Module MATH1541: STATISTICS

Department: MATHEMATICAL SCIENCES

MATH1541: STATISTICS

Prerequisites

• Normally, A level Mathematics at grade C or better, or equivalent.

Corequisites

• None.

Excluded Combination of Modules

• Foundation Mathematics (MATH1641) may not be taken with or after this module; Data Analysis, Modelling and Simulation (MATH1711) may not be taken before, with or after this module.

Aims

• The module is designed to be a first statistics course, suitable for all students satisfying the entrance requirements.
• No prior statistical knowledge is assumed.
• The emphasis is upon the understanding of real-life statistical problems, and develops the basic concepts and statistical methods by example.
• Most practical sessions are devoted to computing with a statistical package to apply and illustrate the material presented in lectures.

Content

• Sources of data.
• Descriptive statistics.
• Exploring two-variable relationships.
• Methods for more than two variables.
• Data analysis topics.
• Probability.
• Random variables.
• Inference.
• Confidence intervals and hypothesis testing.
• Inferences for means of Normally distributed populations.
• Inference for relationships.
• Methods of categorical data.
• Distribution-free methods.

Learning Outcomes

• By the end of the module students will: be able to solve a range of predictable or less predictable problems in statistics.
• have an awareness of the basic concepts of theoretical mathematics in the field of statistics.
• have a broad knowledge of the basic understanding of these subjects demonstrated though one or more of the following topic areas: Principles of data collection.
• Basic analysis of variance and multiple regression.
• computing for data analysis.
• Probability, random variables and statistical inference.
• an introduction to confidence intervals and hypothesis testing.
• Parametric and nonparametric procedures for common applications.

• students will have basic mathematical skills in the following areas: Modelling, computation.
• students will have basic skills in exploratory data analysis.

• students will have basic problem solving skills.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Lectures demonstrate what is required to be learned and the application of the theory to practical examples.
• Tutorials provide the practice and support in applying the methods to relevant situations as well as active engagement and feedback to the learning process.
• Summative weekly coursework provides an incentive for students to consolidate the learning of material as the module progresses (there are no higher level modules in the department of Mathematical Sciences which build on this module). It serves as a guide in the correct development of students' knowledge and skills, as well as an aid in developing their awareness of standards required.
• The end-of-year written examination provides a substantial complementary assessment of the achievement of the student.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

45 minute collection paper in the first week of Epiphany term.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University