Business Statistics Using EXCEL and SPSS

Nick Lee, Mike Peters

• Publisher: SAGE Publications Ltd
• Year: 2015
• eBook ISBN: 9781473943889
• Edition: 1
• Topic: Business
• Subtopic: Statistics for Business & Economics
• Index: Business

Takes the challenging and makes it understandable. The book contains useful advice on the application of statistics to a variety of contexts and shows how statistics can be used by managers in their work.? - Dr Terri Byers, Assistant Professor, University Of New Brunswick, Canada A book about introductory quantitative analysis, the authors show both how and why quantitative analysis is useful in the context of business and management studies, encouraging readers to not only memorise the content but to apply learning to typical problems. Fully up-to-date with comprehensive coverage of IBM SPSS and Microsoft Excel software, the tailored examples illustrate how the programmes can be used, and include step-by-step figures and tables throughout. A range of 'real world' and fictional examples, including "The Ballad of Eddie the Easily Distracted" and "Esha?s Story" help bring the study of statistics alive. A number of in-text boxouts can be found throughout the book aimed at readers at varying levels of study and understanding

• Back to Basics for those struggling to understand, explain concepts in the most basic way possible - often relating to interesting or humorous examples
• Above and Beyond for those racing ahead and who want to be introduced to more interesting or advanced concepts that are a little bit outside of what they may need to know
• Think it over get students to stop, engage and reflect upon the different connections between topics

A range of online resources including a set of data files and templates for the reader following in-text examples, downloadable worksheets and instructor materials, answers to in-text exercises and video content compliment the book. An ideal resource for undergraduates taking introductory statistics for business, or for anyone daunted by the prospect of tackling quantitative analysis for the first time.

Part 1: The Ballad of Eddie the Easily Distracted

As Eddie sat in the back row for the first lecture of QUAN101 Quantitative Analysis, he wondered exactly how his life had come to this. Perhaps he had died and gone to hell. Or even, he thought with a flash of hope, he might be in the wrong lecture. Yes that was it – he was in the wrong lecture, surely? I mean, what possible interest would he have in his future career with all these formulae and numbers?

His heart sank as the lecturer – a young lady who herself looked only a few years older than him – explained how the course would be assessed by an individual assignment and an exam. He wouldn’t even be able to freeload off other students!

But where to start? There seemed so much to cover in the subject. Dr Jones, the lecturer, seemed pleasant enough certainly, but so had his teachers in the past, and he had never done too well there either. In fact, just the sight of numbers made him feel a little nauseous.

Still, Eddie thought, he was in the lecture anyway so he might as well try to pay attention. Nevertheless, his gaze kept going to the girl in the front row who was taking copious notes, but looking just as bored as he felt. He thought he recognized her from the Student Union bar last night; she’d left early while he had spent many hours with his new friends – which he rather regretted now. What was her name again? Esha he seemed to remember. Seemed nice enough, if a little serious.

Anyway, he tried to get his attention back to the task in hand, but he just couldn’t seem to concentrate. The trouble was that each new concept seemed to build on an earlier idea, and if he hadn’t understood that one, he was totally lost! Given that Eddie was easily distracted, this was a bit of a problem. Eddie resolved to try his best to keep up, but what he really needed was a place where all these basic concepts were addressed slowly, so he could take them in at his own pace.

Eddie left the lecture a little downcast, accidentally bumping into that girl Esha on the way out, who Eddie thought looked at him rather unnecessarily angrily. Later that evening, before meeting his friends in the bar again, he resolved to open the first chapter of his QUAN101 textbook and see if there was anything useful in it.

Esha’s Story: Part 1

Esha had sat in the front row (as she always did) through the first of what she thought, with barely concealed disdain, would probably be a series of interminably boring lectures for QUAN101. Her mood had not been improved when the scruffy-looking daydreamer from the Student Union bar last night had walked straight into her on the way out as if she was invisible.

As Esha walked back to her room on campus, she reflected on the lecture. She had always hated this mathematical stuff. Not because she didn’t understand it – she understood it very well, thank you very much – but because for the life of her she just could not see the point of all this in the real world. She came to university to study management, not maths!

She called her father that night. He had always been useful in situations like this; he owned his own successful firm and had been really pleased when Esha had gone to university to study management, although she had always thought it odd that he had a degree in engineering himself. ‘Dad’ she said with some exasperation, ‘I don’t understand the point of all this maths business, what’s the point of it? I want to study management, not numbers!’

‘Well,’ Esha’s Dad began, as Esha got the feeling she was in for a second lecture of the day, ‘first of all, what do you think I do all day?’ Esha thought about this, and realized she didn’t really know any actual details about what Dad did at work; she just heard him tell interesting stories about the decisions he’d had to take, and what happened afterwards. ‘I’m not sure, Dad. I guess you make decisions about people.’ ‘Quite right,’ he said, ‘but how do you think I make those decisions? Just by guessing?’ Esha got the uncomfortable feeling that she knew where this was going. ‘In order to make big decisions which affect the company, and even people’s lives, you need to have information – and most of that information comes in numbers. Business people who just go on their instincts may do well for a short time, but hardly ever do they stay successful – and in my experience that is true for almost any business career. And if you always rely on others to look at the numbers for you, how do you make your own decisions?’ Esha was beginning to understand the point of QUAN101.

‘But there is a second answer,’ continued her Dad, who was clearly warming to the subject, ‘didn’t you ever wonder why I have an engineering degree, yet I run my own snack food firm? The fact is, sometimes learning things is its own reward. My degree gave me the skills to critically analyse situations and information, even though it wasn’t directly business related at the time. Similarly, understanding mathematics helps you in the interpretation of information, as well as in becoming comfortable with systematic and repeatable answers to general problems. It helps you to think in abstract terms, and to simplify complex specific problems into more general answers – as well as many other useful things.’ Esha had already begun to feel a little better about things, and after she had spoken to her sister about some new shoes (which seemed to be all her sister was ever interested in), she thought she might have a quick look at the first chapter of the QUAN101 textbook.

1 Demystifying Quantitative Data Analysis

Contents

• Learning Objectives 1
• Numerophobia 2
• How is Quantitative Analysis used in Business? 4
• This Section is Really Important! 8
• A Recap of Key Mathematical and Statistical Concepts 15
• Summary 24
• Final Checklist 25
• Exercises 25

learning objectives

This is the first chapter, and our learning objectives are simple really; however, there are quite a few, and they do cover some pretty foundational issues, so please try to bear the following objectives in mind when studying this chapter:

• ☑ Understand why people might be scared or turned off by studying quantitative methods.
• ☑ Understand how quantitative analysis for business is primarily to help you make decisions in your future career, even in what you think might be the most exciting and creative professions.
• ☑ Understand exactly what data is, and what is an element (or data point), a variable and an observation, and how these together make a data set.
• ☑ Understand the difference between qualitative and quantitative variables, and discrete and continuous data.
• ☑ Begin to see how we often approximate the amount of qualities (like happiness) by numbers, but that these numbers are not the exact same thing.
• ☑ Learn the names and properties of the four different scales of measurement – nominal, ordinal, interval and ratio.
• ☑ Understand the difference between cross-sectional and longitudinal data.
• ☑ Understand what a sample is, what a population is, and the relation between the two.
• ☑ Learn why variation is important in quantitative analysis.
• ☑ Learn the concepts of BEDMAS, exponential notation, powers/exponents and logarithms.
• ☑ Understand what equations and functions are, and how they can often be expressed in sigma notation.

If you are reading this, then you are probably beginning a basic, introductory or otherwise foundational quantitative methods course. It will probably be concerned with business studies in some way, but may not be. Many of you will be quite apprehensive at this stage. Like so many people in this world, you may not feel confident with numbers, mathematics and statistics. If you are anything like me, you might have not done so well at these in the past, and may even have forgotten much of what you learnt previously. Or perhaps you might not really see the point of studying quantitative analysis anyway; after all, your course is probably in something else like human resources, work psychology, general management or (like my undergraduate degree) marketing. So the aim of this chapter is to get you off on the right foot in your quantitative analysis studies from now on – whether you are straight out of school, coming back after some work experience, or whatever. I will go through some really key concepts of number theory, mathematics and statistics, and hopefully give you the basic tools to approach quantitative analysis with some confidence. But at the same time, I will do my best to help you understand why quantitative analysis is important for business studies and many other areas of life.

But the first thing to remember is, if you are scared, you are not alone. At this stage, most students are apprehensive about beginning a quantitative course. In fact, this chapter begins with the stories of two students who are pretty typical in my experience – of course they are not real people, but more a combination of characters I have met (parts might even be based on me, but I am not telling which).

Numerophobia1

Quantitative data analysis is frightening. Yes it is. Go ahead, admit it, you are scared of numbers. If you aren’t, (a) you are lying to yourself, (b) you don’t even know enough to be scared yet, or (c) you might be one of the lucky people who were always quite good at it. If you are among the latter, then you’d better get used to getting a lot of late-night visits or calls from your colleagues (actually, if you play your cards right, you can work that to your advantage). But even if you are pretty good at it, don’t get lazy – because, unlike many subjects, quantitative analysis can get very tough very quickly, and if you don’t lay the foundations effectively, you will come unstuck at some stage.

However, I’ll let you in on a little secret. It’s not just students who are scared of quantitative analysis – your lecturers may be too! I know it’s hard to believe, but it’s quite probably true. In fact, you could call the quantitative analysis course in many business school (or other university) departments ‘the graveyard shift’. Certainly in my own experience it’s where bright new lecturers start out teaching (unless they claim some kind of stress-related psychiatric condition or something like that). I started out my career teaching market research, and did it for nearly 10 years. Occasionally, at 9 a.m. on a Monday morning, I would walk into the lecture theatre and see tumbleweeds blowing across the floor, so desolate was the environment. Perhaps I am exaggerating, but when I wake up screaming ‘Central Limit Theorem’ in the middle of the night, I’m not so sure.

In fact, the only thing more scary than quantitative analysis is actually writing a book about it. Box 1.1 shows some of the most common sources of fear that individuals have about quantitative analysis, and some alternative ways of thinking about them.

If you are anything like I was when I arrived at university to study my first2 undergraduate mathematics course, you don’t know a heck of a lot about quantitative analysis. You might have studied it at school – you might even have got pretty good grades as well – but after the summer break you probably forgot most of it, or never really learnt it properly in the first place. Now there’s a whole bunch of stuff that you need to know before you can approach a data set with some confidence and analyse it in a meaningful way. The early chapters of the book lay down these foundational concepts in both a theoretical and a practical way. As a student of an applied discipline (like management, marketing and the like) you are also probably not very interested in quantitative analysis. However, I would not be exaggerating when I say that the difference between someone who is a success in business and someone who is not, is often the ability to take data and manipulate it to draw useful conclu...

Table of contents

• Cover
• Half Title
• Publisher Note
• Title Page
• Copyright Page
• Dedication
• Contents
• About the Authors
• Foreword
• Acknowledgements
• About the Companion website
• Guided Tour of the book
• Part 1: The Ballad of Eddie the Easily Distracted
• 1 Demystifying Quantitative Data Analysis
• Part 2: The Ballad of Eddie the Easily Distracted
• 2 Gathering and Preparing Data
• Part 3: The Ballad of Eddie the Easily Distracted
• 3 The Software Environment
• Part 4: The Ballad of Eddie the Easily Distracted
• 4 Describing Your Data
• Part 5: The Ballad of Eddie the Easily Distracted
• 5 Introduction to Probability
• Part 6: The Ballad of Eddie the Easily Distracted
• 6 Random Variables and Probability Distributions
• Part 7: The Ballad of Eddie the Easily Distracted
• 7 Sampling and Intervals
• Part 8: The Ballad of Eddie the Easily Distracted
• 8 Statistical Hypothesis Testing
• Part 9: The Ballad of Eddie the Easily Distracted
• 9 First Steps in Testing Relationships – Goodness of Fit and Independence Tests
• Part 10: The Ballad of Eddie the Easily Distracted
• 10 Correlation and Regression
• Part 11: The Ballad of Eddie the Easily Distracted
• 11 Regression Special Topics
• Part 12: The Ballad of Eddie the Easily Distracted
• 12 Comparing Two Populations
• Part 13: The Ballad of Eddie the Easily Distracted
• 13 Population Variances
• Part 14: The Ballad of Eddie the Easily Distracted
• 14 ANOVA
• Part 15: The Ballad of Eddie the Easily Distracted
• 15 Time Series Models and Forecasting
• Part 16: The Ballad of Eddie the Easily Distracted
• 16 Using Statistics for Quality Control
• Appendix
• References
• Index