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Engineering Mathematics 6

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Department: ManufacturingEngineering

Module Code: MATH71004

Level: Level 7 Contact Hours: 48

Duration: 1 Semester Directed Study Hours: 24

Effective Term: 2010/11 Indep. Study Hours: 28

Credits: 5

Prerequisite Knowledge:

Engineering Mathematics 1

Module Description/Aims:

The module is designed to ensure that students will have appropriate skills tointerpret numerical and graphical information and describe data appropriately.It is intended to enable students to solve problems and make decisions basedon logical impartial statistical tests in engineering and in further research

Contact Type Hours

Lecture 2 Per Week

Practical/Workshop 1 Per Week

Tutorial 1 Per Week

On successful completion of the module, the learner will be able to:

No. Description/Learning Outcomes

1 Define and use in their proper context key statistical terms (statistics,variables, populations, samples, data types and levels, hypothesis, standarderror, p values etc.)

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2 Explain the distinction between descriptive and inferential statisticaltechniques.

3 Describe, explain and compare sets of data using various diagrams, tablesand graphs

4 Effectively use hypothesis tests and regression and correlation for decisionmaking

5 Use IT (eg statistical mode on calculator, spreadsheet eg Microsoft Excel,Statistical packages eg SPSS) to present data and for calculations requiredfor statistical tests and interpret findings

Learning Strategies

The student will engage with the content of the module through a mixture of lecture, tutorial and practical work.
Acknowledging the perceived difficulty of statistics this module will contextualise core content to their field of studythroughout and apply the content to real life problem solving situations.
Theapproach will make use of context-specific problem based worksheets for studentsto practice the procedures.

Content Detail

DescriptiveStatistics

Design of Experiments, Presentation of Data, Exploratory DataAnalysis (Measures of Central Tendency, Dispersion, Graphicrepresentation of data, percentiles and percentile groupings,frequency distributions

StandardNormalDistribution

Introduction to standard normal distribution (SND): Z scores, areaproperties of the SND, probability, sampling error, Standard Error of Mean

HypothesisTestingconcepts

Confidence intervals, p values, the studentized t distribution, degreesof freedom and t tests

InferentialStatistics

Confidence Intervals for population means, hypothesis testing with 1and 2 sample(s), Correlation and Regression, Pearson• s `r•correlation coefficient

Assessment Strategies

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A variety of assessment methods should be employed including short answer, openended, closed questions in task sheets, tests and assignments.

A computer laboratory assessment will be undertaken.

Repeat Assessment strategy will consist of repeating the written examination for themodule at the next available sitting. This result will be combined with the existingCA result.

LearningOutcome

Assessment

Category Assessme nt Method

Additional

Information

%

alloc

3, 5 ContinuousAssessment

Project - Individual 20

3, 4, 5 Continuous

Assessment

Computer based -

Individual

20

1, 2, 3, 4 Final Exam(Scheduled)

Final Written Exam 60

Type ISBN Title Author Publisher Year EditionLibrary

Link

Recommended 0861219805 Understanding StatisticsJ. ReillyFolens

1997 -

Essential 0201614774 Elementary Statistics 9edMario E. Triola Addison-Wesley

2003 -

Type Description

Course Material Mathematics and Statistics Resources Module onBlackboard

Website www.mathcentre.co.uk

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Curricular information is subject to change
http://www.mathcentre.co.uk/

Documents

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