Unit name | Elementary Statistics |
---|---|

Unit code | MATH10510 |

Credit points | 10 |

Level of study | C/4 |

Teaching block(s) |
Teaching Block 2D (weeks 19 - 24) |

Unit director | Dr. Chen |

Open unit status | Open |

Pre-requisites |
GCSE Mathematics Grade C or better |

Co-requisites |
None |

School/department | School of Mathematics |

Faculty | Faculty of Science |

This unit provides a short introduction to the aspects of statistics of most interest and importance to scientists. It is a stand-alone unit but the same material is available as part of the 40cp units in Mathematics 1AS and Mathematics 1ES.

**Aims:**

To introduce some basic ideas of statistics as useful tools for science students.

**Syllabus**

Probability:

The use of probability in everyday life and in scientific modelling. Exploratory methods: plotting data, structure exposed by suitable plots, log-log plots, outliers.

Probability models:

Use of probability to model observed phenomena. Discrete variables: The Binomial distribution, the Poisson distribution Continuous variables: The Normal distribution: its uses and misuses.

Inference:

Hypothesis testing and confidence intervals: What is a p-value? One- and two-sided tests. Standard errors. One and two sample t-tests, One-way Analysis of Variance.

Regression:

Dependence and independence. Linear regression and correlation. Percentage of variability explained.

**Relation to Other Units**

This is a stand-alone 10cp unit on statistics. The same material is available as part of the 40 credit-point units Mathematics 1AS and Mathematics 1ES and of the 20 credit-point unit Mathematics 1FS

At the end of the unit students should:

- have an insight into the value, use and interest of statistical methods in scientific work and thought

- be able to apply simple statistical methods in their own scientific work, and to understand what they are doing

- be able to understand the statistical jargon used in scientific papers.

Transferable Skills:

Increased skills in handling data (numeracy skills).

IT skills developed through use of R programming language.

3 lectures per week plus a computer laboratory practical session using Excel and the R programming language. Marked work is returned to the students and difficulties explained in the tutorials. Attendance at the practicals is compulsory. See the section Award of Credit Points below.

To pass the unit your final assessment mark must be 40 or over. This assessment mark will be made up from four practical Statistics assignments:

Assignment 1 gives 20% of the mark. Assignment 2 gives 25% of the mark. Assignment 3 gives 25% of the mark. Assignment 4 gives 30% of the mark. Each week's assignment is to be handed in the following week that the assignment is set. Assignments handed in late will receive reduced or no marks.

There may be good reasons, such as illness, for handing in work late or not attending the required practical classes: you must provide evidence, such as a doctor's note, in order for marks to be awarded in such cases.

**September Examinations**

If you fail Elementary Statistics in June, you may (depending on which Faculty you are in and how you have done in your other units) be allowed to resit it in September by taking a practical assessment.

Recommended but not required: Gerald Keller, Applied Statistics with Microsoft Excel, published by Duxbury.

You might also find this useful: Bruce E. Trumbo, Learning Statistics with Real Data, Duxbury