Data Analysis for Research
Data Analysis for Research
BML224:
Guidance Booklet #1 Course Outline and Assessment 2015
Scan for Moodle
Business School Dr Andrew Clegg
Data Analysis for Research
Data Analysis for Research Introduction
The acquisition, manipulation, interpretation and presentation of data are important skills for graduates. The aim of this module is to introduce students to the use of computer-based statistical techniques for the analysis and presentation of quantitative data sources. The module provides an appropriate link to Business Research, where more qualitative research methodologies will be discussed. The module is designed to reflect the lack of confidence and anxiety felt by students when dealing with statistical techniques, often for the first time. The module will take the students on a structured and applied journey, starting at an introductory level looking at the rationale and contextualisation for the use of quantitative research methodologies. From here consideration will be given to the generation and use of descriptive statistics, through to the application of more advanced statistical techniques.
Learning Outcomes
Knowledge and Understanding: On successful completion of this module students will be able to: Relate and critically apply the use of quantitative methodologies to their own research Distinguish between the characteristics of different data types and apply to quantitative methodologies and data collection strategies Acquire, analyse, interpret and present quantitative data appropriately using SPSS and Excel Accurately select and apply appropriate advanced statistical techniques in SPSS and analyse the output accordingly Relate underlying statistical theory, such as the normal distribution, to statistical analysis
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Data Analysis for Research
Module Content
Week 1 - 5/9/16:
Introduction
Week 2 - 12/9/16:
Research Design and Data Collection 1
Week 3 - 19/9/16: No Sessions - Self-Directed Tasks Week 4 - 26/9/16: Research Design and Data Collection 2 Week 5 - 3/10/16: Research Design and Data Collection 3 Week 6 - 10/10/16: Exploratory Data Analysis 1 - Basic Descriptive Statistics Week 7 - 17/10/16:
Exploratory Data Analysis 2 - Presenting Data
Week 8 - 24/10/16:
READING WEEK
Week 9 - 31/10/16:
Understanding Your Data: Normal Distribution and Patterns of Dispersion
Week 10 - 7/11/16: Understanding Your Data - Looking for Difference: Student T-Test and Paired Samples T-Test Week 11 - 14/11/16: Understanding Your Data - Looking for Difference: Mann Whitney and Wilcoxon Week 12 - 21/11/16: Understanding Your Data - Looking for Difference: Chi-Squared Week 13 - 28/11/16: Understanding Your Data - Looking for Association: Correlation
Module Resources
Sessions for BML224 will be on Mondays. Specific learning outcomes for each session are provided in your statistics manual and are also detailed on the BML224 homepage on Moodle. Sessions will involve the use of a series of data files that can be downloaded from the BML224 homepage on Moodle. Please download these files into your own file space ready for use in the session.
Additional resources are also available and are detailed
throughout this manual. Activities and resources are signposted by a number of icons including:
This icon refers to class-based and self-directed activities. Details relating to activities are provided in your manual.
p. iii
Data Analysis for Research This icon relates to online simulations that have been developed to provide additional guidance on the use of SPSS. Each of the statistical tests covered in the manual has an accompanying simulation that you can access online. The weblink to these online simulations is available on the BML224 homepage on Moodle.
Self-Directed Activities
As part of the course, you will be asked to complete short tasks as part of the lecture session.
Specific tasks will be allocated on a
weekly basis. It is essential that these tasks are completed, in order to demonstrate your competency in the statistical methods that are being employed during the module. Please ensure that you read through the handouts provided thoroughly.
SPSS Software
The module will be using SPSS. You can get a copy of SPSS to install on your own PC/Mac from the library (free of charge!). This software will be licensed to you as long as you are at student at the University of Chichester. You are free to install SPSS on your own laptop and bring that to the weekly sessions.
p. iv
Data Analysis for Research
Assessment
The assessment for this module will focus primarily around a small quantitative research project, from which students will be asked to present a research briefing (30%; 1,050 word equivalent /
approximately 10 minutes per group) and a research poster (70%; 2,450 word equivalent). Research Project Working in small teams, students will be expected to develop a suitable research topic and design an on-line questionnaire. The research should be designed to demonstrate progression from basic to advanced statistical techniques, covering the key techniques covered in the module. Students will be asked to present a research /press briefing detailing a specific aspect(s) of their research methodology and related findings. Students will also be asked to present a supporting poster which will outline the overall themes and results of their wider research project. Students will then be invited to discuss and critically reflect on the research process as a part of the ‘live marking’ of their poster with the module tutor(s). The assessment criteria for research presentation/briefing: Evidence of clear research aims and objectives informed by background research Clear and logical structure of the presentation demonstrating progression from basic to advanced statistical techniques referencing a specific aspect of the research process/results Clear extrapolation of answers and analysis based on the use of the appropriate statistical techniques and the interpretation of SPSS output Ability to present results accurately, succinctly and to a high standard using appropriate formats and referencing conventions The assessment criteria for research poster: Evidence of clear research aims and objectives informed by background research Clear and logical structure of the poster demonstrating progression from basic to advanced statistical techniques referencing the entire research process/results Clear extrapolation of answers and analysis based on the use of the appropriate statistical techniques and the interpretation of SPSS output Ability to present results accurately, succinctly and to a high standard using appropriate formats and referencing conventions Quality of the demonstrated critical reflection of chosen research methodology and results as part of the ‘live marking’ of their poster with the module tutor(s)
p. v
Data Analysis for Research
Resit Information
The resit for this module will consist of a 3 hour practical examination. A pass on the module is based on your overall grade profile - therefore if you were to unexpectedly fail a specific element of the assessment if your overall grade profile was above 40% (including the fail) you would pass the module. Remember a non-submission in any part of the assessment would also result in the failure of the whole module. Additional details relating to the assessment for this module can be found in Guidance Booklet #2.
Submission Dates
Key dates for your diary:
- The research presentations will take place between Tuesday 13th
and Friday 16th December.
Regardless of the date and time of your presentation, all posters and completed presentations should be submitted by 1pm on Monday 12th December.
I can be found on the top of floor of the Dome on the Bognor Regis campus. If you have any problems please do not hesitate to come see us. While I am usually around, other University duties and external consultancy work does take me off campus from time to time. Therefore while you are welcome to pop in informally, please email myself to make an appointment (a.clegg@chi.ac.uk) to guarantee that we are in to see you. You can also contact me via Skype or Twitter - details are available on the Moodle homepage.
p. vi
Data Analysis for Research
Student Support
You will be introduced to a number of new concepts and techniques in this module. Statistics is not ‘everybody’s cup of tea’ and I am very conscious about what is called ‘statistics anxiety’. If at any time you are unclear about what we are doing, please do not hesitate to come and see us. The support materials for this module have been designed to make the everything as self-explanatory as possible. Please make time to read through the materials provided, and use the online simulations to enhance your familiarity with the different statistical techniques we will be using. The materials have been expanded and developed as a result of feedback from student evaluations. It is imperative that you read through all the materials provided and take responsibility for your own learning. Fail to do so could result in you failing this module.
Evaluation
At the end of the module, you will have the opportunity to complete a module evaluation form to comment on the overall structure, content and quality of the programme. The module evaluation for 2015 can be found on the BML224 homepage. If you have any immediate concerns about the quality of the module then please do not hesitate to come and talk to me directly. You can also make comments throughout the course of the module by using the comment and suggestion wall that has been embedded into the BML224 homepage.
Student Conduct
The University’s Commitment Charter (Section C) sets out the codes of behaviour that staff and students can expect from one another. Every member of the University community is expected to uphold the Charter commitments and to help to maintain a respectful and constructive learning environment for themselves and for others. In contact (class) time, and outside of it, the University expects you to show consideration towards other students and the staff of the University. In lectures, seminars and workshops it is your responsibility to avoid behaviour which distracts the learning process for yourself and others. Behaviours which may seem insignificant to you, such as whispering to friends, or texting during a seminar, are almost always noticed! They can have an accumulative, negative impact on the group and the tutor. Such behaviours signal lack of respect for others - even if this was not your intention.
p. vii
Data Analysis for Research To help illustrate these points, here are some behaviours that students and tutors have found distracting: •
Talking or whispering in lectures, outside times set aside for group discussion
•
Talking or whispering while other students are making points
•
Interrupting other students or the tutor while they are talking
•
Habitually arriving late or leaving early (without forewarning the tutor)
•
Sending and receiving texts
•
Mobile phones ringing
•
Using MP3 players
•
Playing electronic games
•
Surfing the net in class
Students whose behaviour disrupts a class persistently may be asked to leave the session. However we are sure that as adult learners you’ll use common sense and be willing to help create the best possible learning environment for everyone. Students often find statistical analysis rather difficult. Therefore considerable time and effort has gone into the design of learning and teaching materials. The sessions will be tutor-led to start, therefore students are asked to pay close attention to the instructions that are given. Please note: [1] I will not expect to see students using software other than that
being used in the session - no emailing, checking Facebook
or equivalent. Students infringing this request will be asked to leave the session.
[2] Please be punctual as there is considerable ground to cover in each of the weekly sessions. Evidence indicates that students who have a poor attendance record fail this module.
[3] Mobile phones should be switched off before the session. [4] This is a challenging module and you will need to concentrate.
I will need to try and help everybody through the session. This is not helped by constant chatting, as such any students
persistently talking or causing a distraction will be asked to leave the session.
p. viii
Data Analysis for Research [5] It is critical that any self-directed activities or quizzes are completed satisfactorily. Failure to complete weekly tasks
will result in you being excluded from sessions until these activities are completed. Please note that I can monitor
completion via Moodle, and I will contact students that are not
engaging with resources. Failure to engage with the module resources will ultimately result in you failing the module.
Attendance
Students are reminded that attendance at all modules is compulsory. If you miss a session, for whatever reason, you should complete and submit a student absence form to the admin office. It is also courteous to let the module tutor know of any absence in advance or immediately after the session that was missed. This should be completed as soon as possible from the date of absence. You are reminded that persistent absence can potentially result in your de-registration from the module. The full University regulations regarding attendance can be found in your student handbook. You are also asked to arrive punctually for your lectures. Students that are persistently late will be marked as absent. If you do miss a session for BML224 is it imperative that you read through the lecture notes and complete all set tasks. If you fail to do this you will find yourself falling behind, and unable to follow activities undertaken during the sessions. I will not be repeating material in the session for those that have lost their way through non-attendance. For reference, students that tend to fail this module do so because of a lack of attendance and engagement. You are
also advised that student engagement with tasks is monitored closely via Moodle, and any student persistently shown to be not engaging will be asked to attend a meeting with the module tutor to explain their lack of academic endeavour.
p. ix
Data Analysis for Research
Group Details
Group No:
Group Name Group Members
Name
Contact Details
Research Title
Research Objectives
Note your research objectives here:
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Data Analysis for Research
Indicative Reading
Keep a note of your background reading here:
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