KC4020 - Probability and Statistics

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What will I learn on this module?

This module is designed to introduce you to the important areas of Statistics. In this module, you will learn about data collection methods, probability theory and random variables, hypothesis testing and simple linear regression. Real-life examples will be used to demonstrate the applications of these statistical techniques. You will learn how to use R to analyse data in various practical applications.

Outline Syllabus
Data collection: questionnaire design, methods of sampling - simple random, stratified, quota, cluster and systematic. Sampling and non-sampling errors. Random number generation using tables or calculator.

Population and sample, types of data, data collection, frequency distributions, statistical charts and graphs, summary measures, analysis of data using R.

Probability: sample space, types of events, definition of probability, addition and multiplication laws, conditional probability. Discrete probability distributions including Binomial, Poisson. Continuous probability distributions including the Normal. Central Limit Theorem. Mean and variance of linear combination of random variables. Use of Statistics tables.

Hypothesis tests on one and two samples, confidence intervals using the normal and Student t distributions.

Correlation and simple linear regression.

How will I learn on this module?

You will learn through a series of formal sessions including both lectures and seminars. During lectures, main concepts with suitable applications/examples are introduced. Seminars allow you to gain experience in applying concepts introduced in lectures through working on practical questions. All the seminars will be scheduled in our modern computer laboratories, enabling you to apply the techniques and deepen your understanding of the material and develop your practical skills. This, in turn, develops your confidence to explore the subject area further as an independent learner outside the classroom.

Formative feedback is available weekly in the classes as you get to grips with new techniques and solve problems. In addition, we operate an open door policy where you can meet with your module tutor to seek further advice or help if required. Your ability to select appropriate techniques to solve practical problems is assessed in a 3-hours exam at the end of the module covering all Module Learning Outcomes.

General feedback on assessments will be given in class and individual feedback will be written on scripts. An opportunity to discuss work further will be available on an individual basis when work is returned and also through the open door policy.

How will I be supported academically on this module?

Direct contact with the teaching team during the formal sessions will involve participation in both general class discussions as well as one to one discussions during the hands-on part of the formal sessions. This gives you a chance to get immediate feedback pertinent to your particular needs in this session. Further feedback and discussion with the teaching team are also available at any time through our open door policy. In addition, all teaching materials and supplementary material (such as relevant journal articles and news) are available through the e-learning portal.

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. Apply and appraise procedures for data collection;
2. Perform an appropriate hypothesis test within a given context;

Intellectual / Professional skills & abilities:
3. Compute and interpret probability statements to tackle real-life problems;
4. Construct simple linear regression to quantify a statistical relationship between variables.

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
5. Analyse data arising from practical problems in health and social sciences using appropriate statistical techniques, interpret and communicate results to general audiences.
6. Work in group, share knowledge and responsibilities, effective time management

How will I be assessed?

SUMMATIVE
Group work presentation (20%)- 1,2,3,4,5,6
Examination (80%) – 1, 2, 3, 4, 5

FORMATIVE
Seminar problems – 1, 2, 3, 4, 5

Formative assessment will be available on a weekly basis in the formal sessions through normal lecturer-student interactions, allowing them to extend, consolidate and evaluate their knowledge.

Formative feedback will be provided on student work and errors in understanding will be addressed reactively using individual discussion. Solutions for laboratory tasks will be provided after the students have attempted the questions, allowing students to receive feedback on the correctness of their solutions and to seek help if matters are still not clear.

Pre-requisite(s)

N/A

Co-requisite(s)

N/A

Module abstract

‘Probability and Statistics’ will equip you with the fundamental and essential statistical techniques and will enable you to solve real-life statistical problems using appropriate statistical software. In ‘Statistics’, you will gain both the theoretical understanding of a wide range of statistical techniques and experience in applying these techniques in practical situations.

This module comprises of both lectures, where main concepts with suitable applications/examples are introduced, and regular seminars, which allow you to gain experience in applying concepts introduced in lectures through working on practical questions. You will be assessed by a mid-term group work presentation (20%) a final examination (80%).

‘Probability and Statistics’ will enhance your employability, providing you with a sound foundation in statistics, which is required for working in various industry sectors as well as for your future study.

Course info

UCAS Code G101

Credits 20

Level of Study Undergraduate

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

Department Mathematics, Physics and Electrical Engineering

Location City Campus, Northumbria University

City Newcastle

Start September 2020

Fee Information

Module Information

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