# MATH07025 2013 STATISTICS AND COMPUTING

**Full Title**

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**Code**

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**Subject Area**

**Department**

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**End Term**

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**Description**

This course introduces the student to descriptive statistics, probability and probability distributions and statistical inference. The student will also be introduced to the use of an appropriate computing package to perform statistical analysis of data.

### Learning Outcomes

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

**1.**

Graphically display and numerically summarise data using methods of descriptive statistics.

**2.**

Apply probability and probability distributions to data analysis.

**3.**

Choose and apply appropriate test of hypotheses.

**4.**

Use regression methods to analyse relationships between variables.

**5.**

Use Microsoft Excel (or an equivalent statistical program) to perform statistical analysis of data

### Module Assessment Strategies

Assessment of this module will include continuous assessment worth 50% and an end of semester exam worth 50%. The end of semester exam will be employed to assess student's knowledge of statistics. Continuous assessment is designed to give the student an in-depth understanding and knowledge of the capabilities of Microsoft Excel for statistical analysis of data and will include weekly computer based activities/tasks and in-class test assignments.

### Module Dependencies

**Prerequisites**

**Co-requisites**

**Incompatibles**

### Indicative Syllabus

**Descriptive Statistics **

Types of data, graphical representation of data. Measurements of central tendency, dispersion and skewness.

**Probability **

Laws of probability, algebra of events, mutually exclusive events, independent events.

**Probability Distributions **

Continuous and discrete distributions: binomial, Poisson and normal, use of tables.

**Sampling theory **

Sampling theory, estimation, point and interval estimates.

**Tests of hypothesis **

Tests of sample means and sample proportions, z tests and t tests. Chi-squared tests.

**Correlation and Regression **

Calculation of Correlation coefficient and its significance, Tests for linearity of calibration data; analysis of residuals for linearity testing.

**Experimental Design**

Random allocation of samples in a study, bias, response bias and use of controls; sampling; summarising data; The partial factorial design for testing ruggedness/robustness of an experiment.

### Coursework & Assessment Breakdown

**Coursework & Continuous Assessment**

**End of Semester / Year Formal Exam**

### Coursework Assessment

Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
---|---|---|---|---|---|---|

1 | Weekly activities in practicals in computer lab. | Continuous Assessment | UNKNOWN | 25 % | OnGoing | 1,2,3,4,5 |

2 | Continuous Assessment 1. | Continuous Assessment | UNKNOWN | 10 % | Week 6 | 1,2,3,4,5 |

3 | Continuous Assessment 2. | Continuous Assessment | UNKNOWN | 15 % | Week 12 | 1,2,3,4,5 |

### End of Semester / Year Assessment

Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
---|---|---|---|---|---|---|

1 | End of Term Exam. | Final Exam | UNKNOWN | 50 % | End of Term | 1,2,3,4 |

### Full Time Mode Workload

Type | Location | Description | Hours | Frequency | Avg Workload |
---|---|---|---|---|---|

Lecture | Tiered Classroom | Lecture | 2 | Weekly | 2.00 |

Laboratory Practical | Computer Laboratory | Laboratory Practical | 1 | Weekly | 1.00 |

Independent Learning | UNKNOWN | Self Study | 4 | Weekly | 4.00 |

### Module Resources

**Non ISBN Literary Resources**

Reilly, James (2006), Using Statistics, Gill & Macmillan

Owen, Frank (1994), Statistics, Prentice Hall

Bluman, Allan (2007), Elementary Statistics, McGraw Hill

**Other Resources**

Resources presented on Moodle

Exam centre for end of term exam

**Additional Information**

None