# MATH08005 2019 Statistics

### General Details

Full Title
Statistics
Transcript Title
Statistics
Code
MATH08005
Attendance
N/A %
Subject Area
MATH - Mathematics
Department
MENG - Mech. and Electronic Eng.
Level
08 - NFQ Level 8
Credit
05 - 05 Credits
Duration
Semester
Fee
Start Term
2019 - Full Academic Year 2019-20
End Term
9999 - The End of Time
Author(s)
Paul Curran
Programme Membership
SG_EADVA_E08 201900 Level 8 Certificate in Engineering in Advanced Lean Sigma Quality SG_EPOLY_K08 201900 Bachelor of Engineering (Honours) in Polymer Processing SG_EQLTY_K08 201900 Bachelor of Science (Honours) in Engineering in Quality Management and Tech SG_EPOLP_K08 202200 Bachelor of Engineering (Honours) in Polymer Process Engineering
Description

The student should be able to have a foundation in statistical analysis and be able to manipulate statistical data.

### Learning Outcomes

On completion of this module the learner will/should be able to;

1.

Summarise, describe data and identify the position of a data value in a dataset.

2.

Determine the probability of an event using probability rules.

3.

Calculate the probability for outcomes using discrete and continuous distributions.

4.

Calculate confidence intervals for population mean, proportion and variance.

5.

Perform hypothesis testing using parametric and nonparametric tests.

6.

Make decisions and draw conclusions on the basis of statistical analysis.

### Teaching and Learning Strategies

The teaching strategy will be through the use of on-line lectures and tutorials with assessments timed to co-incide with the end of delivery of a particular topic so as to re-enforce  and embed the knowledge of the material with the student.

### Module Assessment Strategies

Assessment will be performed throughout the academic period through assignments and mini-examinations. There will be a final examination at the end of the academic period.

### Repeat Assessments

Repeat assessment will be by way of sitting another examination on the subject. Alternatively, at the discretion of the lecturer, assignments covering the deficient areas of the course may be set.

### Indicative Syllabus

1. Descriptive Statistics: Measures of Central Tendency and Measures of Dispersion, Sampling. Use of corresponding statistical functions in Excel/statistical software.
2. Laws of Probability: Addition Rule, Multiplication Rule, Conditional Probability, Bayes's Theorem
3. Discrete Probability Distributions: Binomial, Poisson, Geometric and Hypergeometric distributions. Use of statistical software to calculate probability distributions.
4. Continuous Probability Distributions: Uniform, Normal and Exponential distributions. Normal distribution as approximation to Binomial. Central Limit Theorem. Use of statistical software to calculate probability distributions.
5. Estimation: Point estimation and confidence intervals. Confidence intervals for population mean. T Distribution. Confidence Intervals for a population proportion. Determining sample size. Confidence Intervals for a population variance.  Distribution. Use of statistical software to develop confidence intervals.
6. Hypothesis Testing: Fundamentals, Testing a claim about a mean, proportion, standard deviation or variance. P-values. Use statistical software to perform hypothesis testing.
7. Inference from Two Samples: Inference about two means, independent samples and matched pairs. Inference about two proportions. Comparing variation in two samples. F Distribution. Use of statistical software to perform corresponding test.
8. Chi Squared Tests: Goodness of Fit Testing, Contingency Tables
9. Nonparametric Statistics: Sign test, Wilcoxon test.

### Coursework & Assessment Breakdown

Coursework & Continuous Assessment
20 %
End of Semester / Year Formal Exam
80 %

### Coursework Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 Assignment Continuous Assessment UNKNOWN 20 % OnGoing 1,2,3,4,5,6

### End of Semester / Year Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 Final Exam Final Exam UNKNOWN 80 % End of Term 1,2,3,4,5,6

Type Location Description Hours Frequency Avg Workload
Lecture Not Specified Lecture 2 Weekly 2.00
Tutorial Not Specified Tutorial 2 Weekly 2.00
Total Full Time Average Weekly Learner Contact Time 4.00 Hours

Type Location Description Hours Frequency Avg Workload
Lecture Not Specified Lecture 2 Weekly 2.00
Tutorial Not Specified Tutorial 2 Weekly 2.00
Total Part Time Average Weekly Learner Contact Time 4.00 Hours

### Required & Recommended Book List

Elementary Statistics: A Step by Step Approach McGraw Hill

Probability and Statistics for Engineers and Scientists Pearson 2014-02 Statistics for Engineers and Scientists
ISBN 1259251608 ISBN-13 9781259251603

This title stands out for its crystal clear presentation of applied statistics. Suitable for a one or two semester course, the book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work.

### Module Resources

Non ISBN Literary Resources

Journal Resources

N/A

URL Resources

N/A

Other Resources

None