Statistical Practice I

Resources for Statistical Practice I (including Life Sciences and Vet Bio) - for more information about the courses, please see course outlines.

Maths background knowledge

There is some maths knowledge that is important to have in order to make sense of some concepts in Stat Prac I. These resources will be helpful to learn or relearn some of this background knowledge.

This seminar was given by the MLC in 2013 and discusses how to make sense of mathematical notation.

This series of seminars covers fundamental maths ideas such as decimals and rounding, solving equations and straight line graphs. These are all useful for Stat Prac I.

Useful resources

This webpage describes three ways to create a picture of a normal distribution in a word document, which might be useful for doing your assignments.

This seminar describes how to go about making yourself a formula sheet for use during an exam where you are allowed notes.

Resources to help with the course content

    Interpreting stats

    This handout has sentence frames you can use to say the right words for interpreting statistics such as confidence intervals, slopes and coefficients of determination. 

    Statistical concepts and choosing the right stats

    The following material was presented for Medical students in 2022, 2018 and 2016  It has an overview of the information you need to know to choose what statistical procedure goes with what. It also has explanations of what hypothesis testing, confidence intervals and regression are doing. (Some of the terminology is different to Stat Prac I, and it covers more stats procedures than are covered in Stat Prac I, but the ideas are similar.)

    Revision seminars

    These revision seminars were given to students in Statistical Practice I over the years. (There were others between 2013 and 2021, but the videos have been lost.)

    Note that this course has changed its curriculum several times over the last several years, so the older seminars might not match the current version of the course exactly. In particular they may mention things no longer in the curriculum or leave out things that are now in the curriculum. Also, the computer program R was only introduced to the course in 2020. Please check against your course material if you are in doubt of anything.

    2023 Semester 2

    David discussed margin of error for confidence intervals and using it to calculate sample size (at the start), and what information to look for in a question to figure out what statistics to do (starting at 49m16s).

    2023 Semester 1

    David discussed ANOVA (at the start) and also regression confidence and prediction intervals (starting at 1h21m36s). 

    2022 Semester 2

    David discussed the different meanings of the word distribution across the course, including talking about the distribution of sample data, probability distributions like normal and binomial, and the distributions of test statistics. (The only thing missed was distribution for assumption checking.)

    2022 Semester 1

    David discussed what sorts of questions statistics is capable of answering, including the meaning of confounding, as well as the different types of variables. Then, starting at 53m40s, he discussed the two kinds of chi-squared tests in detail.

    2021 Semester 1

    David discussed the Chi-squared test for association/independence, then the Chi-squared test for goodness of fit (starting at 1h2m45s), then ANOVA (starting at 1h14m40s).

    2013 Semester 2

    In this revision seminar in Semester 2 2013, David gave a description of each of the twelve hypothesis tests that appeared in Stat Prac I in that year, including the assumptions that need to be checked for each. Note that there may be a different set of tests in the semester you are doing the course, and a different computer program, but the general idea should still be helpful.

      2013 Semester 1

      A revision seminar mainly on probability and distributions, including types of variables, probability distributions, theoretical means and standard deviations and probability laws. It also included a little on how to choose what hypothesis test goes with what situation, as well as the chi-squared test.