PHYS10792
Introduction to Data Science
10
Semester 2
Undergraduate
Level 1
Andrew Markwick
Unit coordinator
Michaela Queitsch-Maitland
Unit coordinator
Department of Physics & Astronomy
1
FHEQ level (Framework for Higher Education Qualifications) ' First part HE study/Bachelors '
European Credit Transfer & Accumulation System Rating : 5.0
<p>Introduction to Data Science</p>
<p>Introduction to Data Science</p>
<p><span style="background-color:rgb(255,255,255);color:rgba(0,0,0,0.87);"><span style="-webkit-text-stroke-width:0px;display:inline !important;float:none;font-family:"Segoe UI", Lato, "Helvetica Neue", Arial, Helvetica, sans-serif;font-size:14px;font-style:normal;font-variant-caps:normal;font-variant-ligatures:normal;font-weight:400;letter-spacing:normal;orphans:2;text-align:start;text-decoration-color:initial;text-decoration-style:initial;text-decoration-thickness:initial;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;">To introduce basics of statistical methods and modern-day advanced data analysis techniques, as required in all fields working with data. To deepen the understanding of how data analysis works for small and large data samples. To obtain a comprehensive set of tools to analyse data.</span></span></p>
<p paraeid="{f4a344e6-50e6-438f-9340-2492f4312a81}{162}" paraid="166480505">On completion successful students will be able to: </p><p paraeid="{f4a344e6-50e6-438f-9340-2492f4312a81}{170}" paraid="415458028">• Define the basics of the statistical analysis of data</p><p paraeid="{f4a344e6-50e6-438f-9340-2492f4312a81}{180}" paraid="1325317552">• Explain methods of data analysis and their idea</p><p paraeid="{f4a344e6-50e6-438f-9340-2492f4312a81}{190}" paraid="1497338893">• Apply a set of analysis techniques as required for basic and advanced datasets </p><p paraeid="{f4a344e6-50e6-438f-9340-2492f4312a81}{200}" paraid="1025774744">• Assess new results derived from datasets, conclude on validity of the hypotheses</p><p paraeid="{f4a344e6-50e6-438f-9340-2492f4312a81}{212}" paraid="1129807310">• Build on the knowledge of statistical data analysis to study more advanced and new techniques</p>
<ol><li>Probabilities and interpretations </li><li>Probability distributions </li><li>Parameter estimation </li><li>Maximum likelihood</li><li>Least square, chi2, correlations </li><li>Monte Carlo basics </li><li>Goodness of fit tests</li><li>Hypothesis testing</li><li>Probability and confidence level </li><li>Limit setting </li><li>Introduction to multivariate analysis techniques </li></ol>
0
Other
10%
1
Written exam
90%
<p>* Other = Online quizzes.</p>
<p>Feedback is through exercises (via online feedback) and the exam.</p>
PHYS10071
Mathematics 1
Pre-Requisite
Compulsory
N
<p>Barlow, R., <em>Statistics – A Guide to the Use of Statistical Methods in the Physical Sciences</em>, Wiley</p><p>Cowan, G., <em>Statistical Data Analysis</em>, Oxford</p><p>Behnke, O., et al, <em>Data Analysis in High Energy Physics: A Practical Guide to Statistical Methods</em>, Wiley</p>
Assessment written exam
1.5
eAssessment
12
Lectures
24
0
62.5