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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>POPH67802</Code>
  </UnitCode>
  <UnitTitle Applicant="Y" Label="Unit title" Student="Y">
    <Title>Practical Statistics for Population Health</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 2</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>Islay Gemmell</Name>
      <Role>Unit coordinator</Role>
    </StaffMember>
  </StaffList>
  <OfferedBy Applicant="Y" Label="Offered by" Student="Y">
    <OrganisationList>
      <Organisation>
        <OrgName></OrgName>
      </Organisation>
    </OrganisationList>
    <GroupList>
      <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>
    </Ects>
  </OfferedBy>
  <MarketingOverview Applicant="Y" Label="Marketing Course unit overview" Student="">
    <Content>&lt;p&gt;This course is relevant to current or future professionals whose careers will involve either conducting quantitative research or interpreting the findings of quantitative research studies. Statistical analysis of data is a key part of research and many research findings and recommendations are based on the results of statistical analysis. An awareness of statistical methods and the ability to interpret data from published studies is important for a career in public health.&lt;/p&gt;&lt;p&gt;The course materials include worked examples, video demos, quizzes and practice tasks. Students are expected to work through the online course materials in their own time and use the discussion boards to ask questions and check their understanding of the course material. &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; Students on the On campus programme will also &amp;nbsp;need to be available for the face to face teaching/practical sessions that will be in the timetable. These will be delivered on campus at the University of Manchester. The same content will be delivered in webinars for online students. On Campus students are welcome to attend the webinars. All webinars will be recorded and shared on Canvas.&lt;/p&gt;</Content>
  </MarketingOverview>
  <UnitOverview Applicant="" Label="Course unit overview" Student="Y">
    <Content>&lt;p&gt;This course will provide you with the skills to conduct quantitative research and apply statistical thinking to public health practice. You will learn how to conduct statistical analysis using a statistical package (SPSS or R) and how to interpret the results of your analyses. Data from a longitudinal study of coronary heart disease risk factors will be used throughout the course to demonstrate how to conduct statistical analyses of health data using a statistical package.&lt;br&gt;&lt;br&gt;&amp;nbsp;&lt;/p&gt;</Content>
  </UnitOverview>
  <Aims Applicant="Y" Label="Aims" Student="Y">
    <Content>&lt;p&gt;The aim of this course unit is to provide students with an understanding of statistics that they can apply within their own professional practice. This could include conducting quantitative research, interpreting the findings of quantitative research studies or applying statistical thinking to public health practice. The course will teach you how to conduct statistical analyses using a statistical package (SPSS or R).&lt;/p&gt;</Content>
  </Aims>
  <LearningOutcomes Applicant="Y" Label="Learning outcomes" Student="Y">
    <Content>&lt;p&gt;On completion of this unit, successful students will be able to:&lt;/p&gt;&lt;ul&gt;	&lt;li&gt;		Apply statistical thinking when conducting or reviewing research in professional practice.&lt;/li&gt;	&lt;li&gt;		Demonstrate an understanding of the relationship between populations, samples and variability in research studies.&lt;/li&gt;	&lt;li&gt;		Define different types of data and demonstrate an understanding of confidence intervals and the normal distribution.&lt;/li&gt;	&lt;li&gt;		Perform correlation and simple linear regression and interpret the results.&lt;/li&gt;	&lt;li&gt;		Construct and interpret multiple regression models and logistic regression models demonstrating an understanding of confounding.&lt;/li&gt;	&lt;li&gt;		Demonstrate the use of methods for statistical inference.&lt;/li&gt;	&lt;li&gt;		Perform and interpret survival analyses.&lt;/li&gt;	&lt;li&gt;		Use a statistical package to analyse a data set&lt;/li&gt;&lt;/ul&gt;</Content>
  </LearningOutcomes>
  <Knowledge Applicant="Y" Label="Knowledge and understanding" Student="Y">
    <Content>&lt;ul&gt;&lt;li&gt;Demonstrate an understanding of the relationship between populations, samples and variability in research studies.&lt;/li&gt;&lt;li&gt;Define different types of data and demonstrate an understanding of confidence intervals and the normal distribution.&amp;nbsp;&lt;/li&gt;&lt;/ul&gt;</Content>
  </Knowledge>
  <IntellectualSkills Applicant="Y" Label="Intellectual skills" Student="Y">
    <Content>&lt;ul&gt;&lt;li&gt;Perform correlation and simple linear regression and interpret the results.&lt;/li&gt;&lt;li&gt;Construct and interpret multiple regression models and logistic regression models demonstrating an understanding of confounding.&lt;/li&gt;&lt;li&gt;Demonstrate the use of methods for statistical inference.&lt;/li&gt;&lt;li&gt;Perform and interpret survival analyses.&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</Content>
  </IntellectualSkills>
  <PracticalSkills Applicant="Y" Label="Practical skills" Student="Y">
    <Content>&lt;ul&gt;&lt;li&gt;Use a statistical package to analyse a data set&amp;nbsp;&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;Apply statistical thinking when conducting or reviewing research in professional practice.&lt;/li&gt;&lt;/ul&gt;</Content>
  </TransferableSkills>
  <EmployabilitySkillsList Applicant="Y" Label="Employability skills" Student="Y">
    <Skill>
      <SkillId>Analytical skills</SkillId>
      <SkillDescription>Students will develop their analytical skills by learning how to conduct statistical analyses using a statistical package and how to interpret the results of their analysis.</SkillDescription>
    </Skill>
    <Skill>
      <SkillId>Problem solving</SkillId>
      <SkillDescription>Students will develop problem solving skills through developing their skills in statistical thinking.</SkillDescription>
    </Skill>
    <Skill>
      <SkillId>Research</SkillId>
      <SkillDescription>Students will develop skills in conducting quantitative research and interpreting the findings of quantitative research studies.</SkillDescription>
    </Skill>
  </EmployabilitySkillsList>
  <Syllabus Applicant="Y" Label="Syllabus" Student="Y">
    <Content>&lt;ul&gt;&lt;li&gt;Introduction to statistical thinking&lt;/li&gt;&lt;li&gt;Types of data&lt;/li&gt;&lt;li&gt;Populations and sampling, variability and sample size&lt;/li&gt;&lt;li&gt;The normal distribution and confidence intervals&lt;/li&gt;&lt;li&gt;Correlation and simple linear regression&lt;/li&gt;&lt;li&gt;Multiple regression&lt;/li&gt;&lt;li&gt;Logistic regression&lt;/li&gt;&lt;li&gt;Statistical inference for continuous and categorical data&lt;/li&gt;&lt;li&gt;Survival Analysis&lt;/li&gt;&lt;li&gt;Statistics in Practice&lt;/li&gt;&lt;/ul&gt;</Content>
  </Syllabus>
  <TeachingMethods Applicant="Y" Label="Teaching and learning methods" Student="Y">
    <Content>&lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;The course materials are provided via the virtual learning environments Canvas and Articulate Rise. The course consists of 10 topics and within each topic there is a quiz or practical assignment to complete. There are weekly discussion board topics and the discussion boards are moderated by the course unit leader and teaching assistants. The core text is referenced in each topic, and although you should be able to complete the topic adequately without the core textbook we recommend that you obtain a copy as it will help you gain a deeper understanding of the subject. The course can be seen as a tutorial in using a statistical analysis package (SPSS or R) and includes demonstrations of how to carry out statistical tests in these packages.&lt;/p&gt;&lt;p&gt;SPSS is a menu driven statistical software which is available via a licence code for which there are some restrictions for distance learning students, R is free and open source and can be installed on any computer.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;On campus students only&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;You are expected to attend bi-weekly lectures and other face to face activities. Access to the SPSS software will be available via the PC clusters on campus. &amp;nbsp;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Distance/blended learning students only&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;You will be able to attend bi-weekly webinars which will be recorded. You will download the SPSS software through a secure link from the UoM managed platform ZendTo unless you are a national of a USA embargoed country (see additional notes below) in which case you must use the R software.&amp;nbsp;&lt;/p&gt;&lt;p&gt;This is a mandatory course unit for students studying on the on-campus programme, or an optional course unit for students on the online programme. There are &amp;nbsp;written materials accessible online for all students which guide students through the course and include worked examples, video demos, quizzes and practice tasks. Students are expected to work through these materials in their own time. The lectures and webinars supplement the online resources.&lt;/p&gt;&lt;p&gt;There will be regular interaction with the tutors via the lectures and PC cluster practical sessions on the on-campus programme and &amp;nbsp;online through the webinars and &amp;nbsp;discussion boards. Students will be encouraged to use self-reflection to think about the ideas discussed, and take part in discussion board activities. Students should work through the unit in a logical sequence. The individual course unit timetables will guide what should be done and when. Participation in the discussion boards is greatly encouraged, and can help enhance your learning experience and prepare you for your assessment.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;For all students&lt;/strong&gt; - The majority of the course will be delivered through the virtual learning platform, which will include worked examples, video demos, quizzes, &amp;nbsp;required reading, practice assignments and discussion boards. &amp;nbsp;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Online students &lt;/strong&gt;- There will be webinars that will be recorded to allow synchronous and asynchronous learning. Online students may join webinars live, but it is not mandatory. Recordings of all webinars be made available.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;For on campus students&lt;/strong&gt; - All face-to-face activities are mandatory for all students. Attendance is monitored and an escalation policy is in place for non-attendance. We also have weekly peer-led team study sessions where you will be asked to undertake tasks linked to the course unit materials using the discussion boards.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;For all students&lt;/strong&gt; - In line with guidance from the Office for Students and Quality Assurance Agency, the programme will be augmented by the Programme Director Seminar Series to deliver study skills, written English, academic writing, research skills, &amp;nbsp;critical thinking and understanding arguments, careers and employability skills, revision/assessment/examination skills including time management.&amp;nbsp;&lt;/p&gt;</Content>
  </TeachingMethods>
  <AssessmentMethods Applicant="Y" Label="Assessment methods" Student="Y">
    <IntroText> </IntroText>
    <Method>
      <MethodId>2</MethodId>
      <MethodName>Written assignment (inc essay)</MethodName>
      <MethodWeight>100%</MethodWeight>
    </Method>
  </AssessmentMethods>
  <FeedbackMethods Applicant="Y" Label="Feedback methods" Student="Y">
    <Content>&lt;div&gt;Students will be provided with personalised feedback for their final summative assignment within 20 working days.&lt;br/&gt;&lt;br/&gt;Further opportunities for formative feedback (on non-assessed work) will also be provided during the course unit.&lt;/div&gt;</Content>
  </FeedbackMethods>
  <RequirementsList Applicant="Y" Label="Pre/co-requisites" Student="Y">
    <Requirement>
      <UnitCode></UnitCode>
      <UnitTitle></UnitTitle>
      <RequirementType></RequirementType>
      <Description></Description>
    </Requirement>
  </RequirementsList>
  <AcademicPrograms Applicant="Y" Label="Academic programmes" Student="Y">
    <AcademicProgram>
      <Program>MPH: the evidence bsd app (12)</Program>
      <Plan>Masters in Public Health F2F</Plan>
      <Level>PGDT Taught Component</Level>
      <Requirement>Mandatory</Requirement>
    </AcademicProgram>
  </AcademicPrograms>
  <FreeChoice Applicant="Y" Label="Available as a free choice unit?" Student="Y">
    <Content>N</Content>
  </FreeChoice>
  <Accreditation Applicant="Y" Label="Accreditation" Student="Y">
    <Content></Content>
  </Accreditation>
  <RecommendedReading Applicant="Y" Label="Recommended reading" Student="Y">
    <Content>&lt;p&gt;The core text for the course is: Essential Medical Statistics by Kirkwood and Sterne (2003).&lt;/p&gt;&lt;p&gt;All students should have access to an electronic copy of this book via Koretext which can be accessed via the 'Reading Lists Online' link on the menu in the VLE.&lt;/p&gt;&lt;p&gt;Another useful introductory textbook is An Introduction to Medical Statistics by Martin Bland (2000) (Bland M., 2000).&lt;/p&gt;&lt;p&gt;Students may find the Statistics at Square One website helpful during the course.&amp;nbsp;&lt;/p&gt;</Content>
  </RecommendedReading>
  <StudyHours Applicant="Y" Label="Study hours" Student="Y">
    <IntroText> </IntroText>
    <ScheduledHours Applicant="Y" Label="Scheduled activity hours" Student="Y">
      <ActivityHours>
        <ActivityType>eAssessment</ActivityType>
        <Hours>50</Hours>
      </ActivityHours>
      <ActivityHours>
        <ActivityType>Practical classes &amp; workshops</ActivityType>
        <Hours>23</Hours>
      </ActivityHours>
    </ScheduledHours>
    <PlacementHours Applicant="Y" Label="Placement hours" Student="Y">
      <ActivityHours>
        <ActivityType></ActivityType>
        <Hours></Hours>
      </ActivityHours>
    </PlacementHours>
    <TotalHours Applicant="Y" Label="Independent study hours" Student="Y">
      <Hours>77</Hours>
    </TotalHours>
  </StudyHours>
  <Notes Applicant="Y" Label="Additional notes" Student="Y">
    <Content>&lt;p&gt;If you have any questions about the content of this unit, please contact the course unit leader, Isla Gemmell, via email at &lt;a href="mailto:isla.gemmell@manchester.ac.uk"&gt;isla.gemmell@manchester.ac.uk&lt;/a&gt;. If you have any other queries, please contact the PGT programme team at &lt;a href="mailto:shs.programmes@manchester.ac.uk"&gt;shs.programmes@manchester.ac.uk&lt;/a&gt;.&lt;/p&gt;&lt;p&gt;Embargoed country list &amp;nbsp;&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Afghanistan &amp;nbsp;&lt;/li&gt;&lt;li&gt;Belarus &amp;nbsp;&lt;/li&gt;&lt;li&gt;Burma &amp;nbsp;&lt;/li&gt;&lt;li&gt;Cambodia &amp;nbsp;&lt;/li&gt;&lt;li&gt;Central African Republic &amp;nbsp;&lt;/li&gt;&lt;li&gt;China &amp;nbsp;&lt;/li&gt;&lt;li&gt;Democratic Republic of Congo &amp;nbsp;&lt;/li&gt;&lt;li&gt;Cuba &amp;nbsp;&lt;/li&gt;&lt;li&gt;Cyprus &amp;nbsp;&lt;/li&gt;&lt;li&gt;Eritrea &amp;nbsp;&lt;/li&gt;&lt;li&gt;Haiti &amp;nbsp;&lt;/li&gt;&lt;li&gt;Iran &amp;nbsp;&lt;/li&gt;&lt;li&gt;Iraq &amp;nbsp;&lt;/li&gt;&lt;li&gt;Lebanon &amp;nbsp;&lt;/li&gt;&lt;li&gt;Libya &amp;nbsp;&lt;/li&gt;&lt;li&gt;North Korea &amp;nbsp;&lt;/li&gt;&lt;li&gt;Russia &amp;nbsp;&lt;/li&gt;&lt;li&gt;Somalia &amp;nbsp;&lt;/li&gt;&lt;li&gt;Republic of South Sudan &amp;nbsp;&lt;/li&gt;&lt;li&gt;Sudan &amp;nbsp;&lt;/li&gt;&lt;li&gt;Syria &amp;nbsp;&lt;/li&gt;&lt;li&gt;Venezuela &amp;nbsp;&lt;/li&gt;&lt;li&gt;Zimbabwe&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;Online distance learning students who are nationals of these countries cannot download and install SPSS on their own devices and therefore must use the R software to complete the course.&amp;nbsp;&lt;/p&gt;</Content>
  </Notes>
</CourseUnit>
