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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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162 CHAPTER 6 | Probability

the probability problem “What is the probability of selecting a king from a deck of cards?”

can be restated as “What proportion of the whole deck consists of kings?” In each case,

the answer is 4

52 , or “4 out of 52.” This translation from probability to proportion may seem

trivial now, but it will be a great aid when the probability problems become more complex.

In most situations, we are concerned with the probability of obtaining a particular sample

from a population. The terminology of sample and population will not change the basic

definition of probability. For example, the whole deck of cards can be considered as a

population, and the single card we select is the sample.

Probability Values The definition we are using identifies probability as a fraction or a

proportion. If you work directly from this definition, the probability values you obtain are

expressed as fractions. For example, if you are selecting a card at random,

Or, if you are tossing a coin,

psspaded 5 13

52 5 1 4

psheadsd 5 1 2

If you are unsure how to

convert from fractions

to decimals or percentages,

you should review

the section on proportions

in the math review,

Appendix A.

You should be aware that these fractions can be expressed equally well as either decimals

or percentages:

p 5 1 5 0.25 5 25%

4

p 5 1 5 0.50 5 50%

2

By convention, probability values most often are expressed as decimal values. But you

should realize that any of these three forms is acceptable.

You also should note that all the possible probability values are contained in a limited

range. At one extreme, when an event never occurs, the probability is zero, or 0% (Box 6.1).

At the other extreme, when an event always occurs, the probability is 1, or 100%. Thus, all

probability values are contained in a range from 0–1. For example, suppose that you have

a jar containing 10 white marbles. The probability of randomly selecting a black marble is

The probability of selecting a white marble is

■ Random Sampling

psblackd 5 0 10 5 0

pswhited 5 10

10 5 1

For the preceding definition of probability to be accurate, it is necessary that the outcomes

be obtained by a process called random sampling.

DEFINITION

A random sample requires that each individual in the population has an equal

chance of being selected. A sample obtained by this process is called a simple

random sample.

A second requirement, necessary for many statistical formulas, states that if more than

one individual is being selected, the probabilities must stay constant from one selection

to the next. Adding this second requirement produces what is called independent random

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