KC7021 - Statistics and Business Intelligence

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What will I learn on this module?

The aim of the module is to provide you with the knowledge and practical skills for applying modern analytical techniques to business data. The module combines both theoretical and practical approaches so that you will have the skills to tackle problems in various realistic business settings.

This module is primarily concerned with examining and analysing (big) data arising from business(es) and to relate the extracted information to strategic, tactical and operational decision-making in organisations. You will covers topics such as:

• Data processing and big data
• Exploratory data analysis
• Probability and distributions
• Hypothesis testing
• Correlation and regression analysis
• Classification
• Distance measures
• Clustering

How will I learn on this module?

Full-time students: The module includes a combination of methods to support learning, including lectures and computer assisted seminars, tutor feedback and independent directed and self-directed learning to allow you to put the theory into practice. Topics will normally be introduced in lectures and explored through real world examples and practical exercises (helping you to develop the knowledge and understanding needed) and guided learning activities. You will be encouraged to develop independent learning skills to explore further in the subject area.

Distance learning students: The module includes a combination of methods to support learning, including lecture slides/notes, independent directed and self-directed learning to allow you to put the theory into practice, and tutor feedback provided through online discussions. Topics will normally be introduced in slides/notes provided and explored through real world examples and self-learning practical exercises and guided learning activities. You will be encouraged to explore further in the subject area. You will also learn at work, through reflecting on your experiences and applying your knowledge from the module to your practice in the workplace.

How will I be supported academically on this module?

Full-time students: You will be given advice and feedback on your work and progress during the timetabled classes and workshops. In addition, the eLP (electronic learning portal module) blackboard will be used to provide extensive support materials.

Distance learning students: You will be given advice and feedback on your work and progress in a time slot(s) mutually discussed with all the students and through discussions via email/blackboard forum and independent directed learning. In addition, the eLP (electronic learning portal module) blackboard will be used to provide extensive support materials.

What will I be expected to read on this module?

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

What will I be expected to achieve?

Knowledge & Understanding:

1. A critical understanding of key aspects of statistics and business intelligence techniques for forecasting future trends and business growth

2. Application of appropriate techniques for understanding and exploring business data and how it can be exploited for decision making

Intellectual / Professional skills & abilities:

3. Apply different statistics and business intelligence techniques to complex real world business environment having to deal with and exploit huge volumes of data

4. Critically evaluate and critically reflect on solving real life business problems using suitable exploratory data analysis techniques and algorithms

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):

5. Build an awareness of legal, cultural and ethical issues surrounding analysis, exploration and dissemination of data

How will I be assessed?

Assessments: A written assignment.

• The coursework assessment will comprise analysis of data by using appropriate statistical and business intelligence techniques for understanding and exploring business data and solving business decision problems (100%) and will test MLOs 1, 2, 3, 4 and 5.

Feedback: You will be given detailed feedback on the assignment clearly identifying both the weaknesses and strong points of the work.

Pre-requisite(s)

None

Co-requisite(s)

None

Module abstract

The aim of the module is to provide you with the knowledge and practical skills for applying modern analytical techniques to business data. The module combines both theoretical and practical approaches so that you will have the skills to tackle problems in various realistic business settings. This module is primarily concerned with examining and analysing (big) data arising from business(es) and to relate the extracted information to strategic, tactical and operational decision-making in organisations. The module adopts a research tutored approach which focuses the learning and teaching activities on current research issues related to the subject and subsequent skillset required by potential employers. The subject is structured around research active staff within the area with a secure knowledge of personal development planning and employability.

What will I learn on this module?

The aim of the module is to provide you with the knowledge and practical skills for applying modern analytical techniques to business data. The module combines both theoretical and practical approaches so that you will have the skills to tackle problems in various realistic business settings.

This module is primarily concerned with examining and analysing (big) data arising from business(es) and to relate the extracted information to strategic, tactical and operational decision-making in organisations. You will covers topics such as:

• Data processing and big data
• Exploratory data analysis
• Probability and distributions
• Hypothesis testing
• Correlation and regression analysis
• Classification
• Distance measures
• Clustering

Course info

UCAS Code G408

Credits 20

Level of Study Undergraduate

Mode of Study 4 years full-time or 5 years with a placement (sandwich)/study abroad

Department Computer and Information Sciences

Location City Campus, Northumbria University

City Newcastle

Start September 2019 or September 2020

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