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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/