This is an introductory study-unit in statistics designed to provide students with a theoretical background in statistical techniques and data analysis with emphasis on application. Students will learn to differentiate between different types of data and how it is collected, the different ways in which these can be represented graphically, how to summarize and analyze a presented data set, as well as the basics of probability and probability distributions. Practical examples from different fields will be used to illustrate the techniques discussed. A more detailed list of topics is presented below.
Introduction to Statistics
Definition and importance of statistics
Types of data: qualitative vs. quantitative
Types of measurement: eg. nominal, ordinal, interval
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This study-unit introduces students to methods for gathering, organising, summarising and analysing quantitative data using Excel software. It also delves into fundamental statistical principles, including, measures of central tendency, variability and probability distributions, which will help the student to foster the ability to critically analyse data, recognise patterns, and interpret results, enabling more informed decision-making.
Learning Outcomes: Knowledge and Understanding
By the end of the study-unit the student will be able to:
Define and explain the significance of key statistical terms and concepts.
Distinguish between different types of data and levels of measurement.
Design surveys and experiments using appropriate sampling methods.
Recognise and mitigate sources of bias in data collection.
Calculate and interpret measures of central tendency (mean, median, mode) and variability (range, variance, standard deviation).
Create and interpret graphical representations of data, including histograms, bar charts, pie charts, and box plots.
Use basic probability rules to solve problems involving random events.
Identify and apply appropriate probability distributions for different types of data.
Learning Outcomes: Skills
By the end of the study-unit the student will be able to:
Perform basic statistical analysis using spreadsheets.
Create and interpret various types of graphs and charts, such as histograms, bar charts, pie charts, and scatter plots, to effectively communicate data insights.
Apply key probability concepts and distributions.
Interpret and critically evaluate statistical results in the context of real-world scenarios.
Assess the validity and reliability of conclusions drawn from statistical analyses.
Non EU Applicants:
EUR260
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