Quantitative Methods in Language Sciences

LELA32011 Quantitative Methods in Language Sciences 20 Semester 1 Undergraduate Level 3 Andrea Nini Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Last part of a Bachelors ' European Credit Transfer & Accumulation System Rating : 10.0 This course aims to familiarize students with the basic concepts of statistics through hands-on practice. Topics covered in the course include distributions of data, basic principles of probability, describing and visualizing quantitative data, and interpreting quantitative data through hypothesis testing. This course aims to familiarize students with the basic concepts of statistics through hands-on practice. Topics covered in the course include distributions of data, basic principles of probability, describing and visualizing quantitative data, and interpreting quantitative data through hypothesis testing. The principal aims of the course unit are as follows:<ul> <li style="margin-bottom: 11px;">To familiarize students with basic statistical concepts and terms necessary to understand quantitative research</li> <li style="margin-bottom: 11px;">To help students understand the rules of describing, visualizing, and interpreting data</li> <li style="margin-bottom: 11px;">To help students develop computer skills needed to work with quantitative data</li> <li style="margin-bottom: 11px;">To foster critical thinking skills necessary for conducting quantitative research in the future</li></ul> By the end of this course students will be able to:<ul> <li style="margin-bottom: 11px;">Understand fundamentals of quantitative analysis</li> <li style="margin-bottom: 11px;">Be familiar with basic statistical methods</li> <li style="margin-bottom: 11px;">Describe, summarize, and visualize data</li> <li style="margin-bottom: 11px;">Conduct basic statistical tests by hand and using computer statistical software</li></ul> By the end of this course students will be able to:<ul> <li style="margin-bottom: 11px;">Identify appropriate descriptive and data visualization methods for different types of data</li> <li style="margin-bottom: 11px;">Assess validity and soundness of conclusions drawn from basic statistical tests</li></ul> By the end of this course students will be able to:<ul> <li style="margin-bottom: 11px;">Form sound statistical hypotheses based on research questions</li> <li style="margin-bottom: 11px;">Use computer programs to visualize and summarize data and conduct basic statistical tests.</li> <li style="margin-bottom: 11px;">Write simple computer code (using the R package)</li></ul> By the end of this course students will be able to:<ul> <li style="margin-bottom: 11px;">Use a variety of quantitative techniques to explore quantitative data</li> <li style="margin-bottom: 11px;">Draw conclusions from quantitative data through both descriptive and inferential statistics</li> <li style="margin-bottom: 11px;">Become comfortable working with quantitative data</li> <li style="margin-bottom: 11px;">Develop time management skills by working to deadline</li></ul> Analytical skills By the end of the semester, students are expected to be able to use computer software programs to describe, visualize data, and conduct some basic statistical tests. These skills will be beneficial to students regardless of whether they intend to pursue academic or non-academic careers. Research For students interested in pursuing postgraduate degrees in linguistics, many subfields of linguists are becoming more and more data-driven, so the quantitative skills acquired in this class will provide a good foundation, making it easier for students to start their own research. Other For students intending to pursue non-academic careers, quantitative skills will be a valuable asset as many employers increasingly look for job candidates that have both domain-specific knowledge (e.g., linguistic knowledge) and general quantitative skills. Some representative topics covered:<ul> <li style="margin-bottom: 11px;">Variable types</li> <li style="margin-bottom: 11px;">Descriptive statistics</li> <li style="margin-bottom: 11px;">Visualising Data</li> <li style="margin-bottom: 11px;">Probability and Inference</li> <li style="margin-bottom: 11px;">Correlation and regression</li> <li style="margin-bottom: 11px;">Multiple regression</li> <li style="margin-bottom: 11px;">Comparing means</li> <li style="margin-bottom: 11px;">Experimental design and generalisation</li></ul> Weekly 1 hour lecture (online)Weekly 2 hour computer data-analysis tutorialE-learning: The Canvas environment will provide: lecture recordings, lecture slides, tutorials on using R, reading assignments (beyond the main textbook), revision quizzes, additional exercises. We will also use the Canvas discussion forum. 0 Other 100% <figure class="table"><table class="MsoTableGrid" style="border-collapse:collapse;"><tbody><tr><td style="border:1px solid black;padding:0cm 7px;vertical-align:top;width:200px;">Assessment Task</td><td style="border-bottom:1px solid black;border-left-style:none;border-right:1px solid black;border-top:1px solid black;padding:0cm 7px;vertical-align:top;width:200px;">Formative or Summative</td><td style="border-bottom:1px solid black;border-left-style:none;border-right:1px solid black;border-top:1px solid black;padding:0cm 7px;vertical-align:top;width:200px;">Weighting</td></tr><tr><td style="border-bottom:1px solid black;border-left:1px solid black;border-right:1px solid black;border-top-style:none;padding:0cm 7px;vertical-align:top;width:200px;">Canvas Quizzes</td><td style="border-bottom:1px solid black;border-left-style:none;border-right:1px solid black;border-top-style:none;padding:0cm 7px;vertical-align:top;width:200px;">Formative</td><td style="border-bottom:1px solid black;border-left-style:none;border-right:1px solid black;border-top-style:none;padding:0cm 7px;vertical-align:top;width:200px;">0%</td></tr><tr><td style="border-bottom:1px solid black;border-left:1px solid black;border-right:1px solid black;border-top-style:none;padding:0cm 7px;vertical-align:top;width:200px;">Coursework (Analysis Report)</td><td style="border-bottom:1px solid black;border-left-style:none;border-right:1px solid black;border-top-style:none;padding:0cm 7px;vertical-align:top;width:200px;">Summative</td><td style="border-bottom:1px solid black;border-left-style:none;border-right:1px solid black;border-top-style:none;padding:0cm 7px;vertical-align:top;width:200px;">60%</td></tr><tr><td style="border-bottom:1px solid black;border-left:1px solid black;border-right:1px solid black;border-top-style:none;padding:0cm 7px;vertical-align:top;width:200px;">Mid-term Exam</td><td style="border-bottom:1px solid black;border-left-style:none;border-right:1px solid black;border-top-style:none;padding:0cm 7px;vertical-align:top;width:200px;">Summative</td><td style="border-bottom:1px solid black;border-left-style:none;border-right:1px solid black;border-top-style:none;padding:0cm 7px;vertical-align:top;width:200px;">40%</td></tr></tbody></table></figure>  <figure class="table"><table style="width:500px;" border="1" cellpadding="1" cellspacing="1"><tbody><tr><td>Canvas quizzes: individual scores</td><td>Formative</td></tr><tr><td>Coursework mark and individual feedback</td><td>Formative and summative</td></tr><tr><td>Exam mark</td><td>Summative</td></tr></tbody></table></figure>  LELA Quantitative Methods - Level 2 and Level 3 Quantitative Methods can not both be taken by the same student BA(Hons) English Language BA (Hons) English Language Third Year Optional BA(Hons) Linguistics BA (Hons) Linguistics Third Year Optional Y Winter, B. (2019). Statistics for linguists: An introduction using R. RoutledgeField, A. and Hole, G., 2002. How to design and report experiments. Sage.Crawley, Michael J. (2005). Statistics: An Introduction Using R.Johnson, Keith (2008). Quantitative Methods in Linguistics. Assessment written exam 1.5 Lectures 11 Tutorials 22 0 165.5