Book: Statistics for Managers Using Microsoft Excel

Book: Statistics for Managers Using Microsoft Excel

For one- or two-semester business statistics courses. Not a new book, but a popular one (8th edition.)
This text is the gold standard for learning how to use Excel in business statistics, helping students gain the understanding they need to be successful in their careers. The authors present statistics in the context of specific business fields; full chapters on business analytics further prepare students for success in their professions. Current data throughout the text lets students practice analyzing the types of data they will see in their professions. The friendly writing style include tips throughout to encourage learning.
The book also integrates PHStat, an add-in that bolsters the statistical functions of Excel.

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Table of Contents
First Things FirstFTF.1 Think Differently About Statistics
FTF.2 Business Analytics: The Changing Face of Statistics
FTF.3 Getting Started Learning Statistics
FTF.4 Preparing to Use Microsoft Excel for Statistics
1. Defining and Collecting Data
1.1 Defining Variables
1.2 Collecting Data
1.3 Types of Sampling Methods
1.4 Data Preparation
1.5 Types of Survey Errors
2. Organizing and Visualizing Variables
2.1 Organizing Categorical Variables
2.2 Organizing Numerical Variables
2.3 Visualizing Categorical Variables
2.4 Visualizing Numerical Variables
2.5 Visualizing Two Numerical Variables
2.6 Organizing and Visualizing a Mix of Variables
2.7 The Challenge in Organizing and Visualizing Variables
3. Numerical Descriptive Measures
3.1 Central Tendency
3.2 Variation and Shape
3.3 Exploring Numerical Data
3.4 Numerical Descriptive Measures for a Population
3.5 The Covariance and the Coefficient of Correlation
3.6 Statistics: Pitfalls and Ethical Issues
4. Basic Probability
4.1 Basic Probability Concepts
4.2 Conditional Probability
4.3 Ethical Issues and Probability
4.4 Bayes’ Theorem
4.5 Counting Rules
5. Discrete Probability Distributions
5.1 The Probability Distribution for a Discrete Variable
5.2 Binomial Distribution
5.3 Poisson Distribution
5.4 Covariance of a Probability Distribution and its Application in Finance
5.5 Hypergeometric Distribution
6. The Normal Distribution and Other Continuous Distributions
6.1 Continuous Probability Distributions
6.2 The Normal Distribution
6.3 Evaluating Normality
6.4 The Uniform Distribution
6.5 The Exponential Distribution
6.6 The Normal Approximation to the Binomial Distribution
7. Sampling Distributions
7.1 Sampling Distributions
7.2 Sampling Distribution of the Mean
7.3 Sampling Distribution of the Proportion
8. Confidence Interval Estimation
8.1 Confidence Interval Estimate for the Mean (Known)
8.2 Confidence Interval Estimate for the Mean (Unknown)
8.3 Confidence Interval Estimate for the Proportion
8.4 Determining Sample Size
8.5 Confidence Interval Estimation and Ethical Issues
8.6 Application of Confidence Interval Estimation in Auditing
8.7 Estimation and Sample Size Estimation for Finite Populations
8.8 Bootstrapping
9. Fundamentals of Hypothesis Testing: One-Sample Tests
9.1 Fundamentals of Hypothesis-Testing Methodology
9.2 t Test of Hypothesis for the Mean (Unknown)
9.3 One-Tail Tests
9.4 Z Test of Hypothesis for the Proportion
9.5 Potential Hypothesis-Testing Pitfalls and Ethical Issues
9.6 Power of the Test
10. Two-Sample Tests
10.1 Comparing the Means of Two Independent Populations
10.2 Comparing the Means of Two Related Populations
10.3 Comparing the Proportions of Two Independent Populations
10.4 F Test for the Ratio of Two Variances
10.5 Effect Size
11. Analysis of Variance
11.1 The Completely Randomized Design: One-Way ANOVA
11.2 The Factorial Design: Two-Way ANOVA
11.3 The Randomized Block Design
11.4 Fixed Effects, Random Effects, and Mixed Effects Models
12. Chi-Square and Nonparametric Tests
12.1 Chi-Square Test for the Difference Between Two Proportions
12.2 Chi-Square Test for Differences Among More Than Two Proportions
12.3 Chi-Square Test of Independence
12.4 Wilcoxon Rank Sum Test: A Nonparametric Method for Two Independent Populations
12.5 Kruskal-Wallis Rank Test: A Nonparametric Method for the One-Way ANOVA
12.6 McNemar Test for the Difference Between Two Proportions (Related Samples)
12.7 Chi-Square Test for the Variance or Standard Deviation
13. Simple Linear Regression
13.1 Types of Regression Models
13.2 Determining the Simple Linear Regression Equation
13.3 Measures of Variation
13.4 Assumptions of Regression
13.5 Residual Analysis
13.6 Measuring Autocorrelation: The Durbin-Watson Statistic
13.7 Inferences About the Slopeand Correlation Coefficient
13.8 Estimation of Mean Values and Prediction of Individual Values
13.9 Potential Pitfalls in Regression
14. Introduction to Multiple Regression
14.1 Developing a Multiple Regression Model
14.2 r2, Adjusted r2, and the Overall F Test
14.3 Residual Analysis for the Multiple Regression Model
14.4 Inferences Concerning the Population Regression Coefficients
14.5 Testing Portions of the Multiple Regression Model
14.6 Using Dummy Variables and Interaction Terms in Regression Models
14.7 Logistic Regression
15. Multiple Regression Model Building
15.1 Quadratic Regression Model
15.2 Using Transformations in Regression Models
15.3 Collinearity
15.4 Model Building
15.5 Pitfalls in Multiple Regression and Ethical Issues
16. Time-Series Forecasting
16.1 The Importance of Business Forecasting
16.2 Component Factors of Time-Series Models
16.3 Smoothing an Annual Time Series
16.4 Least-Squares Trend Fitting and Forecasting
16.5 Autoregressive Modeling for Trend Fitting and Forecasting
16.6 Choosing an Appropriate Forecasting Model
16.7 Time-Series Forecasting of Seasonal Data
16.8 Index Numbers
17. Getting Ready to Analyze Data in the Future
17.1 Analyzing Numerical Variables
17.2 Analyzing Categorical Variables
17.3 Introduction to Business Analytics
17.4 Descriptive Analytics
17.5 Predictive Analytics
18. Statistical Applications in Quality Management (online)
18.1 The Theory of Control Charts
18.2 Control Chart for the Proportion: The p Chart
18.3 The Red Bead Experiment: Understanding Process Variability
18.4 Control Chart for an Area of Opportunity: The c Chart
18.5 Control Charts for the Range and the Mean
18.6 Process Capability
18.7 Total Quality Managementice
18.8 Six Sigma
19. Decision Making (online)
19.1 Payoff Tables and Decision Trees
19.2 Criteria for Decision Making
19.3 Decision Making with Sample Information
19.4 Utility
A. Basic Math Concepts and Symbols
                  A.1 Rules for Arithmetic Operations
                  A.2 Rules for Algebra: Exponents and Square Roots
                  A.3 Rules for Logarithms
                  A.4 Summation Notation
                  A.5 Statistical Symbols
                  A.6 Greek Alphabet
B. Important Excel and Minitab Skills and Concepts
                  B.1 Which Excel Do You Use?
                  B.2 Basic Operations
                  B.2 Formulas and Cell References
                  B.4 Entering a Formula
                  B.5 Formatting Cell Contents
                  B.6 Formatting Charts
                  B.7 Selecting Cell Ranges for Charts
                  B.8 Deleting the “Extra” Histogram Bar
                  B.9 Creating Histograms for Discrete Probability Distributions
C. Online Resources
                  C.1 About the Online Resources for This Book
                  C.2 Accessing the Online Resources
                  C.3 Details Online Resources
                  C.4 PHStat
D. Configuring Microsoft Excel
                  D.1 Getting Microsoft Excel Ready for Use
                  D.2 Checking for the Presence of the Analysis ToolPak or Solver Add-Ins
                  D.3 Configuring Microsoft Windows Excel Security Settings
                  D.4 Opening Pearson-Supplied Add-Ins
E. Tables
                  E.1 Table of Random Numbers
                  E.2 The Cumulative Standardized Normal Distribution
                  E.3 Critical Values of t
                  E.4 Critical Values of
                  E.5 Critical Values of F
                  E.6 Lower and Upper Critical Values, T1, of the Wilcoxon Rank Sum Test
                  E.7 Critical Values of the Studentized Range, Q
                  E.8 Critical Values, dI and dU, of the Durbin–Watson Statistic, D (Critical Values Are One-Sided)
                  E.9 Control Chart Factors
                  E.10 The Standardized Normal Distribution online
F. Useful Excel Knowledge
                  F.1 Useful Keyboard Shortcuts
                  F.2 Verifying Formulas and Worksheets
                  F.3 New Function Names
                  F.4 Understanding the Nonstatistical Functions
G. Software FAQs
                  G.1 PHStat FAQs
                  G.2 Microsoft Excel FAQs
Self-Test Solutions and Answers to Selected Even-Numbered Problems

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