Courses / Module

STATISTICAL METHODS FOR DATA SCIENCE 1 (R)

Module code: DS863
Credits: 5
Semester: 1
Department: MATHEMATICS AND STATISTICS
International:

	Overview
	This course covers probability and statistical techniques for data analytics and data science. Topics include: Exploratory data analysis and visualisation. Probability basics, independence, Bayes theorem. Probability models for data, including Binomial, Poisson, Exponential and Normal. Confidence intervals and hypothesis testing: one and two samples, paired samples, proportions. Case studies in R. Lectures and labs as for DS663.

Overview

This course covers probability and statistical techniques for data analytics and data science. Topics include: Exploratory data analysis and visualisation. Probability basics, independence, Bayes theorem. Probability models for data, including Binomial, Poisson, Exponential and Normal. Confidence intervals and hypothesis testing: one and two samples, paired samples, proportions. Case studies in R.

Lectures and labs as for DS663.

	Learning Outcomes
	On successful completion of the module, students should be able to: Analyse data using R. Write statistical reports. Model data using probability distributions. Choose and construct appropriate data visualisations.

Teaching & Learning methods

Assessment

	Autumn Supplementals/Resits
	Are supplemental/resit registrations permitted? No

	Pre-Requisites
	This module is for Registered Research students. Permission is required from the Head of the Mathematics and Statistics Department to take this module.

	Timetable
	Click on the link to open the Timetable for Module [DS863]. Venue locations can be found here.

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Courses / Module

STATISTICAL METHODS FOR DATA SCIENCE 1 (R)