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August 2019

Statistical Practice I (Life Sciences)

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Statistical ideas and methods are essential tools in virtually all areas that rely on data to make decisions and reach conclusions. This includes diverse fields such as science, technology, government, commerce, manufacturing and the life sciences. In broad terms, statistics is about getting information from data. This includes both the important question of how to obtain suitable data for a given purpose and also how best to extract the information, often in the presence of random variability. This course provides an introduction to the contemporary application of statistics to a range of real world situations. It has a strong practical focus using the statistical package SPSS to analyse real data relevant to the life sciences.


To introduce and practise a methodology of scientific problem-solving; To develop your ability to plan simple experiments and surveys; To enable you to recognize the appropriate techniques for the analysis of a variety of experimental and observational studies; To present Statistics as a coherent discipline in its own right; To provide a sound preparation for those intending to continue with the more theoretical and mathematical study of Statistics at Levels II and III; To provide a suitable grounding in Statistics for those who are continuing in other fields and who may need to use Statistics in later experimental studies. By the end of this subject, students should be able to: construct stemplots, boxplots and summary measures from a set of data, describe a distribution in terms of location, spread and shape, togehter wi th an assessment of outliers and Normality, describe and use the principles of experimental design, including control, randomisation, blocking and replication, and perform simple randomisations, understand the terms sample and population, statistics and parameters, and know the basic ideas of sample surveys, know and use the basic rules of probability, calculate means and variances for simple discrete random variables, calculate probabilities using Normal tables, and apply this to the Normal a pproximation to the Binomial distribution, know and apply the Central Limit Theorem, write down null and alternative hypotheses, apply the appropriate test for a one-sample test, a paired t-test and a two-sample t-test, determining the P-va lue and drawing the appropriate conclusions, fit a straight line to a set of data, interpret the result, perform test of significance on the slope, perform a one-sample and a two-sample test for proportions, interpret two-way tables and test for appropriate hypotheses in such tables.


Topics covered are: organisation, description and presentation of data in the life sciences; design of experiments and surveys; random variables, probability distributions, the binomial distribution and the normal distribution; statistical inference, tests of significance, confidence intervals; inference for means and proportions, one-sample tests, two independent samples, paired data, t-tests, contingency tables; analysis of variance; linear regression, least squares estimation, residuals and transformations, inference for regression coefficients, prediction.

Sue Middleton
Lecturer for this course

Graduate attributes

Linkage future

All students completing this subject can go on to Statistical Practice I. For students who have also done Mathematics I or Mathematics IM, other Level II Statistics subjects are available.

Recommended text

Moore, D. S. & McCabe, G. P. (1997).Introduction to the practice of statistics. 3rd Ed Freeman. The book is available at Unibooks (the campus bookshop) and will bereferred to from now on as MM. The course will follow the textbook andyou should have your own copy. There are also copies available onReserve in the library. You should read ahead in MM aspreparation for the lectures.Moore & McCabe will also be useful in Level II Statisticssubjects, particularly Statistical Practice II.