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INTRODUCTION TO DATA ANALYSIS

Module code: MT122S
Credits: 2.5
Semester: 2
Department: MATHEMATICS AND STATISTICS
International:

	Overview
	Module Objective: To introduce students to Data Analysis. Quantitative data: histograms, boxplots. Numerical summaries: mean, median, quartiles, IQR, standard deviation. Comparisons: Grouped data. Paired data. Categorical data: frequency tables, barcharts. Contingency tables, conditional distributions, clustered and segmented barcharts. Probability: Sample spaces, events, conditional probability, independence, Bayes theorem. The Normal model. Sampling distribution of mean. X-bar charts.

Overview

Module Objective:
To introduce students to Data Analysis.

Quantitative data: histograms, boxplots. Numerical summaries: mean, median, quartiles, IQR, standard deviation.
Comparisons: Grouped data. Paired data.
Categorical data: frequency tables, barcharts. Contingency tables, conditional distributions, clustered and segmented barcharts. Probability: Sample spaces, events, conditional probability, independence, Bayes theorem.
The Normal model. Sampling distribution of mean. X-bar charts.

	Learning Outcomes
	On successful completion of the module, students should be able to: Describe various types of data using numerical or graphical techniques. Interpret graphical and tabular data presentations. Calculate probabilities and conditional probabilities and for unions and intersections of events. Calculate probabilities based on the Normal model. Construct and interpret x-bar charts. Use the methods from the course to solve problems. State definitions and theorems covered in the course.

Learning Outcomes

Teaching & Learning methods

Assessment

	Autumn Supplementals/Resits
	Continuous assessment mark is carried forward to the Autumn. University scheduled written examination (Autumn): 60 minutes

	Timetable
	This timetable is not currently available, please contact the Mathematics And Statistics Department.

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Courses / Module

INTRODUCTION TO DATA ANALYSIS