Taking the Fear Out of Data Analysis
A Step-by-Step Approach
Published on 8. April 1997
Book
Paperback/Softback
304 pages
978-1-86152-430-0 (ISBN)
Description
This text is aimed at students who may not like statistics but who need to understand the subject in order to complete their course or gain employment. It is a comprehensive but digestible introduction to statistics, guiding the reader through the number crunching of data analysis without memorising formulae. It is designed to help students understand the theory of data analysis. The text is divided into three parts - understanding data, preparing data for analysis and carrying out analysis - which link the stages of the data analysis process. Examples are used throughout and hints and warnings emphasise key points. This text is suitable for all students studying quantitative methods.
This text is aimed at students who may not like statistics but who need to understand the subject in order to complete their course or gain employment. It is a comprehensive but digestible introduction to statistics, guiding the reader through the number crunching of data analysis without memorising formulae. It is designed to help students understand the theory of data analysis. The text is divided into three parts - understanding data, preparing data for analysis and carrying out analysis - which link the stages of the data analysis process. Examples are used throughout and hints and warnings emphasise key points. This text is suitable for all students studying quantitative methods.
This text is aimed at students who may not like statistics but who need to understand the subject in order to complete their course or gain employment. It is a comprehensive but digestible introduction to statistics, guiding the reader through the number crunching of data analysis without memorising formulae. It is designed to help students understand the theory of data analysis. The text is divided into three parts - understanding data, preparing data for analysis and carrying out analysis - which link the stages of the data analysis process. Examples are used throughout and hints and warnings emphasise key points. This text is suitable for all students studying quantitative methods.
Reviews / Votes
Introduction PART 1: UNDERSTANDING DATA 1. What is Data (And Should You Lose Any Sleep Over It)? 2. Does Sampling Have A Purpose Other than Providing Employment for Statisticians? 3. Why Should You be Concerned about Measurement and are Some Measures Better than Others? PART 2: PREPARING DATA FOR ANALYSIS 4. Have You Cleaned Your Data and Found the Mistakes You Made? 5. Do You Have Access to a Computer Package or Must You Employ A Computer Whiz-Kid? 6. Why Do You Need to Know Your Objective Before You Fail to Achieve It? 7. Why Not Take it Easy Initially and Describe Your Data? 8. Can You Use Few Numbers in Place of Many to Summarise Your Data? 9. What about Using Estimation to See What the Population Looks Like? PART 3: CARRYING OUT THE ANALYSIS 10. How about Sitting Back and Hypothesising? 11. Simple Things First: One Variable, One Sample 12. Getting Experienced: Making Comparisons 13. Getting Adventurous: Searching for Relationships PART 4: PRESENTING THE ANALYSIS 14. A Look into A Multivariate Future 15. It?s All Over, or Is It? Appendices IndexIntroduction PART 1: UNDERSTANDING DATA 1. What is Data (And Should You Lose Any Sleep Over It)? 2. Does Sampling Have A Purpose Other than Providing Employment for Statisticians? 3. Why Should You be Concerned about Measurement and are Some Measures Better than Others? PART 2: PREPARING DATA FOR ANALYSIS 4. Have You Cleaned Your Data and Found the Mistakes You Made? 5. Do You Have Access to a Computer Package or Must You Employ A Computer Whiz-Kid? 6. Why Do You Need to Know Your Objective Before You Fail to Achieve It? 7. Why Not Take it Easy Initially and Describe Your Data? 8. Can You Use Few Numbers in Place of Many to Summarise Your Data? 9. What about Using Estimation to See What the Population Looks Like? PART 3: CARRYING OUT THE ANALYSIS 10. How about Sitting Back and Hypothesising? 11. Simple Things First: One Variable, One Sample 12. Getting Experienced: Making Comparisons 13. Getting Adventurous: Searching for Relationships PART 4: PRESENTING THE ANALYSIS 14. A Look into A Multivariate Future 15. It?s All Over, or Is It? Appendices Index
More details
Language
English
Place of publication
London
United Kingdom
Target group
College/higher education
Professional and scholarly
Illustrations
appendices, index
Dimensions
Height: 246 mm
Width: 188 mm
Thickness: 15 mm
Weight
528 gr
ISBN-13
978-1-86152-430-0 (9781861524300)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Dr Bodo Schlegelmilch is Chair of International Marketing Management at the Vienna University of Economics.
Dr Bodo Schlegelmilch is Chair of International Marketing Management at the Vienna University of Economics.
Dr Bodo Schlegelmilch is Chair of International Marketing Management at the Vienna University of Economics.
Content
Introduction. PART 1: UNDERSTANDING DATA. 1. What is Data (And Should You Lose Any Sleep Over It)? 2. Does Sampling Have A Purpose Other than Providing Employment for Statisticians? 3. Why Should You be Concerned about Measurement and are Some Measures Better than Others? PART 2: PREPARING DATA FOR ANALYSIS. 4. Have You Cleaned Your Data and Found the Mistakes You Made? 5. Do You Have Access to a Computer Package or Must You Employ A Computer Whiz-Kid? 6. Why Do You Need to Know Your Objective Before You Fail to Achieve It? 7. Why Not Take it Easy Initially and Describe Your Data? 8. Can You Use Few Numbers in Place of Many to Summarise Your Data? 9. What about Using Estimation to See What the Population Looks Like? PART 3: CARRYING OUT THE ANALYSIS. 10. How about Sitting Back and Hypothesising? 11. Simple Things First: One Variable, One Sample. 12. Getting Experienced: Making Comparisons. 13. Getting Adventurous: Searching for Relationships. PART 4: PRESENTING THE ANALYSIS. 14. A Look into A Multivariate Future. 15. Its All Over, or Is It? Appendices. Index.