MGMT2063 Research Methods for Business Unit 7_Version 1 1

UNIT 7

Data Preparation and Presentation

Overview

In the last two units we focused on data collection. We will now move on to the preparation

and presentation of data for analysis. More specifically you will learn about editing and coding,

and you will be introduced to the data dictionary, data entry and data cleaning. We will also

look at some ways of displaying data in visual form to facilitate analysis. Throughout the unit

you will be asked to complete a variety of activities including reading, watching videos,

participating in discussions and reflecting on what you have learnt.

Unit 7 Learning Objectives

By the end of this Unit you will be able to:

1. Identify when a response is an error and should be edited

2. Explain how to code qualitative and quantitative data

3. Explain the purpose and construction of the codebook

4. Compare and contrast software used to code and analyse qualitative and quantitative

data

5. Explain the purpose of using a data dictionary

6. Explain the relationship between data fields, data records, data files and databases

7. Describe the tasks involved in data entry, cleaning and modification

8. Distinguish between different techniques for displaying data 9. Explain appropriate use of different techniques for displaying data 10. Create and interpret visual representations of data

MGMT2063 Research Methods for Business Unit 7_Version 1 2

This Unit is divided into three sessions as follows: Session 7.1: Editing and Coding

Session 7.2: The Data Dictionary

Session 7.3: Displaying the Data

Readings and Resources

California State University. (2004, September). Creating a codebook. Available at

http://ccjr.csusb.edu/docs/researchmanualdocs/creatingacodebook.pdf

Data Analysis Excel. (2015, April 4). Create a histogram with Excel [Video file]. Available at: https://www.youtube.com/watch?v=GL91GrVf3EY

Frankfort-Nachmias, C., Nachmias, D., (2008). Research Methods in the Social Sciences (7th

ed.). New York, NY: Worth Publishers.

Igines. (2012, December 9). How to make a bar graph in Excel (Scientific data) [Video file]. Available at: https://www.youtube.com/watch?v=vV6WreL9wxo Igines. (2012, December 9). How to make a line graph in Excel (Scientific data) [Video file]. Available at: https://www.youtube.com/watch?v=Xn7Sd5Uu42A Kirkland Students. (2015, March 15). Data analysis (frequency table) [Video file]. Available at: https://www.youtube.com/watch?v=4UnWevIF9Zw Kirkland Students. (2015, March 18). Data analysis (Stem and leaf plot) [Video file]. Available at: https://www.youtube.com/watch?v=wf5_EjWrKGc LearnChemE. (2012, May 2). Scatter plots in Excel [Video file]. Available at: https://www.youtube.com/watch?v=EiZAW0uxq_U

Lofgren, K. (2013, May 19). Qualitative analysis of interview data: A step-by-step guide [Video

file]. Available at https://www.youtube.com/watch?v=DRL4PF2u9XA

Mencaraglia, A. (2012, May 30). Excel pie chart – Introduction to how to make a pie chart in Excel [Video file] . Available at: https://www.youtube.com/watch?v=FVRJU–8YMY NEDARC. (n.d.). Defining Variables (Data Dictionary). Available at http://www.nedarc.org/tutorials/collectingData/planHowToStoreData/definingVariables. html

http://ccjr.csusb.edu/docs/researchmanualdocs/creatingacodebook.pdf
https://www.youtube.com/watch?v=Xn7Sd5Uu42A
https://www.youtube.com/watch?v=wf5_EjWrKGc
https://www.youtube.com/watch?v=DRL4PF2u9XA
https://www.youtube.com/watch?v=FVRJU–8YMY
MGMT2063 Research Methods for Business Unit 7_Version 1 3

QSR International. (2012, June 20). Introducing NVivo 10 for Windows Software [Video file]. Available at https://www.youtube.com/watch?v=7bLZ7fqSEEc

Quantatative Specialists. (2013, June 29). SPSS Introduction – SPSS for Newbies (Part 1) [Video file]. Available at https://www.youtube.com/watch?v=eTHvlEzS7qQ

Quantatative Specialists. (2013, November 23). SPSS Introduction – Getting Started in SPSS (Part 2) [Video file]. Available at https://www.youtube.com/watch?v=klrC94nO2ds&feature=iv&src_vid=1VVeR5C5BpM&a nnotation_id=annotation_1810116217

Shukla, P. (2008). Essentials of marketing research. Available at

http://bookboon.com/en/marketing-research-an-introduction-ebook

University of Leicester. (2012). Presenting numerical data. Available at http://www2.le.ac.uk/offices/ld/resources/study-guides-pdfs/numeracy-skills- pdfs/presenting%20numerical%20data%20updated%20LD.pdf

https://www.youtube.com/watch?v=eTHvlEzS7qQ
https://www.youtube.com/watch?v=klrC94nO2ds&feature=iv&src_vid=1VVeR5C5BpM&annotation_id=annotation_1810116217
https://www.youtube.com/watch?v=klrC94nO2ds&feature=iv&src_vid=1VVeR5C5BpM&annotation_id=annotation_1810116217
http://bookboon.com/en/marketing-research-an-introduction-ebook
MGMT2063 Research Methods for Business Unit 7_Version 1 4

Session 7.1

Editing and Coding

Introduction

In this session, we look at data editing and coding. This stage of data analysis allows the researcher to transform raw data (the unedited responses of respondents) collected during data

collection into useable data. We will discuss the various methods of coding used by researchers.

We will look at the editing process and we will learn rules for coding and the construction of a codebook. We will learn about various coding devices and software programs used in storing,

processing, accessing, and analyzing data sets.

Learning Objectives

By the end of this session you will be able to: 1. Identify when a response is an error and should be edited

2. Explain how to code qualitative and quantitative data

3. Explain the purpose and construction of the codebook

4. Compare and contrast software used to code and analyse qualitative and quantitative

data

Data Editing

After completing data collection the researcher will need to make sense of the data collected and present it to the decision makers. Fieldwork often produces data that contains errors which

must be removed to ensure the integrity of the data. The process of checking data for

omissions, consistency, and legibility in preparation for coding is called data editing.

Consider the examples provided below and what the researcher/editor should do.

MGMT2063 Research Methods for Business Unit 7_Version 1 5

In the first example, data should not have been collected from the respondent because he did not fall within the target population. The researcher/editor should remove this respondent’s

data from the study. In the second example, the respondent has provided inconsistent

information. The researcher/editor can correct the error by adjusting the answer to the first question to “3” Eastern Caribbean countries travelled to in the last year.

When editing and cleaning data, it is important that the researcher/editor makes “intelligent, experienced, and objective decisions” (Zikmund, Babin, Carr, & Griffin, 2009, p 468) to minimize

interference with the data, avoid bias, make logical adjustments and make ethical decisions. To avoid

having to remove the respondent’s responses, the researcher may need to contact the respondent for

clarification of responses.

Coding Data

Edited data are assigned codes to simplify analysis. Coding refers to the assignment of a numerical score or a classifying symbol to edited data to group data into categories. This

facilitates the entry of data into computer software for analysis. For example, when coding a

response on gender a 1 can be assigned to the response “female” and a 2 for the response “male”:

Female = 0 Male = 1

Note that codes are not always numerical and in qualitative research, numbers are usually not used for codes, words and phrases that represent themes are most common (Zikmund, Babin,

Carr, & Griffin, 2009).

Examples of Need for Editing and Cleaning

Example 1:

A grocery store is studying the shopping habits of young adults aged 18-30. One

respondent indicated that he was 17 years old. What should the researcher or editor do?

Example 2:

A respondent has selected “2” to a question that asked how many Eastern Caribbean

countries were visited in the last year. The same respondent indicates in a later question

that she visited Antigua and Barbuda, Grenada and the British Virgin Islands in the last six months. What should the researcher or editor do?

MGMT2063 Research Methods for Business Unit 7_Version 1 6

Constructing the Codebook

A codebook, also called a coding scheme, contains details on all the codes used in the research.

It can be used to for more accurate and efficient data entry and analysis. The information

contained in the codebook includes:

 the variable name

 the variable number

 the coding scheme

 codes

 codes for missing data

Using the Codebook

The codebook describes data files which are the files used to conduct analyses. Today data files are computer files that contain the data. In a data editor, such as SPSS (Statistical Package for

Social Scientists), data appear in the form of spreadsheets (figure 7.1) where the data appears as

columns of information representing the different variables. Each column in the data file is equal to one variable from the data file.

Figure 7.1 – SPSS Data Editor

The codebook is useful when using software such as:

 SPSS – commonly used for quantitative data coding and analysis

 NVivo – commonly used for qualitative data coding and analysis

http://www.spss-tutorials.com/spss-data-editor-window/
MGMT2063 Research Methods for Business Unit 7_Version 1 7

The resources below provide useful introductions to these software packages.

Useful link/Resource

 Quantatative Specialists. (2013, June 29). SPSS Introduction – SPSS for Newbies (Part 1) [Video file]. Available at https://www.youtube.com/watch?v=eTHvlEzS7qQ

 QSR International. (2012, June 20). Introducing NVivo 10 for Windows Software [Video file]. Available at https://www.youtube.com/watch?v=7bLZ7fqSEEc

You may find the resource provided below to be useful. It describes the process involved in

coding qualitative data.

Useful link/Resource

 Lofgren, K. (2013, May 19). Qualitative analysis of interview data: A step-by-step guide [Video file]. Available at https://www.youtube.com/watch?v=DRL4PF2u9XA

Let’s explore editing and coding in greater detail. Please complete Learning

Activity 7.1.

LEARNING ACTIVITY 7.1

Instructions:

1. Frankfort-Nachmias, C., Nachmias, D., & DeWaard, J. (2014). Research methods

in the social sciences (8th edition). Worth Publishers Chapter 14 pages 303-317

2. Read the following article: Creating a codebook available at

http://ccjr.csusb.edu/docs/researchmanualdocs/creatingacodebook.pdf

3. Research a software application not mentioned in this session that

researchers use to code qualitative or quantitative data. Write a blog entry

https://www.youtube.com/watch?v=eTHvlEzS7qQ
https://www.youtube.com/watch?v=7bLZ7fqSEEc
https://www.youtube.com/watch?v=DRL4PF2u9XA
http://ccjr.csusb.edu/docs/researchmanualdocs/creatingacodebook.pdf
MGMT2063 Research Methods for Business Unit 7_Version 1 8

reviewing, comparing and contrasting coding using your selected

software and SPSS or NVivo.

Session Summary

In this session we examined the editing and coding of data. We explored the importance

of checking data for omissions, consistency, legibility and errors to ensure the integrity

of the data. We also looked at the process of coding data to make it more

understandable by computer software in preparation for analysis. This included

constructing and using a codebook and software use to code data. We ended the session

by the construction of a codebook and software that may be used to create and analyse

data codes. You should now be able to:

 identify when a response is an error and should be edited,

 explain how to code qualitative and quantitative data,

 explain the purpose and construction of the codebook, and

 compare and contrast software used to code and analyse qualitative and

quantitative data.

MGMT2063 Research Methods for Business Unit 7_Version 1 9

Session 7.2

The Data Dictionary

Introduction

In the last session you learnt about coding and constructing the codebook. You were also

introduced to software used for compiling data and which will be used to facilitate analysis. In this session we continue the process by learning about database management and the data

dictionary. You will also learn about the procedures for creating a data file and the tasks

involved in data cleaning and data modification.

Learning Objectives

By the end of this session you will be able to: 1. Explain the purpose of using a data dictionary

2. Explain the relationship between data fields, data records, data files and databases

3. Describe the tasks involved in data entry, cleaning and modification

Working with Databases

In preparing data for analysis, the researcher will need to create a database, which is an

electronic representation of the data collected during research. The database allows for the data

to be organized and stored for ease of manipulation and analysis. A database is structured

based on fields, records and files. You will need to distinguish between these terms as you

engage with the resources in this and the upcoming unit.

Field – a field is a single piece of data, such as name, age and occupation, which is each an

answer to a specific question.

Record – a record is a set of data fields that are related to a case or participant, such as all the

responses of one participant in a study.

File – a file is a set of records, such as the responses of all respondents in a study.

MGMT2063 Research Methods for Business Unit 7_Version 1 10

What is a Data Dictionary?

A data dictionary is a collection of descriptions of the data objects or items in a database. It usually serves clarification purposes for the benefit of programmers and other persons involved in the analytic process. Each object must be identified and it must be described in relation to the other objects. Each object must be given a descriptive name. Possible predefined values must be listed and described briefly. The data dictionary is consulted when there is any confusion about any of the data items. The dictionary usually comprises eight columns as shown in Table 7.1. Variable Name

Variable Label

Value Label

Field Type Decimal Field Width

Start End

This column includes the variable name

May be two or three words; represents the variable to be measured;

Labels for the values e.g. the actual sex of a respondent

The value to be given to the code such as alphanumeric values

Number of decimal places

Number of digits in the field

Where the field begins

Where the field ends

sex gender 1 – male 2 – female

numeric 0 1 4 4

Table 7.1 Data dictionary

You will learn more about the data dictionary in Learning Activity 7.2.

Data Entry

Data entry is the process of inputting data gathered into a database for manipulation, storage

and analysis. This is done once coding had been completed.

The software applications mentioned in the previous session, along with other options, can be

used to create databases. The resources provided below show how to enter data in SPSS.

Useful link/Resource

 Quantatative Specialists. (2013, June 29). SPSS Introduction – SPSS for Newbies (Part 1) [Video file]. Available at https://www.youtube.com/watch?v=eTHvlEzS7qQ

 Quantatative Specialists. (2013, November 23). SPSS Introduction – Getting Started in SPSS (Part 2) [Video file]. Available at https://www.youtube.com/watch?v=klrC94nO2ds&feature=iv&src_vid=1VVeR5C 5BpM&annotation_id=annotation_1810116217

https://www.youtube.com/watch?v=eTHvlEzS7qQ
https://www.youtube.com/watch?v=klrC94nO2ds&feature=iv&src_vid=1VVeR5C5BpM&annotation_id=annotation_1810116217
https://www.youtube.com/watch?v=klrC94nO2ds&feature=iv&src_vid=1VVeR5C5BpM&annotation_id=annotation_1810116217
MGMT2063 Research Methods for Business Unit 7_Version 1 11

Data Cleaning

Data cleaning is a very important step to be taken before any data processing can be

undertaken. Similar to editing, it is an important means of quality control. Cleaning allows the

researcher to verify that all values collected are correct or that they conform to certain rules. For example, under gender there can only be one of two values 1 or 2. Some basic checks to be

conducted to verify the data are:

 wildcode checking – this is a check which ensures that no impossible codes are entered.

For example entering a 3 under sex.

 consistency checking – involves cross checking with other values, fields to ensure the

data is consistent. For example, if the parent admits to having only one child but later on the form the heights of two children are recorded.

Data Modification

Data modification is the alteration of the data. This may be done for the following reasons:

 the researcher can combine several indicators to create an index;

 to create an index score by adding the data used to code the responses

 to rearrange the numerical order of categories.

 to create broader categories of variables.

Please complete Learning Activity 7.2 before continuing with the unit. This activity will require you to read further about the data dictionary and data entry and cleaning and participate in a

discussion based on the readings.

LEARNING ACTIVITY 7.2

Instructions:

1. Read Defining Variables (Data Dictionary) available at

http://www.nedarc.org/tutorials/collectingData/planHowToStoreData/definingVaria

bles.html

2. Read section 7.3 of Shukla (2008) available at http://bookboon.com/en/marketing-

research-an-introduction-ebook

http://www.nedarc.org/tutorials/collectingData/planHowToStoreData/definingVariables.html
http://www.nedarc.org/tutorials/collectingData/planHowToStoreData/definingVariables.html
http://bookboon.com/en/marketing-research-an-introduction-ebook
http://bookboon.com/en/marketing-research-an-introduction-ebook
MGMT2063 Research Methods for Business Unit 7_Version 1 12

Session Summary

In this session we continued to explore preparation of data for analysis. You were

introduced to the processes of data cleaning and data modification, and the need for

these two processes. You also learnt about the data dictionary and its place in the

process. You should now be able to:

 explain the purpose of using a data dictionary,

 explain the relationship between data fields, data records, data files and databases;

and

 describe the tasks involved in data entry, cleaning and modification.

MGMT2063 Research Methods for Business Unit 7_Version 1 13

Session 7.3

Displaying the Data

Introduction

In the previous sessions of this unit you were introduced to the activities involved in preparing data for analysis. After preparing data for analysis it may be tempting to jump into data

analysis to determine if data support the hypotheses or to answer the research questions.

However, when dealing with statistical data, the researcher should first engage in exploratory data analysis to visualize the data. In this session, you will explore techniques that the

researcher can use to visualize and graphically represent the data to facilitate preliminary

analysis for patterns in data. You will learn about devices such as tables and various types of graphs.

Learning Objectives

After completing the session, you will be able to: 1. Distinguish between different techniques for displaying data 2. Explain appropriate use of different techniques for displaying data 3. Create and interpret visual representations of data

Frequency Tables

A frequency table can be used to present numerical data. The data is easily read and

interpreted when organized in a table form. It is a simple way of arraying numerical data. This

device is useful for showing where no observations occur within the range, which cannot be

captured in a bar chart or pie chart.

Age Group Frequency Percentage Cumulative

percentage

12-17 36 15.0 15.0

18-23 44 18.3 33.3

24-29 43 17.9 51.2

30-35 46 19.2 70.4

36-41 34 14.2 84.6

42-47 37 15.4 100.0

Total 240 100.0% 100.0%

MGMT2063 Research Methods for Business Unit 7_Version 1 14

Figure 7.1 Frequency table

The resource below explains how to create a frequency table.

Useful Link/Resource

Kirkland Students. (2015, March 15). Data analysis (frequency table) [Video file]. Available at: https://www.youtube.com/watch?v=4UnWevIF9Zw

Graphs and Charts

Some reasons for drawing charts and graphs are to show frequency, distribution, trends, composition, flows, processes, location and comparisons. The construction of charts and graphs

can be done manually, using traditional methods. However, today this is done more commonly

using software such as Microsoft Excel, SPSS and Minitab.

There are a wide variety of graphs and charts that the researcher can use to analyse data. These

include bar charts, pie charts, line graphs, scatter plots and stem-and-leaf displays. Let’s take a closer look at some of the common techniques.

Bar Charts

Bar charts are used to display number and frequency for discrete categories or groups. These

charts are useful for ungrouped data, but not grouped data (see Figure 7.3).

Figure 7.3 Bar chart

https://www.youtube.com/watch?v=4UnWevIF9Zw
MGMT2063 Research Methods for Business Unit 7_Version 1 15

The resource below explains how to create a bar chart.

Useful Link/Resource

Igines. (2012, December 9). How to make a bar graph in Excel (Scientific data) [Video file]. Available at: https://www.youtube.com/watch?v=vV6WreL9wxo

Histograms

Bar charts cannot be used to present continuous data. However, histograms may be used to

represent continuous random variables (see Figure 7.4). Histograms allow the researcher to easily identify the most popular class in the data and simple patterns in data.

Figure 7.4 Histogram

The resource below explains how to create a histogram.

Useful link/Resource

Data Analysis Excel. (2015, April 4). Create a histogram with Excel [Video file]. Available at: https://www.youtube.com/watch?v=GL91GrVf3EY

https://www.youtube.com/watch?v=vV6WreL9wxo
MGMT2063 Research Methods for Business Unit 7_Version 1 16

Pie Charts

Pie charts are used to display categorical or grouped data. They represent the total distribution of data across categories.

Figure 7.5 Pie chart

The resource below explains how to create a pie chart.

Useful link/Resource

Mencaraglia, A. (2012, May 30). Excel pie chart – Introduction to how to make a pie chart in

Excel [Video file]. Available at: https://www.youtube.com/watch?v=FVRJU–8YMY

Line Graphs

Line graphs are used to show how one or more variables vary over a continuous period of time.

MGMT2063 Research Methods for Business Unit 7_Version 1 17

Figure 7.6 Line graph

The resource below explains how to create a line graph.

Useful link/Resource

Igines. (2012, December 9). How to make a line graph in Excel (Scientific data) [Video file]. Available at: https://www.youtube.com/watch?v=Xn7Sd5Uu42A

Scatter Plots

Scatter plots are used to display the relationship between two variables. They can be used to determine systematic or causal relationships.

https://www.youtube.com/watch?v=Xn7Sd5Uu42A
MGMT2063 Research Methods for Business Unit 7_Version 1 18

Figure 7.7 Scatter plot

The resource below explains how to create a scatter plot.

Useful link/Resource

LearnChemE. (2012, May 2). Scatter plots in Excel [Video file]. Available at: https://www.youtube.com/watch?v=EiZAW0uxq_U

Stem and Leaf Plots

Stem and leaf plots are a quick way to represent large amounts of data graphically. They are useful for presenting discrete and continuous data.

https://www.youtube.com/watch?v=EiZAW0uxq_U
MGMT2063 Research Methods for Business Unit 7_Version 1 19

Figure 7.8 Stem and leaf display

The video below provides useful information on creating stem and leaf plots.

Useful link/Resource

Kirkland Students. (2015, March 18). Data analysis (Stem and leaf plot) [Video file]. Available at: https://www.youtube.com/watch?v=wf5_EjWrKGc

If you are having trouble understanding any of the charts and graphs that we just discussed, remember that there is a wide variety of tutorials available online.

Presenting Data in Reports

It is important that you understand appropriate use of the display techniques to

facilitate preliminary data analysis and for use in reports to be read by others. Although

we are focusing, in this session, on displaying data for analysis, you should note that

the formats used above can also be used for displaying data in reports during the

presentation stage of research as a means of summarizing results. When used for this

purpose, there are design factors that the researcher will need to consider to ensure ease

of interpretation by persons who are not as intimate with the research and the data. You

may find the resource provided below to be useful.

https://www.youtube.com/watch?v=wf5_EjWrKGc
MGMT2063 Research Methods for Business Unit 7_Version 1 20

Useful link/Resource

 University of Leicester. (2012). Presenting numerical data. Available at http://www2.le.ac.uk/offices/ld/resources/study-guides-pdfs/numeracy-skills- pdfs/presenting%20numerical%20data%20updated%20LD.pdf

Please complete Learning Activity 7.3 which requires you to apply what you have just learnt about displaying data to create a graph or chart of your own.

LEARNING ACTIVITY 7.3

Instructions:

1. Use a visual technique to display the following data on students’ modes of transportation:

Student Mode Student Mode Student Mode

1 Car 6 Bus 11 Bus

2 Bus 7 Car 12 Car

3 Walk 8 Walk 13 Car

4 Walk 9 Bus 14 Bus

5 Walk 10 Walk 15 Bus

2. Post your graph or chart in the discussion forum on the learning exchange and explain your choice of display technique and how you created it. Comment on the posts of two or your peers.

Session Summary

In this session you learnt about methods of presenting data. You were introduced to

graphical display methods such as tables, bars graphs, and charts. You learnt how to

construct these charts and graphs. You should now be able to:

http://www2.le.ac.uk/offices/ld/resources/study-guides-pdfs/numeracy-skills-pdfs/presenting%20numerical%20data%20updated%20LD.pdf
http://www2.le.ac.uk/offices/ld/resources/study-guides-pdfs/numeracy-skills-pdfs/presenting%20numerical%20data%20updated%20LD.pdf
MGMT2063 Research Methods for Business Unit 7_Version 1 21

 distinguish between different techniques for displaying data,

 explain appropriate use of different techniques for displaying data, and

 create and interpret visual representations of data.

Learning Activity 7.4

In the first unit you created a 'wall' at https://padlet.com/ Create another 'box' for Unit 7 and

summarise what you have learnt from this unit. Do remember to include your reflections on the topics learnt. Remember, your summary should not exceed one box.

Unit 7 Summary

This unit focused on data preparation and presentation. This involves editing and coding data, centering and cleaning data and displaying data for analysis. You learnt that quality control is very important throughout preparation of data for analysis, which is why data should be edited and cleaned at the respective stages in the process. You also learnt that data may be more difficult to analyse and interpret unless it is appropriately displayed in a visual form. Having completed preparation for data analysis, you are now ready to analyse the data. You will cover this topic in the next and final session of this course.

References

California State University. (2004, September). Creating a codebook. Available at

http://ccjr.csusb.edu/docs/researchmanualdocs/creatingacodebook.pdf

Data Analysis Excel. (2015, April 4). Create a histogram with Excel [Video file]. Available at: https://www.youtube.com/watch?v=GL91GrVf3EY

Frankfort-Nachmias, C., Nachmias, D., (2008). Research Methods in the Social Sciences (7th

ed.). New York, NY: Worth Publishers.

https://padlet.com/
http://ccjr.csusb.edu/docs/researchmanualdocs/creatingacodebook.pdf
MGMT2063 Research Methods for Business Unit 7_Version 1 22

Lofgren, K. (2013, May 19). Qualitative analysis of interview data: A step-by-step guide [Video

file]. Available at https://www.youtube.com/watch?v=DRL4PF2u9XA

QSR International. (2012, June 20). Introducing NVivo 10 for Windows Software [Video file]. Available at https://www.youtube.com/watch?v=7bLZ7fqSEEc

Quantatative Specialists. (2013, June 29). SPSS Introduction – SPSS for Newbies (Part 1) [Video file]. Available at https://www.youtube.com/watch?v=eTHvlEzS7qQ

Shukla, P. (2008). Essentials of marketing research. Available at

http://bookboon.com/en/marketing-research-an-introduction-ebook

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