Sale!

Basic Statistics in Business and Economics 10th Edition by Douglas A Lind, William G Marchal, Samuel A Wathen ISBN 9781260597578 1260597571

Name: Basic Statistics in Business and Economics 10th Edition by Douglas A Lind, William G Marchal, Samuel A Wathen ISBN 9781260597578 1260597571
SKU: EB-33967932
Availability: InStock

Original price was: $50.00.Current price is: $25.00.

Basic Statistics in Business and Economics (ISE HED IRWIN STATISTICS) 10th Edition Douglas A. Lind Digital Instant Download

Author(s): Douglas A. Lind, William G. Marchal, Samuel A. Wathen

ISBN(s): 9781260597578, 1260597571

Edition: 10

File Details: EPUB, 53.19 MB

Year: 2021

Language: English

SKU: EB-33967932 Category: Mathematics Tags: Douglas A. Lind, Samuel A. Wathen, William G. Marchal

Description

Basic Statistics in Business and Economics 10th Edition by Douglas A Lind, William G Marchal, Samuel A Wathen – Ebook PDF Instant Download/Delivery: 9781260597578 ,1260597571
Full download Basic Statistics in Business and Economics 10th Edition after payment

Product details:

ISBN 10: 1260597571
ISBN 13: 9781260597578
Author: Douglas A Lind, William G Marchal, Samuel A Wathen

Basic Statistics in Business ; Economics provides students majoring in management, marketing, finance, accounting, economics, and other fields of business administration with an introductory survey of descriptive and inferential statistics. Many examples and exercises that focus on business applications are used to illustrate the application of statistics, but also relate to the current world of the college student. A previous course in statistics is not necessary, and the mathematical requirement is first-year algebra. Students are given every step needed to be successful in a basic statistics course. This step-by-step approach enhances performance, accelerates preparedness, and significantly improves motivation. Understanding the concepts, seeing and doing plenty of examples and exercises, and comprehending the application of statistical methods in business and economics are the focus of this book. Today, the practice of data analytics is widely applied to big data. The practice of data analytics requires skills and knowledge in several areas. Computer skills are needed to process large volumes of information. Analytical skills are needed to evaluate, summarize, organize, and analyze the information. Critical thinking skills are needed to interpret and communicate the results of processing the information. This text supports the development of basic data analytical skills with the end of each chapter sections called Data Analytics providing the instructor and student with opportunities to apply statistical knowledge and statistical software to explore several business environments. Interpretation of the analytical results is an integral part of these exercises. A variety of statistical software is available to complement the 10th edition. Microsoft Excel includes an add-in with many statistical analyses. MegaStat is an add-in available for Microsoft Excel. Minitab and JMP are stand-alone statistical software packages available to download for either PC or Mac. In the text, Microsoft Excel, Minitab, and MegaStat are used to illustrate statistical software analyses. The text also includes references or links to Excel tutorials in Connect. These provide users with clear demonstrations using statistical software to create graphical and descriptive statistics and statistical analyses to test hypotheses. Digital resources within McGraw Hill Connect? help students apply what they’ve learned and achieve higher outcomes in the course. Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need when they need it and how they need it so that class time is more engaging and effective.

Basic Statistics in Business and Economics 10th Edition Table of contents:

Chapter 1: What Is Statistics?

What Is Statistics?

Introduction

Why Study Statistics?

What Is Meant by Statistics?

Types of Statistics

Descriptive Statistics

Inferential Statistics

Types of Variables

Levels of Measurement

Nominal-Level Data

Ordinal-Level Data

Interval-Level Data

Ratio-Level Data

Ethics and Statistics

Basic Business Analytics

Chapter Summary

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Chapter 2: Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation

Describing Data: Frequency Tables, Frequency Distributions, And Graphic Presentation

Introduction

Constructing Frequency Tables

Relative Class Frequencies

Graphic Presentation of Qualitative Data

Constructing Frequency Distributions

Relative Frequency Distribution

Graphic Presentation of a Distribution

Histogram

Frequency Polygon

Cumulative Distributions

Chapter Summary

Chapter Exercises

Data Analytics

Practice Test

Part 1–Objective

Part 2—Problems

Chapter 3: Describing Data: Numerical Measures

Describing Data: Numerical Measures

Introduction

Measures of Location

The Population Mean

The Sample Mean

Properties of the Arithmetic Mean

The Median

The Mode

Software Solution

The Relative Positions of the Mean, Median, and Mode

The Weighted Mean

Why Study Dispersion?

Range

Variance

Population Variance

Population Standard Deviation

Sample Variance and Standard Deviation

Software Solution

Interpretation and Uses of the Standard Deviation

Chebyshev’s Theorem

The Empirical Rule

Ethics and Reporting Results

Chapter Summary

Pronunciation Key

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Chapter 4: Describing Data: Displaying and Exploring Data

Describing Data: Displaying and Exploring Data

Introduction

Dot Plots

Measures of Position

Box Plots

Skewness

Describing the Relationship between Two Variables

Correlation Coefficient

Contingency Tables

Chapter Summary

Pronunciation Key

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Chapter 5: A Survey of Probability Concepts

A Survey of Probability Concepts

Introduction

What is a Probability?

Approaches to Assigning Probabilities

Classical Probability

Empirical Probability

Subjective Probability

Rules of Addition for Computing Probabilities

Special Rule of Addition

Complement Rule

The General Rule of Addition

Rules of Multiplication to Calculate Probability

Special Rule of Multiplication

General Rule of Multiplication

Contingency Tables

Tree Diagrams

Chapter Summary

Pronunciation Key

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Chapter 6: Discrete Probability Distributions

Discrete Probability Distributions

Introduction

What is a Probability Distribution?

Random Variables

Discrete Random Variable

Continuous Random Variable

The Mean, Variance, and Standard Deviation of a Discrete Probability Distribution

Mean

Variance and Standard Deviation

Binomial Probability Distribution

How Is a Binomial Probability Computed?

Binomial Probability Tables

Cumulative Binomial Probability Distributions

Poisson Probability Distribution

Chapter Summary

Chapter Exercises

Data Analytics

Practice Test

Part 1–Objective

Part 2—Problems

Chapter 7: Continuous Probability Distributions

Continuous Probability Distributions

Introduction

The Family of Uniform Probability Distributions

The Family of Normal Probability Distributions

The Standard Normal Probability Distribution

The Standard Normal Distribution

Applications of the Standard Normal Distribution

The Empirical Rule

Chapter Summary

Chapter Exercises

Data Analytics

Practice Test

Part 1–Objective

Part 2—Problems

Chapter 8: Sampling, Sampling Methods, and the Central Limit Theorem

Sampling, Sampling Methods, and the Central Limit Theorem

Introduction

Research and Sampling

Sampling Methods

Simple Random Sampling

Systematic Random Sampling

Stratified Random Sampling

Cluster Sampling

Sample Mean as a Random Variable

Sampling Distribution of the Sample Mean

The Central Limit Theorem

Standard Error of the Mean

Using the Sampling Distribution of the Sample Mean

Chapter Summary

Pronunciation Key

Chapter Exercises

Data Analytics

Practice Test

Part 1–Objective

Part 2—Problems

Chapter 9: Estimation and Confidence Intervals

Estimation and Confidence Intervals

Introduction

Point Estimate for a Population Mean

Confidence Intervals for a Population Mean

Population Standard Deviation, Known σ

A Computer Simulation

Population Standard Deviation, σ Unknown

A Confidence Interval for a Population Proportion

Choosing an Appropriate Sample Size

Sample Size to Estimate a Population Mean

Sample Size to Estimate a Population Proportion

Chapter Summary

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Chapter 10: One-Sample Tests of Hypothesis

One-Sample Tests of Hypothesis

Introduction

What Is Hypothesis Testing?

Six-Step Procedure for Testing a Hypothesis

Step 1: State the Null Hypothesis (H0) and the Alternate Hypothesis (H1)

Step 2: Select a Level of Significance

Step 3: Select the Test Statistic

Step 4: Formulate the Decision Rule

Step 5: Make a Decision

Step 6: Interpret the Result

One-Tailed and Two-Tailed Hypothesis Tests

Hypothesis Testing for a Population Mean: Known Population Standard Deviation

A Two-Tailed Test

A One-Tailed Test

p-Value in Hypothesis Testing

Hypothesis Testing for a Population Mean: Population Standard Deviation Unknown

A Statistical Software Solution

Test a Hypothesis of a Population Proportion

Chapter Summary

Pronunciation Key

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Chapter 11: Two-Sample Tests of Hypothesis

Two-Sample Tests of Hypothesis

Introduction

Comparing Two Population Variances

The F-Distribution

Testing a Hypothesis of Equal Population Variances

Two-Sample Tests of Hypothesis: Independent Samples

Comparing Population Means with Unknown Population Standard Deviations

Two-Sample Pooled Test

Unequal Population Standard Deviations

Two-Sample Tests of Hypothesis: Dependent Samples

Comparing Dependent and Independent Samples

Two-Sample Tests about Proportions

Chapter Summary

Pronunciation Key

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Chapter 12: Analysis of Variance

Analysis of Variance

Introduction

Anova: Analysis of Variance

ANOVA Assumptions

The ANOVA Test

Inferences about Pairs of Treatment Means

Interaction Plots

Testing for Interaction

Hypothesis Tests for Interaction

Chapter Summary

Pronunciation Key

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Chapter 13: Correlation and Linear Regression

Correlation and Linear Regression

Introduction

What Is Correlation Analysis?

The Correlation Coefficient

Testing the Significance of the Correlation Coefficient

Regression Analysis

Least Squares Principle

Drawing the Regression Line

Testing the Significance of the Slope

Evaluating a Regression Equation’s Ability to Predict

The Standard Error of Estimate

The Coefficient of Determination

Relationships among the Correlation Coefficient, the Coefficient of Determination, and the Standard Error of Estimate

Interval Estimates of Prediction

Assumptions Underlying Linear Regression

Constructing Confidence and Prediction Intervals

Transforming Data

Chapter Summary

Pronunciation Key

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Chapter 14: Multiple Regression Analysis

Multiple Regression Analysis

Introduction

Multiple Regression Analysis

Evaluating a Multiple Regression Equation

The ANOVA Table

Multiple Standard Error of Estimate

Coefficient of Multiple Determination

Adjusted Coefficient of Determination

Inferences in Multiple Linear Regression

Global Test: Testing the Multiple Regression Model

Evaluating Individual Regression Coefficients

Evaluating the Assumptions of Multiple Regression

Linear Relationship

Variation in Residuals Same for Large and Small y ^ Values

Distribution of Residuals

Multicollinearity

Independent Observations

Qualitative Independent Variables

Stepwise Regression

Review of Multiple Regression

Chapter Summary

Pronunciation Key

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Chapter 15: Nonparametric Methods: Nominal Level Hypothesis Tests

Nonparametric Methods: Nominal Level Hypothesis Tests

Introduction

Goodness-of-Fit Tests: Comparing Observed and Expected Frequency Distributions

Hypothesis Test of Equal Expected Frequencies

Hypothesis Test of Unequal Expected Frequencies

Limitations of Chi-Square

Contingency Table Analysis

Chapter Summary

Pronunciation Key

Chapter Exercises

Data Analytics

Practice Test

Part 1—Objective

Part 2—Problems

Appendix A: Data Sets

Appendixes Introduction

Appendix A: Data Sets

A.1 Data Set 1—North Valley Real Estate Data

A.2 Data Set 2—Baseball Statistics, 2022 Season

A.3 Data Set 3—Lincolnville School District Bus Data

A.4 Data Set 4—Applewood Auto Group

Appendix B: Tables

B.1 Binomial Probability Distribution

B.2 Poisson Distribution

B.3 Areas under the Normal Curve

B.4 Table of Random Numbers

B.5 Student’s t-Distribution

B.6A Critical Values of the F-Distribution (α = .01)

B.6A Critical Values of the F-Distributionα=.05

B.6B Critical Values of the F-Distribution (α = .01)

B.6B Critical Values of the F-Distributionα=.01

B.7 Critical Values of Chi-Square

Appendix C: Answers to Odd-Numbered Chapter Exercises & Solutions to Practice Tests

Answers to Odd-Numbered Chapter Exercises

Appendix C: Solutions to Practice Tests

Appendix D: Answers to Self-Review

Appendix D: Answers To Self-Review

Glossary

Index

Student’s t-Distribution

Areas under the Normal Curve

Accessibility Content: Text Alternatives for Images

CHART 1–1 Text Alternative (Chapter 1)

Example Text Alternative (FM)

Exercises Text Alternative (FM)

Two Tables Text Alternative (FM)

Frequency Text Alternative (FM)

MinitabText Alternative (FM

Dialog Box Text Alternative (FM)

Excel Text Alternative (FM)

Population consists Text Alternative (Chapter 1)

CHART 1–2 Text Alternative (Chapter 1)

CHART 1–3 Text Alternative (Chapter 1)

Table lists Text Alternative (Chapter 1)

Exxon Mobile Text Alternative (Chapter 1)

Pie chart show Text Alternative (Chapter 1)

Basic Business Analytics Text Alternative (Chapter 1)

Corresponding bar graph Text Alternative (Chapter 2)

Spreadsheet shows profit class Text Alternative (Chapter 2)

Chart 2–3 Text Alternative (Chapter 2)

Table 2–4 Text Alternative (Chapter 2)

Chart 2–4 Text Alternative (Chapter 2)

Frequency polygon Text Alternative (Chapter 2)

Chart 2–6 Text Alternative (Chapter 2)

Histogram showing Text Alternative (Chapter 2)

Frequency polygon Text Alternative (Chapter 2)

Chart 2–7 Text Alternative (Chapter 2)

Cumulative Frequency Polygon Text Alternative (Chapter 2)

Cumulative Frequency Polygon showing Text Alternative (Chapter 2)

Frequency histogram Text Alternative (Chapter 2)

Cumulative Frequency Polygon showing Text Alternative (Chapter 2)

Pie chart showingText Alternative (Chapter 2)

Percentages shownText Alternative (Chapter 2)

Chart 3–1Text Alternative (Chapter 3)

Spreadsheet shows profitText Alternative (Chapter 3)

A histogram plotsText Alternative (Chapter 3)

Charts 3–4Text Alternative (Chapter 3)

Charts 3–5Text Alternative (Chapter 3)

Histogram plotsText Alternative (Chapter 3)

Chart 3–6Text Alternative (Chapter 3)

California AirportsText Alternative (Chapter 3)

Spreadsheet screenshotText Alternative (Chapter 3)

VarianceText Alternative (Chapter 3)

Ontario AirportText Alternative (Chapter 3)

Showing the sales dataText Alternative (Chapter 3)

Chart 3–7Text Alternative (Chapter 3)

A photograph of a lady collecting coffee Text Alternative (Chapter 3)

Dotplot Text Alternative (Chapter 4)

Minitab screenshot Text Alternative (Chapter 4)

Exclusive and inclusiveText Alternative (Chapter 4)

Exclusive MethodText Alternative (Chapter 4)

BoxplotText Alternative (Chapter 4)

ApplewoodText Alternative (Chapter 4)

Seattle, WashingtonText Alternative (Chapter 4)

Amount spent for booksText Alternative (Chapter 4)

Public collegesText Alternative (Chapter 4)

Chart 4–1Text Alternative (Chapter 4)

Minitab screenshot Text Alternative (Chapter 4)

Two graphs plot negative Text Alternative (Chapter 4)

Chart 4-2 Text Alternative (Chapter 4)

Scatter diagram of age Text Alternative (Chapter 4)

Dotplot of the number Text Alternative (Chapter 4)

Georgetown, Moncks Corner Text Alternative (Chapter 4)

District of Columbia Text Alternative (Chapter 4)

Walter Gogel Company Text Alternative (Chapter 4)

A photograph of rings Text Alternative (Chapter 4)

SOLUTION Text Alternative (Chapter 4)

Number of employees Text Alternative (Chapter 4)

A photograph of an excel-1 Text Alternative (Chapter 5)

A photograph of an excel-2 Text Alternative (Chapter 5)

Diagram illustrating Text Alternative (Chapter 5)

Chart showing two possible Text Alternative (Chapter 5)

Chart 5-1 Text Alternative (Chapter 5)

Venn Diagram illustrating Text Alternative (Chapter 5)

Event A and Event Text Alternative (Chapter 5)

Overlapping circles Text Alternative (Chapter 5)

Draw a King Text Alternative (Chapter 5)

Chart 5.2 Text Alternative (Chapter 5)

Chart 6-1 Text Alternative (Chapter 6)

Systematic list Text Alternative (Chapter 6)

Graph plots probability Text Alternative (Chapter 6)

Excel screenshot Text Alternative (Chapter 6)

CHART 6–2 Text Alternative (Chapter 6)

CHART 6–3 Text Alternative (Chapter 6)

Cumulative Binomial Probability Distributions Text Alternative (Chapter 6)

Poisson Probability Distribution Text Alternative (Chapter 6)

CHART 6–4 Text Alternative (Chapter 6)

Uniform distributionText Alternative (Chapter 7)

20 minutes shaded Text Alternative (Chapter 7)

CHART 7–3 Graph of a normal curve Text Alternative (Chapter 7)

CHART 7–4 Three normal distributions Text Alternative (Chapter 7)

CHART 7–5 Three normal distributions Text Alternative (Chapter 7)

CHART 7–6 Different mean and standard deviation Text Alternative (Chapter 7)

Standard deviation of $100 Text Alternative (Chapter 7)

Applications of the Standard Normal Distribution Text Alternative (Chapter 7)

Excel screenshot showing Text Alternative (Chapter 7)

curve has only two values Text Alternative (Chapter 7)

curve has only two values Text Alternative (Chapter 7) Copy

curve has three values labeled Text Alternative (Chapter 7)

Trying to find the area Text Alternative (Chapter 7)

Table 7-6 Text Alternative (Chapter 7)

Excel will also find the earnings value Text Alternative (Chapter 7)

The Empirical Rule Text Alternative (Chapter 7)

Empirical Rule Text Alternative (Chapter 7)

Spreadsheet listing all the days Text Alternative (Chapter 8)

Sample mean as random variable Text Alternative (Chapter 8)

CHART 8–2 Text Alternative (Chapter 8)

Chart 8–3 Text Alternative (Chapter 8)

Chart 8–4 Text Alternative (Chapter 8)

CHART 8–5 Text Alternative (Chapter 8)

Chart 8–6 Text Alternative (Chapter 8)

Chart 8–7 Text Alternative (Chapter 8)

Chart 8–8 Text Alternative (Chapter 8)

Population Standard Deviation, Known σ Text Alternative (Chapter 9) Copy

Intervals relate to normal curve Text Alternative (Chapter 9)

Chart 9–1 Text Alternative (Chapter 9)

Chart 9–2 Text Alternative (Chapter 9)

Chart 9–3 Text Alternative (Chapter 9)

Steps of a hypothesis Text Alternative (Chapter 10)

CHART 10–1 Text Alternative (Chapter 10)

CHART 10–2 Text Alternative (Chapter 10)

Chart 10–3 Text Alternative (Chapter 10)

Components of the z test Text Alternative (Chapter 10)

CHART 10–4 Text Alternative (Chapter 10)

Standard normal curve Text Alternative (Chapter 10)

Chart 10–5Text Alternative (Chapter 10)

Standard normal curveText Alternative (Chapter 10)

Chart 10–6Text Alternative (Chapter 10)

Chart 10–7Text Alternative (Chapter 10)

Chart 10–8 Text Alternative (Chapter 10)

Comparing Two Population VariancesText Alternative (Chapter 11)

The Excel software Text Alternative (Chapter 11)

Chart 11–1Text Alternative (Chapter 10)

Chart 11–2Text Alternative (Chapter 11)

Minitab screenshotText Alternative (Chapter 11)

A box plot compares store Text Alternative (Chapter 11)

A screenshot shows two-sample Text Alternative (Chapter 11)

Table 11-3 Text Alternative (Chapter 11)

Test for paired two-sample for means Text Alternative (Chapter 11)

Test for two-sample assuming equal variances Text Alternative (Chapter 11)

CHART 11–3 Text Alternative (Chapter 11)

Chart 12–1 Text Alternative (Chapter 12)

Chart 12–2 Text Alternative (Chapter 12)

Anova test step 5(1) Text Alternative (Chapter 12)

Anova test step 5(2) Text Alternative (Chapter 12)

Anova test step 5(3) Text Alternative (Chapter 12)

Minitab screenshot Text Alternative (Chapter 12)

Two-Sample Pooled Test Text Alternative (Chapter 12)

Table showing the calculation Text Alternative (Chapter 12)

Two-Way Analysis of Variance Text Alternative (Chapter 12)

Interaction Plots Text Alternative (Chapter 12)

Fisher pairwise comparison Text Alternative (Chapter 12)

Testing for Interaction Text Alternative (Chapter 12)

Driver Deans Using Route Text Alternative (Chapter 12)

Interaction PlotText Alternative (Chapter 12)

Confidence Intervals for the Fisher Text Alternative (Chapter 12)

A table shows Minitab output Text Alternative (Chapter 12)

A graph compares Text Alternative (Chapter 12)

One-way ANOVA output Text Alternative (Chapter 12)

Chart 13–2 Text Alternative (Chapter 13)

Chart 13–1 Text Alternative (Chapter 13)

Chart 13–3 Text Alternative (Chapter 13)

Number line relating Text Alternative (Chapter 13)

Chart 13–4Text Alternative (Chapter 13)

Chart 13–5 Text Alternative (Chapter 13)

Excel screenshot showing the salesText Alternative (Chapter 13)

Excel of age and profit Text Alternative (Chapter 13)

CHART 13–6Text Alternative (Chapter 13)

CHART 13–7Text Alternative (Chapter 13)

Chart 13–8Text Alternative (Chapter 13)

Chart 13–9Text Alternative (Chapter 13)

Chart 13–10Text Alternative (Chapter 13)

Chart 13–11Text Alternative (Chapter 13)

Chart 13–12Text Alternative (Chapter 13)

The Screenshot Of The SpreadsheetText Alternative (Chapter 13)

Testing the Significance of the Slope Text Alternative (Chapter 13)

The Standard Error of Estimate Text Alternative (Chapter 13)

regression and ANOVAText Alternative (Chapter 13) Copy 3

CHART 13–13Text Alternative (Chapter 13)

Minitab screenshotText Alternative (Chapter 13)

A regression line is overlayedText Alternative (Chapter 13)

scatterplot of the transformed dataText Alternative (Chapter 13)

CHART 14–1Text Alternative (Chapter 14)

cost, temperature, insulation,Text Alternative (Chapter 14)

Cost, temp, Insulation Text Alternative (Chapter 14)

F distribution Text Alternative (Chapter 14)

Same spreadsheet for the cost Text Alternative (Chapter 14)

Evaluating Individual Regression Coefficients Text Alternative (Chapter 14)

Evaluating Individual Regression Text Alternative (Chapter 14)

Evaluating Individual Text Alternative (Chapter 14)

Two scatterplots Text Alternative (Chapter 14)

Two residual plots Text Alternative (Chapter 14)

Histogram of the residuals Text Alternative (Chapter 14)

Correlation matrix showing Text Alternative (Chapter 14)

Regression output Text Alternative (Chapter 14)

Scatter plot of fitted values Text Alternative (Chapter 14)

Excel screenshot showing Text Alternative (Chapter 14)

Minitab screenshot showing Text Alternative (Chapter 14)

Correlation matrix showing Text Alternative (Chapter 14)

Regression output for predicting income Text Alternative (Chapter 14)

Regression output for predicting income-1 Text Alternative (Chapter 14)

Regression output for predicting income-2 Text Alternative (Chapter 14)

Two scatterplots Text Alternative (Chapter 14)

Scatterplot of residuals versus Text Alternative (Chapter 14)

Histogram of the residuals Text Alternative (Chapter 14)

Generic output Text Alternative (Chapter 14)

Generic output from a multiple regression Text Alternative (Chapter 14)

Histogram of the residuals Text Alternative (Chapter 14)

Residual plot showing uniform scatter Text Alternative (Chapter 14)

Histogram of the residuals Text Alternative (Chapter 14)

Residual plot showing uniform scatter Text Alternative (Chapter 14)

CHART 15–1 Text Alternative (Chapter 15)

Compute the value of chi-square and make a decision Text Alternative (Chapter 15)

CHART 15–2 Text Alternative (Chapter 15)

CHART 15–3 Text Alternative (Chapter 15)

Chi-square distribution showing Text Alternative (Chapter 15)

Screenshot of an Excel sheet Text Alternative (Chapter 15)

Chart 15-4 Text Alternative (Chapter 15)

B.3 Areas under the Normal Curve Text Alternative (Appendix)

B.5 Student’s t-Distribution Text Alternative (Appendix)

B.7 Critical Values of Chi-Square Text Alternative (Appendix)

A bar graph plots Text Alternative (Appendix)

A bar graph plots frequency versus color Text Alternative (Appendix)

A histogram plots Text Alternative (Appendix)

A line graph plots numberText Alternative (Appendix)

A graph plots frequencies versus frequentText Alternative (Appendix)

A graph plots frequency tableText Alternative (Appendix)

A graph plots dollar versus item.Text Alternative (Appendix)

A pie chart shows sourcesText Alternative (Appendix)

A histogram plots frequencyText Alternative (Appendix)

A graph shows top 5 CanadianText Alternative (Appendix)

A pie chart shows color frequenciesText Alternative (Appendix)

A line graph plots cumulative numberText Alternative (Appendix)

A line graph plots Text Alternative (Appendix)

A graph plots count versus bedrooms Text Alternative (Appendix)

graph plots number of buses versus miles Text Alternative (Appendix)

A line graph shows relative cumulative Text Alternative (Appendix)

A pie chart shows buses built Text Alternative (Appendix)

A box plot representing statistical data Text Alternative (Appendix)

Whisker Plot Text Alternative (Appendix)

A scatter diagram plots Y versus X Text Alternative (Appendix)

A horizontal box plot of price Text Alternative (Appendix)

A horizontal box plot of size Text Alternative (Appendix)

A graph plots price versus size Text Alternative (Appendix)

A box plot statistical data Text Alternative (Appendix)

Two horizontal box plotting Text Alternative (Appendix)

A graph plots accidents versus age Text Alternative (Appendix)

A box plot of stadium age Text Alternative (Appendix)

A box plot of team salary Text Alternative (Appendix)

A graph plots wins versus salary Text Alternative (Appendix)

Tree diagram showing 3 branches Text Alternative (Appendix)

Tree diagram showing two branches Text Alternative (Appendix)

A box plot of team salary Text Alternative (Appendix)

A Box and Whisker Plot Text Alternative (Appendix)

Column chart A is titled Population Text Alternative (Appendix)

A column titled p Text Alternative (Appendix)

A bar graph Text Alternative (Appendix)

A line graph mean versus machine Text Alternative (Appendix)

A line graph mean versus sector Text Alternative (Appendix)

The line graph’s horizontal axis Alternative (Appendix)

A line graph plots Alternative (Appendix)

Scatterplot of number of advertisements versus Text Alternative (Appendix)

Scatterplot of numberText Alternative (Appendix)

A graph plots sales versus total assets.Text Alternative (Appendix)

A graph plots the correlation between Y and X superscript 2Text Alternative (Appendix)

A scatterplot plots Text Alternative (Appendix)

A graph plotsText Alternative (Appendix)

A graph plots price Text Alternative (Appendix)

A graph plots weight versus consumption Text Alternative (Appendix)

A graph plots fare versus distance Text Alternative (Appendix)

A graph plots attendance Text Alternative (Appendix)

A graph plots wins versus point differential Text Alternative (Appendix)

A graph plots hours versus months Text Alternative (Appendix)

A graph plots median age versus population Text Alternative (Appendix)

A scatterplot bidders line fit plot Text Alternative (Appendix)

A graph plots days versus distance Text Alternative (Appendix)

A graph price versus dividend Text Alternative (Appendix)

A graph price versus speed Text Alternative (Appendix)

A graph weight versus consumption Text Alternative (Appendix) Copy

Histogram of the residuals Text Alternative (Appendix)

Four scatterplots: Text Alternative (Appendix)

The peak of the distribution Text Alternative (Appendix)

A graph plots Text Alternative (Appendix)

Histogram of the residualsText Alternative (Appendix)

Scatterplot of the residuals versus the predicted values Text Alternative (Appendix)

A graph plots frequency Text Alternative (Appendixd)

A histogram plots number of suppliersText Alternative (Appendixd)

A line graph plots cumulative frequenciesText Alternative (Appendixd)

A graph plots frequency versusText Alternative (Appendixd)

A graph plots revenueText Alternative (Appendixd)

A Venn diagram plots Text Alternative (Appendixd)

A tree diagramText Alternative (Appendixd)

A graph plots probability Text Alternative (chapter)

A graph continuous uniform distribution Text Alternative (chapter)

A graph frequency versus mean years Text Alternative (chapter)

A graph region of rejection Text Alternative (chapter)

A graph plots region of rejectionText Alternative (Appendix)

A graph plots sales revenue versus advertising expense.Text Alternative (Appendixd)

A graph plots the region of rejection. (Appendix)

A screenshot of the Minitab (Connect)

A graph shows continuous uniform distribution (Appendix)

A graph shows frequency versus mean years. (Appendix)

Student’s t-Distribution (Student’s t-Distribution)

Areas under the Normal Curve (Areas under the Normal Curve)

A finance-related online assignment in a spreadsheet software Text Alternative (Additional Resources)

A finance-related online assignment in a spreadsheet software Text Alternative Text Alternative (Additional Resources)

A graph plots attendance versus team salary. Text Alternative (Appendix)

A box plot representing statistical data. Text Alternative (Appendix C)

A horizontal box plot Text Alternative (Appendix C)

Two horizontal box plots. Text Alternative (Appendix C)

A bar graph Text Alternative (Appendix C)

A scatterplot Text Alternative (Appendix C)

Scatterplot of cost versus age Text Alternative (Appendix C)

Residuals for Diesel Engines Text Alternative (Appendix C)

Morgan Stanley, an investment company Text Alternative Appendix C)

A section title Text Alternative (Appendix C)

People also search for Basic Statistics in Business and Economics 10th Edition:

applied statistics in business and economics 2024 release

basic statistics with examples

basics of business statistics

essential of statistics for business and economics 10e

basic statistics for business and economics 10e

Tags: Douglas A Lind, William G Marchal, Samuel A Wathen, Basic Statistics, Business