Statistical Practice I (Life Sciences)
Go to this course in the University Course Planner.
Description
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.
Objective
To introduce and practise a methodology of scientific
problemsolving;
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 onesample test, a paired ttest and a twosample ttest,
determining the Pva 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 onesample and a twosample test for proportions,
interpret twoway tables and test for appropriate hypotheses in such
tables.
Content
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, onesample tests, two independent samples, paired data, ttests, contingency tables; analysis of variance; linear regression, least squares estimation, residuals and transformations, inference for regression coefficients, prediction.
 
Year  Semester  Level  Units 

2013  1  1  3 
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.
