Quality Control Suppose that a company selects two people who work independently | StudySoup
Statistics: Informed Decisions Using Data | 4th Edition | ISBN: 9780321757272 | Authors: Michael Sullivan, III

Table of Contents

1
Data Collection
1.1
Introduction to the Practice of Statistics
1.2
Observational Studies versus Designed Experiments
1.3
Simple Random Sampling
1.4
Other Effective Sampling Methods
1.5
Bias in Sampling
1.6
The Design of Experiments

2
Organizing and summarizing data
2.1
Organizing Qualitative Data
2.2
Organizing Quantitative Data: The Popular Displays
2.3
Additional Displays of Quantitative Data
2.4
Graphical Misrepresentations of Data

3
Numerically summarizing data
3.1
Measures of Central Tendency
3.2
Measures of Dispersion
3.3
Measures of Central Tendency and Dispersion from Grouped Data
3.4
Measures of Position and Outliers
3.5
The Five-Number Summary and Boxplots

4
Describing the relation between two variables
4.1
Scatter Diagrams and Correlation
4.2
Least-Squares Regression
4.3
Diagnostics on the Least-Squares Regression Line
4.4
Contingency Tables and Association
4.5
Nonlinear Regression: Transformations (on CD)

5
Probability Rules
5.1
Probability Rules
5.2
The Addition Rule and Complements
5.3
Independence and the Multiplication Rule
5.4
Conditional Probability and the General Multiplication Rule
5.5
Counting Techniques
5.6
Putting It Together: Which Method Do I Use?
5.7
Bayes’s Rule (on CD)

6
Discrete Probability Distributions
6.1
Discrete Random Variables
6.2
The Binomial Probability Distribution
6.3
The Poisson Probability Distribution
6.4
The Hypergeometric Probability Distribution (On CD)

7
The normal probability distribution
7.1
Properties of the Normal Distribution
7.2
Applications of the Normal Distribution
7.3
Assessing Normality
7.4
The Normal Approximation to the Binomial Probability Distribution

8
Sampling distributions
8.1
Distribution of the Sample Mean
8.2
Distribution of the Sample Proportion

9
Estimating the value of a parameter
9.1
Estimating a Population Proportion
9.2
Estimating a Population Mean
9.3
Estimating a Population Standard Deviation
9.4
Putting it Together: Which Procedure Do I Use?
9.5
Estimating with Bootstrapping

10
Hypothesis tests regarding a parameter
10.1
The Language of Hypothesis Testing
10.2
Hypothesis Tests for a Population Proportion
10.3
Hypothesis Tests for a Population Mean
10.4
Hypothesis Tests for a Population Standard Deviation
10.5
Putting It Together: Which Method Do I Use?
10.6
The Probability of a Type II Error and the Power of the Test

11
Inferences on two samples
11.1
Inference about Two Population Proportions
11.2
Inference about Two Means: Dependent Samples
11.3
Inference about Two Means: Independent Samples
11.4
Inference about Two Population Standard Deviations
11.5
Putting It Together: Which Method Do I Use?

12
Inference on Categorical Data
12.1
Goodness-of-Fit Test
12.2
Tests for Independence and the Homogeneity of Proportions

13
Comparing three or more means
13.1
Comparing Three or More Means (One-Way Analysis of Variance)
13.2
Post Hoc Tests on One-Way Analysis of Variance
13.3
The Randomized Complete Block Design
13.4
Two-Way Analysis of Variance

14
Inference on the least-squares regression model and multiple regression
14.1
Testing the Significance of the Least-Squares Regression Model
14.2
Confidence and Prediction Intervals
14.3
Multiple Regression

15
Nonparametric Statistics
15.1
An Overview of Nonparametric Statistics
15.2
Runs Test for Randomness
15.3
Inferences about Measures of Central Tendency
15.4
Inferences about the Difference between Two Medians: Dependent Samples
15.5
Inferences about the Difference between Two Medians: Independent Samples
15.6
Spearman’s Rank- Correlation Test
15.7
Kruskal–Wallis Test

Textbook Solutions for Statistics: Informed Decisions Using Data

Chapter 5.3 Problem 20

Question

Quality Control Suppose that a company selects two people who work independently inspecting two-by-four timbers. Their job is to identify low-quality timbers. Suppose that the probability that an inspector does not identify a low-quality timber is 0.20. (a) What is the probability that both inspectors do not identify a low-quality timber? (b) How many inspectors should be hired to keep the probability of not identifying a low-quality timber below 1%? (c) Interpret the probability from part (a).

Solution

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The first step in solving 5.3 problem number 20 trying to solve the problem we have to refer to the textbook question: Quality Control Suppose that a company selects two people who work independently inspecting two-by-four timbers. Their job is to identify low-quality timbers. Suppose that the probability that an inspector does not identify a low-quality timber is 0.20. (a) What is the probability that both inspectors do not identify a low-quality timber? (b) How many inspectors should be hired to keep the probability of not identifying a low-quality timber below 1%? (c) Interpret the probability from part (a).
From the textbook chapter Independence and the Multiplication Rule you will find a few key concepts needed to solve this.

Step 2 of 7)

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Title Statistics: Informed Decisions Using Data  4 
Author Michael Sullivan, III
ISBN 9780321757272

Quality Control Suppose that a company selects two people who work independently

Chapter 5.3 textbook questions

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