1. Chapter 6
Probability
PowerPoint Lecture Slides
Essentials of Statistics for the
Behavioral Sciences
Eighth Edition
by Frederick J. Gravetter and Larry B. Wallnau
2. Chapter 6 Learning Outcomes
• Understand definition of probability1
• Explain assumptions of random sampling2
• Use unit normal table to find probabilities3
• Use unit normal table to find scores for given proportion4
• Find percentiles and percentile rank in normal distribution5
3. Tools You Will Need
• Proportions (Math Review, Appendix A)
– Fractions
– Decimals
– Percentages
• Basic algebra (Math Review, Appendix A)
• z-scores (Chapter 5)
4. 6.1 Introduction to Probability
• Research begins with a question about an
entire population.
• Actual research is conducted using a
sample.
• Inferential statistics use sample data to
answer questions about the population
• Relationships between samples and
populations are defined in terms of
probability
6. Definition of Probability
• Several different outcomes are possible
• The probability of any specific outcome is
a fraction or proportion of all possible
outcomes
outcomespossibleofnumbertotal
Aasclassifiedoutcomesofnumber
Aofyprobabilit
7. Probability Notation
• p is the symbol for “probability”
• Probability of some specific outcome is
specified by p(event)
• So the probability of drawing a red ace
from a standard deck of playing cards
could be symbolized as p(red ace)
• Probabilities are always proportions
• p(red ace) = 2/52 ≈ 0.03846 (proportion is
2 red aces out of 52 cards)
8. (Independent)
Random Sampling
• A process or procedure used to draw
samples
• Required for our definition of probability to
be accurate
• The “Independent” modifier is generally
left off, so it becomes “random sampling”
9. Definition of Random Sample
• A sample produced by a process that
assures:
– Each individual in the population has an equal
chance of being selected
– Probability of being selected stays constant
from one selection to the next when more
than one individual is selected
• Requires sampling with replacement
10. Probability and
Frequency Distributions
• Probability usually involves population of
scores that can be displayed in a frequency
distribution graph
• Different portions of the graph represent
portions of the population
• Proportions and probabilities are equivalent
• A particular portion of the graph
corresponds to a particular probability in the
population
12. Learning Check
• A deck of 52 cards contains 12 royalty cards. If
you randomly select a card from the deck, what
is the probability of obtaining a royalty card?
• p = 1/52A
• p = 12/52B
• p = 3/52C
• p = 4/52D
13. Learning Check - Answer
• A deck of 52 cards contains 12 royalty cards. If
you randomly select a card from the deck, what
is the probability of obtaining a royalty card?
• p = 1/52A
• p = 12/52B
• p = 3/52C
• p = 4/52D
14. Learning Check TF
• Decide if each of the following statements
is True or False.
• Choosing random individuals who
walk by yields a random sampleT/F
• Probability predicts what kind of
population is likely to be obtainedT/F
15. Learning Check - Answers
• Not all individuals walk by, so not
all have an equal chance of being
selected for the sample
False
• The population is given.
Probability predicts what a sample
is likely to be like
False
16. 6.2 Probability and the
Normal Distribution
• Normal distribution is a common shape
– Symmetrical
– Highest frequency in the middle
– Frequencies taper off towards the extremes
• Defined by an equation
• Can be described by the proportions of
area contained in each section.
• z-scores are used to identify sections
19. Characteristics of the
Normal Distribution
• Sections on the left side of the distribution
have the same area as corresponding
sections on the right
• Because z-scores define the sections, the
proportions of area apply to any normal
distribution
– Regardless of the mean
– Regardless of the standard deviation
21. The Unit Normal Table
• The proportion for only a few z-scores can
be shown graphically
• The complete listing of z-scores and
proportions is provided in the unit normal
table
• Unit Normal Table is provided in Appendix
B, Table B.1
24. Probability/Proportion & z-scores
• Unit normal table lists relationships
between z-score locations and proportions
in a normal distribution
• If you know the z-score, you can look up
the corresponding proportion
• If you know the proportion, you can use
the table to find a specific z-score location
• Probability is equivalent to proportion
27. Learning Check
• Find the proportion of the normal curve
that corresponds to z > 1.50
• p = 0.9332A
• p = 0.5000B
• p = 0.4332C
• p = 0.0668D
28. Learning Check - Answer
• Find the proportion of the normal curve
that corresponds to z > 1.50
• p = 0.9332A
• p = 0.5000B
• p = 0.4332C
• p = 0.0668D
29. Learning Check
• Decide if each of the following statements
is True or False.
• For any negative z-score, the tail will
be on the right hand sideT/F
• If you know the probability, you can
find the corresponding z-scoreT/F
30. Learning Check - Answer
• For negative z-scores the tail will
always be on the left sideFalse
• First find the proportion in the
appropriate column then read the
z-score from the left column
True
31. 6.3 Probabilities/Proportions for
Normally Distributed Scores
• The probabilities given in the Unit Normal
Table will be accurate only for normally
distributed scores so the shape of the
distribution should be verified before using it.
• For normally distributed scores
– Transform the X scores (values) into z-scores
– Look up the proportions corresponding to the z-
score values.
34. Box 6.1 Percentile ranks
• Percentile rank is the percentage of
individuals in the distribution who have
scores that are less than or equal to the
specific score.
• Probability questions can be rephrased as
percentile rank questions.
39. Learning Check
• Membership in MENSA requires a score of 130 on
the Stanford-Binet 5 IQ test, which has μ = 100
and σ = 15. What proportion of the population
qualifies for MENSA?
• p = 0.0228A
• p = 0.9772B
• p = 0.4772C
• p = 0.0456D
40. Learning Check - Answer
• Membership in MENSA requires a score of 130 on
the Stanford-Binet 5 IQ test, which has μ = 100 and σ
= 15. What proportion of the population qualifies for
MENSA?
• p = 0.0228A
• p = 0.9772B
• p = 0.4772C
• p = 0.0456D
41. Learning Check
• Decide if each of the following statements
is True or False.
• It is possible to find the X score
corresponding to a percentile rank in
a normal distribution
T/F
• If you know a z-score you can find
the probability of obtaining that z-
score in a distribution of any shape
T/F
42. Learning Check - Answer
• Find the z-score for the percentile
rank, then transform it to XTrue
• If a distribution is skewed the
probability shown in the unit
normal table will not be accurate
False
43. 6.4 Looking Ahead to
Inferential Statistics
• Many research situations begin with a
population that forms a normal distribution
• A random sample is selected and receives a
treatment, to evaluate the treatment
• Probability is used to decide whether the
treated sample is “noticeably different” from
the population
FIGURE 6.1 The role of probability in inferential statistics. Probability is used to predict what kind of samples are likely to be obtained from a population. Thus probability establishes a connection between samples and populations. Inferential statistics rely on this connection when they use sample data as the basis for making conclusions about populations.
FIGURE 6.2 A frequency distribution histogram for a population that consists of N = 10 scores. The shaded part of the figure indicates the portion of the whole population that corresponds to scores greater than X = 4. The shaded portion is two-tenths (p = 2/10) of the whole distribution.
FIGURE 6.3 The normal distribution. The exact shape of the normal distribution is specified by an equation relating each X value (score) with each Y value (frequency). The equation is provided on the slide. (Pi and e are mathematical constants.) In simpler terms the normal distribution is symmetrical with a single mode in the middle. The frequency tapers off as you move farther from the middle in either direction.
FIGURE 6.4 The normal distribution following a z-score transformation.
FIGURE 6.5 The distribution of SAT scores described in Example 6.2.
FIGURE 6.6 A portion of the unit normal table. This table lists proportions of the normal distribution corresponding to each z-score value. Column A of the table lists z-scores. Column B lists the proportion in the body of the normal distribution up to the z-score value. Column C lists the proportion of the normal distribution that is located in the tail of the distribution beyond the z-score value. Column D lists the proportion between the mean and the z-score value.
FIGURE 6.7 Proportions of a normal distribution corresponding to z = +0.25 (a) and -0.25 (b).
FIGURE 6.8 The distribution for Example 6.3a—6.3c
FIGURE 6.9 The distributions for Examples 6.4a and 6.4b.
FIGURE 6.10 The distribution of IQ scores. The problem is to find the probability or proportion of the distribution corresponding to scores less than 120.
FIGURE 6.11 The distribution for Example 6.6.
FIGURE 6.12 The distribution for Example 6.7.
FIGURE 6.13 Determining probabilities of proportions for a normal distribution is shown as a two-step process with z-scores as an intermediate stop along the way. Note that you cannot move directly along the dashed line between X values and probabilities or proportions. Instead, you must follow the solid lines around the corner.
FIGURE 6.14 The distribution of commuting time for American workers. The problem is to find the score that separates the highest 10% of commuting times from the rest.
FIGURE 6.15 The distribution of commuting times for American workers. The problem is to find the middle 90% of the distribution.
FIGURE 6.16 A diagram of a research study. A sample is selected from the populations and receives a treatment. The goal is to determine whether the treatment has an effect.
FIGURE 6.17 Using probability to evaluate a treatment effect. Values that are extremely unlikely to be obtained form the original population are viewed as evidence of a treatment effect.
FIGURE 6.18 A sketch of the distribution for Demonstration 6.1.