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<CourseUnit xmlns="http://www.manchester.ac.uk/CUICourseUnitDetails" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.manchester.ac.uk/CUICourseUnitDetails.xsd">
  <UnitCode Applicant="Y" Label="Unit code" Student="Y">
    <Code>POLI60341</Code>
  </UnitCode>
  <UnitTitle Applicant="Y" Label="Unit title" Student="Y">
    <Title>Tools and techniques of applied quantitative analysis</Title>
  </UnitTitle>
  <MaxUnits Applicant="Y" Label="Credit rating" Student="Y">
    <Units>15</Units>
  </MaxUnits>
  <TeachingPeriods Applicant="Y" Label="Teaching period(s)" Student="Y">
    <Period>Semester 1</Period>
  </TeachingPeriods>
  <AcademicCareer Applicant="Y" Label="Academic career" Student="Y">
    <Value>Postgraduate Taught</Value>
  </AcademicCareer>
  <UnitLevel Applicant="Y" Label="Unit level" Student="Y">
    <Level>Level 7</Level>
  </UnitLevel>
  <StaffList Applicant="Y" Label="Teaching staff" RoleLabel="Course Unit Role" Student="Y">
    <StaffMember>
      <Name>Charlotte Hargrave</Name>
      <Role>Unit coordinator</Role>
    </StaffMember>
  </StaffList>
  <OfferedBy Applicant="Y" Label="Offered by" Student="Y">
    <OrganisationList>
      <Organisation>
        <OrgName>Politics</OrgName>
      </Organisation>
    </OrganisationList>
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      <Group>
        <GroupName></GroupName>
      </Group>
    </GroupList>
    <FheqLevels>
      <FheqLevel>
        <LevelNumber>1</LevelNumber>
        <LevelName>FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 ' </LevelName>
      </FheqLevel>
    </FheqLevels>
    <Ects>
      <MaxUnits>European Credit Transfer &amp; Accumulation System Rating :   7.5</MaxUnits>
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  <MarketingOverview Applicant="Y" Label="Marketing Course unit overview" Student="">
    <Content>&lt;p&gt;POLI60341 is designed to deliver a rigorous grounding in quantitative methods sufficient for independent use of such methods in MA dissertations or PhD research. It aims to offer a balanced mix of training, helping to prepare advanced students who want to engage in secondary data analysis in their MA dissertation or in doctoral research and have some experience of quantitative methods, but also aiming to provide a robust initial grounding who have not received extensive quantitative methods training prior to joining the MA..&lt;/p&gt;</Content>
  </MarketingOverview>
  <UnitOverview Applicant="" Label="Course unit overview" Student="Y">
    <Content>&lt;p&gt;Week 1: An introduction to thinking statistically and using data&lt;/p&gt;&lt;p&gt;Week 2: Understanding and presenting data: an introduction to different kinds of variables (continuous, ordinal, binary, categorical) and how to present them (frequency tables, cross-tabs)&lt;/p&gt;&lt;p&gt;Week 3: Analysis and visualization techniques for the relationship between two variables&lt;/p&gt;&lt;p&gt;Week 4: &amp;nbsp;Relationships between continuous variables – scatter plots and correlation (and why correlation is NOT causation); introduction to regression analysis&lt;/p&gt;&lt;p&gt;Week 5: Building linear regression models to test the impact of multiple factors on an outcome. Visualising linear regression effects&lt;/p&gt;&lt;p&gt;Week 6: Logistic regression analysis&lt;/p&gt;&lt;p&gt;Week 7: Factor analysis/scale construction to combine variables&amp;nbsp;&lt;/p&gt;&lt;p&gt;Week 8: Interaction effects&lt;/p&gt;&lt;p&gt;Week 9: Multilevel modelling&lt;/p&gt;&lt;p&gt;Week 10: Final report preparation: what you need to do, how, and why&lt;/p&gt;</Content>
  </UnitOverview>
  <Aims Applicant="Y" Label="Aims" Student="Y">
    <Content>&lt;p&gt;POLI60341 is relevant for students with diverse academic backgrounds and interests who are interested in developing and applying quantitative methods.&amp;nbsp; It will teach students how to find relevant data for a range of research questions, and explore the limitations and common pitfalls of analysing quantitative data. For all those looking to understand and use data in politics masters and doctoral research, POLI60341 provides an essential step forward in the basic core skills of data evaluation and analysis, as well as introducing more complex statistical techniques that are not typically taught at undergraduate level. It is particularly designed to enable students to conduct work more independently, from finding their own data sources, analysing them and writing up the results for an independent research project. It will be taught using STATA - an advanced statistical software package that is more sophisticated and flexible than SPSS, the package typically used in UG quantitative methods courses&lt;/p&gt;</Content>
  </Aims>
  <LearningOutcomes Applicant="Y" Label="Learning outcomes" Student="Y">
    <Content></Content>
  </LearningOutcomes>
  <Knowledge Applicant="Y" Label="Knowledge and understanding" Student="Y">
    <Content>&lt;ul&gt;	&lt;li&gt;		Learn how to find, use and analyse quantitative data using the most popular quantitative data analysis techniques to answer questions driving political research, and how to write up the findings from such analysis&lt;/li&gt;	&lt;li&gt;		Learn about how academics researching politics gather and use data, with guest lectures from various quantitative researchers in the department explaining how they apply particular techniques to solve particular research problems&lt;/li&gt;	&lt;li&gt;		Learn about which questions can be answered with quantitative data and which cannot.&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</Content>
  </Knowledge>
  <IntellectualSkills Applicant="Y" Label="Intellectual skills" Student="Y">
    <Content>&lt;ul&gt;	&lt;li&gt;		Evaluate data from the point of view of quality, design and method of collection;&lt;/li&gt;	&lt;li&gt;		Develop a critical awareness of the strengths and weaknesses of different methods of analysing data and applying the results of quantitative analysis to political research questions;&lt;/li&gt;	&lt;li&gt;		Understand and analyse some of the central questions in politics research that have been addressed with the use of quantitative data;&lt;/li&gt;&lt;/ul&gt;</Content>
  </IntellectualSkills>
  <PracticalSkills Applicant="Y" Label="Practical skills" Student="Y">
    <Content>&lt;ul&gt;	&lt;li&gt;		Develop a critical awareness of the use of data in political and media debate;&lt;/li&gt;	&lt;li&gt;		Gain an ability to seek out relevant data sources&lt;/li&gt;&lt;/ul&gt;</Content>
  </PracticalSkills>
  <TransferableSkills Applicant="Y" Label="Transferable skills and personal qualities" Student="Y">
    <Content>&lt;ul&gt;	&lt;li&gt;		Improve the ability to interpret and communicate quantitative findings in writing and verbally.&lt;/li&gt;	&lt;li&gt;		Gain an exposure to widely used quantitative political science data sources&lt;/li&gt;	&lt;li&gt;		Gain an ability to conduct a range of basic to intermediate data analysis techniques, including cross-tabulation analysis, graphical analysis and basic regression analysis&lt;/li&gt;	&lt;li&gt;		Gain a working knowledge of STATA, the most widely used statistical software for applied quantitative analysis&lt;/li&gt;&lt;/ul&gt;</Content>
  </TransferableSkills>
  <EmployabilitySkillsList Applicant="Y" Label="Employability skills" Student="Y">
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      <SkillDescription></SkillDescription>
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  <Syllabus Applicant="Y" Label="Syllabus" Student="Y">
    <Content></Content>
  </Syllabus>
  <TeachingMethods Applicant="Y" Label="Teaching and learning methods" Student="Y">
    <Content>&lt;p&gt;10 x 2 hour computer lab sessions&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</Content>
  </TeachingMethods>
  <AssessmentMethods Applicant="Y" Label="Assessment methods" Student="Y">
    <IntroText> </IntroText>
    <Method>
      <MethodId>0</MethodId>
      <MethodName>Other</MethodName>
      <MethodWeight>33%</MethodWeight>
    </Method>
    <Method>
      <MethodId>3</MethodId>
      <MethodName>Report</MethodName>
      <MethodWeight>67%</MethodWeight>
    </Method>
    <OtherDescription>&lt;figure class="table"&gt;&lt;table border="1" cellpadding="0" cellspacing="0" height="245" width="587"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td&gt;Activity&lt;/td&gt;&lt;td&gt;Length required&lt;/td&gt;&lt;td&gt;Weighting&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;Four learning logs of c.250&amp;nbsp;words each: these will test your understanding of the statistical and analytical techniques we have learned, how to apply them, and how to interpret and write up results&lt;/td&gt;&lt;td&gt;1000 words in total&lt;/td&gt;&lt;td&gt;33%&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;End of course report: This report is a more extended piece of writing, where you will need to develop and motivate a hypothesis, explain the data and measures you will use to test it, then present and interpret an extended data analysis examining it. This should feature examples of data visualization (graphs), basic analysis (tables and cross-tabulation) and at least one form of statistical modelling (regression analysis).&lt;/td&gt;&lt;td&gt;2000 words in total&lt;/td&gt;&lt;td&gt;67%&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;Weekly workshop output: you will need to record your activities in each week’s workshop in a stata “do file”. These will be checked to ensure engagement with and understanding of the workshop activities, and formative feedback provided to help you with the learning logs and course report&lt;/td&gt;&lt;td&gt;n/a&lt;/td&gt;&lt;td&gt;formative&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/figure&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</OtherDescription>
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  <FeedbackMethods Applicant="Y" Label="Feedback methods" Student="Y">
    <Content></Content>
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      <UnitTitle></UnitTitle>
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      <Description></Description>
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      <Level></Level>
      <Requirement></Requirement>
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  <FreeChoice Applicant="Y" Label="Available as a free choice unit?" Student="Y">
    <Content>Y</Content>
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  <Accreditation Applicant="Y" Label="Accreditation" Student="Y">
    <Content></Content>
  </Accreditation>
  <RecommendedReading Applicant="Y" Label="Recommended reading" Student="Y">
    <Content></Content>
  </RecommendedReading>
  <StudyHours Applicant="Y" Label="Study hours" Student="Y">
    <IntroText> </IntroText>
    <ScheduledHours Applicant="Y" Label="Scheduled activity hours" Student="Y">
      <ActivityHours>
        <ActivityType>Practical classes &amp; workshops</ActivityType>
        <Hours>20</Hours>
      </ActivityHours>
    </ScheduledHours>
    <PlacementHours Applicant="Y" Label="Placement hours" Student="Y">
      <ActivityHours>
        <ActivityType></ActivityType>
        <Hours>0</Hours>
      </ActivityHours>
    </PlacementHours>
    <TotalHours Applicant="Y" Label="Independent study hours" Student="Y">
      <Hours>130</Hours>
    </TotalHours>
  </StudyHours>
  <Notes Applicant="Y" Label="Additional notes" Student="Y">
    <Content></Content>
  </Notes>
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