Calculating Probabilities Based on a Saint Index survey, assume that when adults are asked to identify the most unpopular projects for their hometown, 54% include WalMart among their choices. Suppose we want to find the probability that when five adults are randomly selected, exactly two of them include WalMart. What is wrong with using the multiplication rule to find the probability of getting two adults who include WalMart followed by three people who do not include WalMart, as in this calculation: (0.54)(0.54)(0.46)(0.46)(0.46)?
Read moreTable of Contents
cc
1
Introduction to Statistics
1-2
Statistical and Critical Thinking
1-3
Types of Data
1-4
Collecting Sample Data
1.2
Statistical and Critical Thinking
1.3
Types of Data
1.4
Collecting Sample Data
2
Summarizing and Graphing
2-2
Frequency Distributions
2-3
Histograms
2-4
Graphs That Enlighten and Graphs That Deceive
2.2
Frequency Distributions
2.3
Histograms
2.4
Graphs That Enlighten and Graphs That Deceive
3
Statistics for Describing, Exploring, and Comparing Data
3-2
Measures of Center
3-3
Measures of Variation
3-4
Measures of Relative Standing and Boxplots
3.2
Measures of Center
3.3
Measures of Variation
3.4
Measures of Relative Standing and Boxplots
4
Probability
4-2
Basic Concepts of Probability
4-3
Addition Rule
4-4
Multiplication Rule: Basics
4-5
Multiplication Rule: Complements and Conditional Probability
4-6
Counting
4.2
Basic Concepts of Probability
4.3
Addition Rule
4.4
Multiplication Rule: Basics
4.5
Multiplication Rule: Complements and Conditional Probability
4.6
Counting
4.7
Probabilities Through Simulations (on CD-ROM)
4.8
Bayes' Theorem (on CD-ROM)
5
Discrete Probability Distributions
5-2
Probability Distributions
5-3
Binomial Probability Distributions
5-4
Parameters for Binomial Distributions
5-5
Poisson Probability Distributions
5.2
Probability Distributions
5.3
Binomial Probability Distributions
5.4
Parameters for Binomial Distributions
5.5
Poisson Probability Distributions
6
Normal Probability Distributions
6-2
The Standard Normal Distribution
6-3
Applications of Normal Distributions
6-4
Sampling Distributions and Estimators
6-5
The Central Limit Theorem
6-6
Assessing Normality
6-7
Normal as Approximation to Binomial
6.2
The Standard Normal Distribution
6.3
Applications of Normal Distributions
6.4
Sampling Distributions and Estimators
6.5
The Central Limit Theorem
6.6
Assessing Normality
6.7
Normal as Approximation to Binomial
7
Estimates and Sample Sizes
7-2
Estimating a Population Proportion
7-3
Estimating a Population Mean
7-4
Estimating a Population Standard Deviation or Variance
7.2
Estimating a Population Proportion
7.3
Estimating a Population Mean
7.4
Estimating a Population Standard Deviation or Variance
8
Hypothesis Testing
8-2
Basics of Hypothesis Testing
8-3
Testing a Claim About a Proportion
8-4
Testing a Claim About a Mean
8-5
Testing a Claim About a Standard Deviation or Variance
8.2
Basics of Hypothesis Testing
8.3
Testing a Claim About a Proportion
8.4
Testing a Claim About a Mean
8.5
Testing a Claim About a Standard Deviation or Variance
9
Inferences from Two Samples
9-2
Two Proportions
9-3
Two Means: Independent Samples
9-4
Two Dependent Samples (Matched Pairs)
9-5
Two Variances or Standard Deviations
9.2
Two Proportions
9.3
Two Means: Independent Samples
9.4
Two Dependent Samples (Matched Pairs)
9.5
Two Variances or Standard Deviations
10
Correlation and Regression
10-2
Correlation
10-3
Regression
10-4
Prediction Intervals and Variation
10-5
Multiple Regression
10-6
Nonlinear Regression
10.2
Correlation
10.3
Regression
10.4
Prediction Intervals and Variation
10.5
Multiple Regression
10.6
Nonlinear Regression
11
Goodness-of-Fit and Contingency Tables
11-2
Goodness-of-Fit
11-3
Contingency Tables
11.2
Goodness-of-Fit
11.3
Contingency Tables
12
Analysis of Variance
12-2
One-Way ANOVA
12-3
Two-Way ANOVA
12.2
One-Way ANOVA
12.3
Two-Way ANOVA
13
Nonparametric Tests
13-3
Wilcoxon Signed-Ranks Test for Matched Pairs
13-4
Wilcoxon Rank-Sum Test for Two Independent Samples
13-5
Kruskal-Wallis Test
13-6
Rank Correlation
13-7
Runs Test for Randomness
13.2
Sign Test
13.2
Sign Test
13.3
Wilcoxon Signed-Ranks Test for Matched Pairs
13.4
Wilcoxon Rank-Sum Test for Two Independent Samples
13.5
Kruskal-Wallis Test
13.6
Rank Correlation
13.7
Runs Test for Randomness
14
Statistical Process Control
14-2
Control Charts for Variation and Mean
14-3
Control Charts for Attributes
14.2
Control Charts for Variation and Mean
14.3
Control Charts for Attributes
Textbook Solutions for Elementary Statistics
Chapter 5-3 Problem 22
Question
Using Technology or the Binomial Probability Formula. In Exercises 2124, assume that when blood donors are randomly selected, 45% of them have blood that is Group O (based on data from the Greater New York Blood Program). If the number of blood donors is n = 16 , find the probability that the number with Group O blood is x = 6 .
Solution
Step 1 of 2
Given:
The number of blood donors is .
The probability that the blood donors have blood that is Group O is .
Subscribe to view the
full solution
full solution
Title
Elementary Statistics 12
Author
Mario F. Triola
ISBN
9780321836960