Answer: Suppose that you read through this year’s issues | StudySoup
Probability and Statistics for Engineering and the Sciences | 9th Edition | ISBN: 9781305251809 | Authors: Jay L. Devore

Table of Contents

1
Supplementary Exercises
1.1
Populations, Samples, and Processes
1.2
Pictorial and Tabular Methods inDescriptive Statistics
1.3
Measures of Location
1.4
Measures of Variability

2
Supplementary Exercises
2.1
Sample Spaces and Events
2.2
Axioms, Interpretations, and Properties of Probability
2.3
Counting Techniques
2.4
Conditional Probability
2.5
Independence

3
Supplementary Exercises
3.1
Random Variables
3.2
Probability Distributions for Discrete Random Variables
3.3
Expected Values
3.4
The Binomial Probability Distribution
3.5
Hypergeometric and Negative Binomial Distributions
3.6
The Poisson Probability Distribution

4
Supplementary Exercises
4.1
Probability Density Functions
4.2
Cumulative Distribution Functions and Expected Values
4.3
The Normal Distribution
4.4
The Exponential and Gamma Distributions
4.5
Other Continuous Distributions
4.6
Probability Plots

5
Supplementary Exercises
5.1
Jointly Distributed Random Variables
5.2
Expected Values, Covariance, and Correlation
5.3
Statistics and Their Distributions
5.4
The Distribution of the Sample Mean
5.5
The Distribution of a Linear Combination

6
Supplementary Exercises
6.1
Some General Concepts of Point Estimation
6.2
Methods of Point Estimation

7
Supplementary Exercises
7.1
Basic Properties of Confidence Intervals
7.2
Large-Sample Confidence Intervals for a Population Mean and Proportion
7.3
Intervals Based on a Normal Population Distribution
7.4
Confidence Intervals for the Variance and Standard Deviation of a Normal Population

8
Supplementary Exercises
8.1
Hypotheses and Test Procedures
8.2
z Tests for Hypotheses about a Population Mean
8.3
The One-Sample t Test
8.4
Tests Concerning a Population Proportion
8.5
Further Aspects of Hypothesis Testing

9
Supplementary Exercises
9.1
z Tests and Confidence Intervals for a Difference Between Two Population Means
9.2
The Two-Sample t Test and Confidence Interval
9.3
Analysis of Paired Data
9.4
Inferences Concerning a Difference Between Population Proportions
9.5
Inferences Concerning Two Population Variances

10
Supplementary Exercises
10.1
Single-Factor ANOVA
10.2
Multiple Comparisons in ANOVA
10.3
More on Single-Factor ANOVA

11
Supplementary Exercises
11.1
Two-Factor ANOVA with Kij 5 1
11.2
Two-Factor ANOVA with Kij . 1
11.3
Three-Factor ANOVA
11.4
2p Factorial Experiments

12
Supplementary Exercises
12.1
The Simple Linear Regression Model
12.2
Estimating Model Parameters
12.3
Inferences About the Slope Parameter b1
12.4
Inferences Concerning mY ? x* and the Prediction of Future Y Values
12.5
Correlation

13
Supplementary Exercises
13.1
Assessing Model Adequacy
13.2
Regression with Transformed Variables
13.3
Polynomial Regression
13.4
Multiple Regression Analysis
13.5
Other Issues in Multiple Regression

14
Supplementary Exercises
14.1
Goodness-of-Fit Tests When Category Probabilities Are Completely Specified
14.2
Goodness-of-Fit Tests for Composite Hypotheses
14.3
Two-Way Contingency Tables

15
Supplementary Exercises
15.1
The Wilcoxon Signed-Rank Test
15.2
The Wilcoxon Rank-Sum Test
15.3
Distribution-Free Confidence Intervals
15.4
Distribution-Free ANOVA

16
Supplementary Exercises
16.1
General Comments on Control Charts
16.2
Control Charts for Process Location
16.3
Control Charts for Process Variation
16.4
Control Charts for Attributes
16.5
CUSUM Procedures
16.6
Acceptance Sampling

Textbook Solutions for Probability and Statistics for Engineering and the Sciences

Chapter 3 Problem 21E

Question

Problem 21E

Suppose that you read through this year’s issues of the New York Times and record each number that appears in a news article—the income of a CEO, the number of cases of wine produced by a winery, the total charitable contribution of a politician during the previous tax year, the age of a celebrity, and so on. Now focus on the leading digit of each number, which could be 1, 2, . . . , 8, or 9. Your first thought might be that the leading digit X of a randomly selected number would be equally likely to be one of the nine possibilities (a discrete uniform distribution). However, much empirical evidence as well as some theoretical arguments suggest an alternative probability distribution called Benford’s law:

a. Without computing individual probabilities from this formula, show that it specifies a legitimate pmf.

b. Now compute the individual probabilities and compare to the corresponding discrete uniform distribution.

c. Obtain the cdf of X.

d. Using the cdf, what is the probability that the leading digit is at most 3? At least 5?

[Note: Benford’s law is the basis for some auditing procedures used to detect fraud in financial reporting—for example, by the Internal Revenue Service.]

Solution

Problem 21E

Answer:

Step1:

We have Suppose that you read through this year’s issues of the New York Times and record each number that appears in a news article—the income of a CEO, the number of cases of wine produced by a winery, the total charitable contribution of a politician during the previous tax year, the age of a celebrity, and so on. Now focus on the leading digit of each number, which could be 1, 2, . . . , 8, or 9. Your first thought might be that the leading digit X of a randomly selected number would be equally likely to be one of the nine possibilities (a discrete uniform distribution). However, much empirical evidence as well as some theoretical arguments suggest an alternative probability distribution called Benford’s law:

P(x) = P(1st digit is x) = , x = 1,2,3,...,9.

We need to find,

a. Without computing individual probabilities from this formula, show that it specifies a legitimate pmf.

b. Now compute the individual probabilities and compare to the corresponding discrete uniform distribution.

c. Obtain the cdf of X.

d. Using the cdf, what is the probability that the leading digit is at most 3? At least 5?

Step2:

a).

We have Benford’s law:

P(x) = P(1st digit is x) = , x = 1,2,3,...,9.

If the sum of the all probabilities is unity then we say that the above function is legitimate.

Consider,

P(x) = , x = 1,2,3,...,9

Apply summation on both sides to above equation

Subscribe to view the
full solution

Title Probability and Statistics for Engineering and the Sciences 9 
Author Jay L. Devore
ISBN 9781305251809

Answer: Suppose that you read through this year’s issues

Chapter 3 textbook questions

×

Login

Organize all study tools for free

Or continue with
×

Register

Sign up for access to all content on our site!

Or continue with

Or login if you already have an account

×

Reset password

If you have an active account we’ll send you an e-mail for password recovery

Or login if you have your password back