed equally. The first sample

has n = 12 and M = 6. (Expressed in dollars instead of scores, this sample has n = 12 people

and each person gets $6 when the total is divided equally.) For each of 12 people to get

M = 6, the total must be SX = 12 × 6 = 72. In the same way, the second sample has n = 8

and M = 7 so the total must be SX = 8 × 7 = 56. Using these values, we obtain an overall

mean of

overall mean 5 M 5 SX 1SX 1 2 72 1 56

5

n 1

1 n 2

12 1 8 5 128

20 5 6.4

The following table summarizes the calculations.

First Sample Second Sample Combined Sample

n 5 12 n 5 8 n 5 20 (12 + 8)

SX 5 72 SX 5 56 SX 5 128 (72 + 56)

M 5 6 M 5 7 M 5 6.4

Note that the overall mean is not halfway between the original two sample means.

Because the samples are not the same size, one makes a larger contribution to the total

group and therefore carries more weight in determining the overall mean. For this reason,

the overall mean we have calculated is called the weighted mean. In this example, the

overall mean of M = 6.4 is closer to the value of M = 6 (the larger sample) than it is to

M = 7 (the smaller sample). An alternative method for finding the weighted mean is

presented in Box 3.1.

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