## LUBS2670 Statistics for Business and Economics 2

### 10 creditsClass Size: 280

Module manager: Dr Luisa Zanchi
Email: L.Zanchi@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2017/18

### Pre-requisites

 LUBS1280 Mathematical Economics

This module is not approved as a discovery module

### Module summary

The module covers intermediate-level elements of mathematical statistics. It requires you to have a good background in introductory statistical techniques and an interest in quantitative subjects. The focus is on the application of statistical theory to the solution of practical problems. The module provides essential tools to deal with the quantitative issues arising in most social sciences. Statistical theory and problem solving techniques at intermediate level form a necessary basis to extend learning in a variety of disciplines within the social sciences, including accounting, finance, economics, econometrics and management. The emphasis is on the application of theory to practical problems in the social sciences.

### Objectives

Building on the knowledge of introductory statistics acquired at level 1, the module aims to provide students with knowledge of essential techniques in mathematical statistics at intermediate level. These techniques address key concepts in the analysis of continuous random variables, bivariate probability theory and bivariate inferential statistics. Studentâ€™s key learning is attained through the solution of quantitative exercises that apply these concepts.

Learning outcomes
Upon completion of this module students will be able to:
- Identify and outline the statistical theory of continuous random variables, bivariate probability distributions and bivariate inferential procedures
- Recognise contexts in accounting, finance, economics, econometrics and management in which intermediate-level concepts in mathematical statistics can be usefully employed
- Interpret and appraise the literature in accounting, finance, economics, econometrics and management that utilises intermediate-level techniques in mathematical statistics

Skills outcomes
Upon completion of this module students will be able to:
Transferable
- Apply analytical ability to problem solving in different contexts
- Apply time management skills in work planning

Subject Specific
- Analyse quantitative issues in the social sciences involving intermediate-level concepts in mathematical statistics
- Apply knowledge of intermediate-level techniques in mathematical statistics to solve problems in accounting, finance, economics, econometrics and management

### Syllabus

Indicative content
- Expected values
- Univariate probability distributions of continuous random variables
- Bivariate probability distributions
- Sampling distributions
- Estimators
- Bivariate interval estimation
- Bivariate hypothesis testing

### Teaching methods

 Delivery type Number Length hours Student hours Example Class 9 1.00 9.00 Office Hour Discussions 20 1.00 20.00 Supervised Practice 1 1.00 1.00 Lecture 16 1.00 16.00 Private study hours 54.00 Total Contact hours 46.00 Total hours (100hr per 10 credits) 100.00

### Private study

- 1 hour reading per lecture: 15 hours
- 2 hours reading and preparation of homework per class: 16 hours
- Revision for mid-term test: 5 hours
- Examination revision: 18 hours.

### Opportunities for Formative Feedback

Students are given the opportunity to submit 7 pieces of homework related to the examples sessions, which will be marked weekly throughout the course. Written solutions to the examples will be available from the module area of the VLE after each example session.

There will also be a compulsory mid-term test in week 7, followed by a feedback session in week 9. Written solutions to the mid-term test will be available from the module area of the VLE after the feedback session.

### Methods of assessment

Exams
 Exam type Exam duration % of formal assessment Standard exam (closed essays, MCQs etc) 2 hr 00 mins 100.00 Total percentage (Assessment Exams) 100.00

Resit will be 100% by exam.