Introduction to Statistics

Module title	Introduction to Statistics
Module code	INT1003
Academic year	2018/9
Credits	15
Module staff	Michael Samuel Hughes (Convenor)

Duration: Term	1	2	3
Duration: Weeks	0	12	0

Number students taking module (anticipated)	150

Description - summary of the module content

Module description

Statistics inform decision makers in all areas of society, for example, Government policymakers, investment planners, business managers, education providers or healthcare managers. In this module you will learn how to summarise and analyse data, test hypotheses and find relationships between different features in a business context. You will learn how to use statistics to draw conclusions, make sensible business decisions and justify your decisions in your business presentations.

This module is the equivalent of BEE 1022. No prior knowledge of statistics is assumed for this module.

Module aims - intentions of the module

This module is an introduction to the basic concepts of statistics and will give a strong foundation to the statistics that will be continued in the second year of a business degree. It will provide students with an understanding of the statistical methodologies used in economics, in the business and management environments, and also other disciplines of study. A combination of theoretical and extensive hands-on practice is used, using Excel software with a variety of data types and statistical methods.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

1. Compute and graph salient features of experimental and survey data, manually and using a computer
2. Carry out a hypothesis test in a variety of contexts
3. Calculate basic statistics and use them to compare data sets
4. Apply certain parametric and non-parametric statistical tests
5. Interpret the results of certain statistical tests in a variety of situations
6. Fit and interpret bivariate and multivariate regression models
7. Demonstrate the ability to utilise a software package (Excel) for a range of statistical applications

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

8. Apply some fundamental statistical methods
9. Analyse data and draw conclusions from it
10. Calculate and interpret statistical parameters

ILO: Personal and key skills

On successfully completing the module you will be able to...

11. Use IT effectively
12. Demonstrate written communication skills
13. Present information in different formats

Syllabus plan

· Introduction to Statistics, Scales of measurement.

· Descriptive Statistics: Frequency Tables, Frequency Distributions.

· Descriptive Statistics: Numerical Measures.

· Descriptive Statistics: Graphical Methods.

· Discrete and continuous random variables.

· Discrete and continuous probability distributions.

· Classical probability concepts.

· Sampling Methods and the Central Limit Theorem.

· Estimation and Confidence Intervals.

· One-Sample and Two-Samples Tests of Hypothesis.

· Analysis of Variance.

· Correlation and Linear Regression.

· Multiple Regression.

Nonparametric Methods: Goodness-of-Fit Tests.

Learning and teaching

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching Activities	Guided independent study	Placement / study abroad
64	86	0

Details of learning activities and teaching methods

Category	Hours of study time	Description
Scheduled learning and teaching activities	24	Lectures (2 x 1Hr)
Scheduled learning and teaching activities	36	Seminar these will be teacher led. You should prepare for each seminar based on the related lecture
Practical	4	Practice applying methods to simulated situations.
Study Clinic	8	Optional sessions to reinforce key skills
Guided Independent Study	78	Reading and research, practice of techniques, web-based activities

Assessment

Formative assessment

Form of assessment	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
4 case studies	1 hour each	1-13	Written

Summative assessment (% of credit)

Coursework	Written exams	Practical exams
20	80	0

Details of summative assessment

Form of assessment	% of credit	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Examination	80	2 hours	1-6,8-10, 12-13	Written
Coursework assessments	20	20 hours in total	1-13	Written & online

Re-assessment

Details of re-assessment (where required by referral or deferral)

Original form of assessment	Form of re-assessment	ILOs re-assessed	Timescale for re-assessment
Examination	Written examination	1-6, 8-10, 12-13	2 weeks after original exam

Re-assessment notes

The pass mark for award of credit in this module is 40%. Referral or deferral is a process whereby a further attempt at the module examination, following an initial failure, is permitted without the requirement to repeat any attendance. This will constitute a second formal examination – coursework will not be included in the re-assessment. Resubmission of coursework is impractical for two reasons; coursework answers and feedback are given to students after marking, and some coursework is assessing IT skills which cannot be measured by the examination process.

All summative coursework must be completed before entitlement to a referral or deferral.

The grade for the re-assessment, and therefore the module grade, will be capped at 40%.

Resources

Indicative learning resources - Basic reading

Lind, D. A., Marchal, W. G. & Wathen, S. A. (2013). Basic Statistics for Business & Economics (8^th Ed.). New York: McGraw Hill Irwin.

Indicative learning resources - Web based and electronic resources

Course Lectures and worklog is available through ELE in addition to online assessments.

http://vle.exeter.ac.uk/course/view.php?id=3291

Online exercises associated with Course textbook. http://connect.mcgraw-hill.com

Module has an active ELE page

Indicative learning resources - Other resources

Other resources, through both self research and those presented or referenced to by the lecturer

Key words search

Statistics business measurement percentages pie charts tables descriptive diagrams calculating correlation regression logarithms time charts average trends deterministic sampling distribution mean confidence intervals normally probabilities testing

Credit value	15
Module ECTS	7.5
Module pre-requisites	None
Module co-requisites	None
NQF level (module)	4
Available as distance learning?	No
Origin date	16/05/08
Last revision date	02/08/2013