# Statistics for Data Science: Introduction

## Overview

This course will introduce statistics to the beginner, covering measures of central tendency, dispersion, probability theory and inferential statistics.

The method of Ordinary Least Squares will be discussed as will the notion of correlation. The theory of probability will be developed including: conditional probability and mutually exclusive events. Discrete and continuous probability distributions will also be investigated and applied to real world problems. Inferential statistics will also be introduced calculating 95% and 99% confidence intervals and performing hypothesis tests. The chi squared distribution will also be applied to contingency tables and to goodness of fit models.

## Programme details

Course starts: 24 Jan 2025

Week 1: Variables and graphs.

Week 2: Frequency distributions and measures of central tendency.

Week 3: The standard deviation and measures of dispersion.

Week 4: The method of Ordinary Least Squares, correlation coefficients.

Week 5: Elementary probability theory, the normal distribution and confidence intervals.

Week 6: The binomial, normal and Poisson distributions.

Week 7: Sampling theory and the central limit theorem.

Week 8: Statistical estimation theory and hypothesis testing.

Week 9: The chi squared distribution.

Week 10: Contingency tables and the F-distribution.

## Certification

Credit Application Transfer Scheme (CATS) points

To earn credit (CATS points) for your course you will need to register and pay an additional £30 fee for each course you enrol on. You can do this by ticking the relevant box at the bottom of the enrolment form or when enrolling online. If you do not register when you enrol, you have up until the course start date to register and pay the £30 fee.

Coursework is an integral part of all online courses and everyone enrolled will be expected to do coursework, but only those who have registered for credit will be awarded CATS points for completing work at the required standard. If you are enrolled on the Certificate of Higher Education, you need to indicate this on the enrolment form but there is no additional registration fee.

Digital credentials

All students who pass their final assignment, whether registered for credit or not, will be eligible for a digital Certificate of Completion. Upon successful completion, you will receive a link to download a University of Oxford digital certificate. Information on how to access this digital certificate will be emailed to you after the end of the course. The certificate will show your name, the course title and the dates of the course you attended. You will be able to download your certificate or share it on social media if you choose to do so.

Please note that assignments are not graded but are marked either pass or fail.

## Fees

Description Costs
Course Fee £285.00
Take this course for CATS points £30.00

## Funding

If you are in receipt of a UK state benefit, you are a full-time student in the UK or a student on a low income, you may be eligible for a reduction of 50% of tuition fees. Please see the below link for full details:

Concessionary fees for short courses

## Tutor

### Dr Vasos Pavlika

Dr Vasos Pavlika is a Associate Professor (Teaching) at UCL and Saturday School lecturer at the LSE. He has been a lecturer in the Department for Continuing Education, Oxford for several years. Vasos also teaches the History of Science and the History of Mathematics  at the Institute of Continuing Education, Cambridge. Vasos is also an Online Tutor at SOAS (University of London in M.Sc modules in Mathematical Finance) an Online Tutor at Goldsmiths College (University of London in B.Sc modules in Computer Science) and an Online Tutor in Mathematics with the Open University.

## Course aims

• To introduce measures of central tendency.
• To discuss the theory of probability.
• To introduce regression and correlation.

### Course Objectives:

• To introduce correlation and regression.
• To introduce probability theory.
• To discuss the theory of sampling.

## Teaching methods

Students will have access to a pre-recorded lecture to be watched in advance of the weekly online session.

## Learning outcomes

By the end of the course students will be expected:

• to comprehend measures of location and and of dispersion;
• to understand the method of ordinary least squares;
• to comprehend inferential statistics.

After attending this course, students will:

• be able to linearise data and to use regression techniques on data provided
• be able to solve problems on probability using the Poisson and binomial distributions as well as many other probability distributions;
• be able to determine confidence intervals and perform hypothesis tests

## Assessment methods

The students will given "Warm Up" exercises (tutorial exercises) based on the previous lecture's material at the beginning of each week and one portfolio exercise (in week 5) that will count towards the award of the 10 CATS points.

A set of exercises (an assignment) will be set in week 5 which will constitute the assessment for the award of the 10 CATs points. Alternatively the students can submit a portfolio of exercises which will arise from solving the homework exercises that will be set at the end of each week.

Coursework is an integral part of all weekly classes and everyone enrolled will be expected to do coursework in order to benefit fully from the course. Only those who have registered for credit will be awarded CATS points for completing work the required standard.

Students must submit a completed Declaration of Authorship form at the end of term when submitting your final piece of work. CATS points cannot be awarded without the aforementioned form - Declaration of Authorship form

## Application

We will close for enrolments 14 days prior to the start date to allow us to complete the course set up. We will email you at that time (14 days before the course begins) with further information and joining instructions. As always, students will want to check spam and junk folders during this period to ensure that these emails are received.

To earn credit (CATS points) for your course you will need to register and pay an additional £30 fee per course. You can do this by ticking the relevant box at the bottom of the enrolment form or when enrolling online.

Please use the 'Book' or 'Apply' button on this page. Alternatively, please complete an Enrolment Form (Word) or Enrolment Form (Pdf)

## Level and demands

Before attending this course, prospective students will:

• know how to use a scientific calculator;
• be familiar with elementary statistics e.g. mean, median, mode and range/spread;
• understand the basics of probability as the theory of chance.

The Department's Weekly Classes are taught at FHEQ Level 4, i.e. first year undergraduate level, and you will be expected to engage in a significant amount of private study in preparation for the classes. This may take the form, for instance, of reading and analysing set texts, responding to questions or tasks, or preparing work to present in class.

Credit Accumulation and Transfer Scheme (CATS)

To earn credit (CATS points) you will need to register and pay an additional £30 fee per course. You can do this by ticking the relevant box at the bottom of the enrolment form or when enrolling online. Students who register for CATS points will receive a Record of CATS points on successful completion of their course assessment.

Students who do not register for CATS points during the enrolment process can either register for CATS points prior to the start of their course or retrospectively from the January 1st after the current full academic year has been completed. If you are enrolled on the Certificate of Higher Education you need to indicate this on the enrolment form but there is no additional registration fee.