Introduction to Statistics (Using R Studio)
Series Description: This course will cover some fundamental concepts in statistics, giving students the tools and confidence to analyse and present their data. This will include an introduction to using RStudio, a widely used software package for statistics.
For students who have encountered little or no maths in their degree so far, there are an additional two Maths for Stats sessions to cover the essential maths skills needed for this course.
Target Audience: This series is for any student who will be working with data as part of their assignments, project, or dissertation. This includes UG, PGT and PGR students.
> Moodle page for this series (includes slides and any recordings)
| Date | Time | Class Title | Class Description | Venue |
| Wed 10 Jun | 14:00-15:00 | Maths for Stats 1: Understanding Formulae | Aimed at students who have encountered little or no maths in their degree so far, this session will cover common mathematical notation, rearranging equations and the types of mathematical relationship you will need to be familiar with (e.g. linear, exponential) for statistics. | St Andrews: 227 |
| Thu 11 Jun | 14:00-15:00 | Introduction to R Studio | This session introduces some of the basic functionality of R Studio. Bring your laptop with you to follow along! We will become comfortable with R Studio and use it to create impactful graphs and predictive models. | St Andrews: 227 |
| Wed 17 Jun | 14:00-15:00 | Maths for Stats 2: What is Probability? | Aimed at students who have encountered little or no maths in their degree so far, this session will cover the basics of probability, introducing how we think about it mathematically and how this relates to real life. | St Andrews: 227 |
| Thu 18 Jun | 14:00-15:00 | Descriptive Statistics | This session covers measures of central tendencies, dispersion, and position. Here we will be able to address the question "When is it better to use the median instead of the mean?" | Adam Smith: 492 |
| Thu 25 Jun | 14:00-15:00 | Probability | To certainly give students a better chance of answering the question "how likely was that?", this session covers the basic rules of probability, as well as both discrete and continuous probability distributions. | Adam Smith: 492 |
| Thu 2 Jul | 14:00-15:00 | Hypothesis Testing | This session will cover hypothesis testing, which is used to draw conclusions about a whole population from a sample of data, e.g. how can news outlets call an election with only a fraction of the votes tallied? We will discuss how to choose the null and alternative hypothesis, and which distributions to use. | Adam Smith: 584 |
| Thu 9 Jul | 14:00-15:00 | Simple and Multiple Linear Regression | This session will discuss the relationship, or more precisely the correlation, between variables, and how to describe these relationships using simple and multiple linear regression. We will use R to generate a best fit line to pairwise ordered data, and then also generate a more complex linear model. | St Andrews: 227 |
| Thu 16 Jul | 14:00-15:00 | Logistic Regression | Does the amount of time a student spends studying increase the probability of passing their course, and if so, what’s my probability of passing if I spend x hours studying? This last session will show how this can be answered using logistic regression, and how this can be implemented in R. | St Andrews: 227 |