Applied statistics for business and management using Microsoft Excel Linda Herkenhoff, John Fogli

Format:

Book

Author/Creator:

Herkenhoff, Linda

Contributor:

Fogli, John

Language:

English

Subjects (All):

Microsoft Excel (Computer file).

Economics--Statistical methods--Data processing.

Economics.

Statistics.

Mathematical statistics.

Economics--Statistics.

statistics.

Genre:

Statistics

Physical Description:

1 online resource

Place of Publication:

New York, NY Springer 2013

System Details:

text file

PDF

Summary:

Applied Business Statistics for Business and Management using Microsoft Exel is the first book to illustrate the capabilities of Microsoft Excel to teach applied statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical statistical problems in industry. If understanding statistics isn't your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in statistics courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Applied Business Statistics for Business and Management capitalizes on these improvements by teaching students and practitioners how to apply Excel to statistical techniques necessary in their courses and workplace. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand business problems. Practice problems are provided at the end of each chapter with their solutions

Contents:

Machine generated contents note: 1. Data and Statistics

Key Concepts

Discussion

Common Pitfalls

Final Thoughts and Activities

Practice Problems

Discussion Boards

Group Activity

Parting Thought

Problem Solutions

2. Introduction to Excel and Basic Charts

Basic Concepts

Bar and Column Charts

Pie Charts

Line Charts and Area Charts

Other Charts

Pivot Tables (Aka Crosstabs)

Excel

3. Summarizing Data: Descriptive Statistics and Histograms

Symbols

The Histogram

Descriptive Statistics

Histograms

4. Normal Distributions

Discussion

Note continued: Excel

5. Survey Design

Survey Design

Scale

Types of Questions

Data

Coding

Errors in Survey Question Creation

Errors in Survey Data Collection

Checklist

Practice Problems and Case Studies

6. Sampling

Types of Problems

Problem Type: Infinite Mean

Practice Problem for Infinite Mean

Problem Type: Infinite Proportion

Practice Problem for Infinite Proportion

Finite Population Correction Factor (fpc)

7. Inference

Note continued: Key Concepts

Inferring Proportions

Example Problem

Inferring Averages

Confidence Intervals with Proportion Inference

8. Probability

Example 1

Example 2

Finding Probabilities Using Normal Distributions

Calculating Combinations and Permutations

Finding Probabilities Using the Binomial Distribution

Common Excel Pitfalls

9. Correlation

Nonlinear data caution

Average data caution

Correlation: One r Value or Correlation Matrix

Final Thoughts and Activities

Note continued: Practice Problems

10. Simple Linear Regression

Residuals and Tests for Linearity

Standardized Residuals and Outliers

Scatterplot: Compute the Regression Line and the Coefficient of Determination

Regression Function: Compute the Regression Model

Compute Residual Plots Using the Regression Function

Using Excel's Regression Tool to Test for Normality of the Distribution of Residuals

Using Excel's Regression Tool to Test for Constant Variance of Residuals

Summary of Regression Analysis Process

Group Activities

11. Significance Tests Part 1

Significance Tests

F-test

t-Test

Common Excel Pitfalls

Note continued: Final Thoughts and Activities

12. Significance Tests Part 2

X2 Test

z-Test

13. Multiple Regression

Step 1 Fit the Model with Selected Independent Variables

Step 2 Does Multicollinearity Exist? Run a Correlation Matrix

Step 3 Run Regression Model

Step 4 Are the Assumptions of Regression Satisfied?

Step 5 Test Overall Model Significance (F-Test)

Step 6 Check p-Values for Independent Variables Meet Significance Criteria (t-Test)

Step 7 Run Model for Prediction and Estimation

Run Regression Model

14. Non-linear Regression

Power

Polynomial

Exponential

Logarithmic

Create the Trendline Graphs

Using the Non-linear Regression Trendline for Prediction

15. Survey Reports

Useful Hints and Phrases for the Report

Effective PowerPoint Presentations with Excel

Executive Summary

Methodology

Sampling Plan and Survey Creation

Results

Conclusions and Recommendations

Background and Objectives

Research Methodology

Note continued: Overview of Results

Conclusions and Recommendations

Notes:

Includes bibliographical references and index

Other Format:

Print version:

ISBN:

9781461484233

1461484235

1461484227

9781461484226

OCLC:

864999751

Publisher Number:

9781461484233

10.1007/978-1-4614-8423-3

Access Restriction:

Restricted for use by site license