16/10/2018  8:50am
Semester 1: Weeks 1 to 11
Semester 1: Weeks 1 to 11
2018/2019 Semester 1 Lectures:

Tuesdays 16:10 to 17:00
David Hume Tower LTs Lecture Theatre B 
Wednesdays 12:10 to 13:00
David Hume Tower LTs Lecture Theatre C
Date  Lecture Title  Description  
1  18/09/2018  Introduction  Overview of the RMS course. 
2

19/09/2018  Data: Measurement, types, plots and tables  Introduction to data and how to present it. 
3  25/09/2018  Central tendency  In this lecture we discuss different ways to calculate the average of a set of numbers. 
4  26/09/2018  Variability  In this lecture we discuss the different ways to describe the spread or variability in data. 
5  02/10/2018  Statistical models  Throughout the research methods training in psychology, we are going to be talking about different statistical models for data. In this lecture, we introduce the concept of a statistical model. 
6  03/10/2018  Functions  Understanding functions is critical to the understanding of statistics. In this lecture, we introduce simple functions, the core ideas, and the relation to graphs. 
7  09/10/2018  Probability 1  Lectures 7 to 9 cover the basic building blocks of probability theory necessary to grasps the way in which we tend to use statistical tests in psychology. In this lecture, we discuss sets. 
8  10/10/2018  Probability 2  Lectures 7 to 9 cover the basic building blocks of probability theory necessary to grasps the way in which we tend to use statistical tests in psychology. In this lecture, we discuss elementary probability and calculating probability. 
9  16/10/2018  Probability 3  Lectures 7 to 9 cover the basic building blocks of probability theory necessary to grasps the way in which we tend to use statistical tests in psychology. In this lecture, we discuss elementary probability and calculating probability. 
10  17/10/2018  Probability Distributions  A fundamental concept in statistical analysis is the probability distribution. Here we will introduce probability distributions and discuss the main principles. 
11  30/10/2018  Binomial Distribution  In this lecture we will discuss a specific example of a discrete distribution, the binomial. 
12  31/10/2018  Normal distribution  The most important distribution in statistics  in this lecture we discuss the normal distribution. 
13  06/11/2018  Sampling (1)  In lectures 13 and 14, we discuss the principles of sampling and sampling distributions and the role they play in statistical testing. 
14  07/11/2018  Sampling (2)  In lectures 13 and 14, we discuss the principles of sampling and sampling distributions and the role they play in statistical testing. 
15  13/11/2018  Sampling and point estimation  In this lecture we will move on from the idea of sampling distributions for statistics, to making point estimations for parameters of interest. 
16  14/11/2018  Point Estimation and Confidence Intervals  In this lecture we will progress from the concept of the point estimate, to the idea of computing intervals around those estimates. 
17  20/11/2018  Hypothesis testing  From lectures 8 to 16, we have been discussing aspects of probability and how it relates to statistical tests in psychology. In this lecture, we draw this together to discuss null hypothesis significance testing  the primary tool used for hypothesis testing in psychology. 
18  21/11/2018  Hypothesis Testing  From lectures 8 to 16, we have been discussing aspects of probability and how it relates to statistical tests in psychology. In this lecture, we draw this together to discuss null hypothesis significance testing  the primary tool used for hypothesis testing in psychology. 
19  27/11/2018  Chisquare goodness of fit test  Now we have put in place all the building blocks of statistical testing, we can begin to discuss what tests we can use to answer different research questions. We will begin by looking at the chisquare goodness of fit test. 
20  28/11/2018  Chisquare test of independence  Next, we will consider the chisquare test of independence  suitable if you wish to understand if two nominal categorical variables are related. 