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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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52 CHAPTER 2 | Frequency Distributions

percentages that appear in the table. Using the table in Example 2.7, for example, you

should be able to answer the following questions:

1. What is the 95th percentile? (Answer: X = 4.5.)

2. What is the percentile rank for X = 3.5? (Answer: 70%.)

However, there are many values that do not appear directly in the table, and it is impossible

to determine these values precisely. Referring to the table in Example 2.7 again,

1. What is the 50th percentile?

2. What is the percentile rank for X = 4?

Because these values are not specifically reported in the table, you cannot answer the

questions. However, it is possible to estimate these intermediate values by using a procedure

known as interpolation.

Before we apply the process of interpolation to percentiles and percentile ranks, we will

use a simple, commonsense example to introduce this method. Suppose that your friend

offers you $60 to work for 8 hours on Saturday helping with spring cleaning in the house

and yard. On Saturday morning, however, you realize that you have an appointment in the

afternoon and will have to quit working after only 4 hours. What is a fair amount for your

friend to pay you for 6 hours of work? Because this is a working-for-pay example, your

automatic response probably is to calculate the hourly rate of pay —how many dollars per

hour you are getting. However, the process of interpolation offers an alternative method for

finding the answer. We begin by noting that the original total amount of time was 8 hours.

You worked 4 hours, which corresponds to 1 2 of the total time. Therefore, a fair payment

would be 1 2 of the original total amount: 1 2 of $60 is $30.

The process of interpolation is pictured in Figure 2.13. In the figure, the line on the left

shows the time for your agreed work, from 0 up to 8 hours, and the line on the right shows

the agreed pay, from 0 to $60. We also have marked different fractions along the way.

Using the figure, try answering the following questions about time and pay.

1. How long should you work to earn $45?

2. How much should you be paid after working 2 hours?

If you got answers of 6 hours and $15, you have mastered the process of

interpolation.

Notice that interpolation provides a method for finding intermediate values—that is,

values that are located between two specified numbers. This is exactly the problem we

faced with percentiles and percentile ranks. Some values are given in the table, but others

are not. Also notice that interpolation only estimates the intermediate values. The basic

assumption underlying interpolation is that there is a constant rate of change from one end

of the interval to the other. In the working-for-pay example, we assume a constant rate of

pay for the entire job. Because interpolation is based on this assumption, the values we

calculate are only estimates. The general process of interpolation can be summarized as

follows:

1. A single interval is measured on two separate scales (for example, time and dollars).

The endpoints of the interval are known for each scale.

2. You are given an intermediate value on one of the scales. The problem is to find the

corresponding intermediate value on the other scale.

3. The interpolation process requires four steps:

a. Find the width of the interval on both scales.

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