DATAX121-23A (HAM)

Introduction to Statistical Methods

15 Points

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Division of Health Engineering Computing & Science
School of Computing and Mathematical Sciences
Department of Mathematics and Statistics

Staff

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Convenor(s)

Lecturer(s)

Administrator(s)

: maria.admiraal@waikato.ac.nz

Placement/WIL Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: alistair.lamb@waikato.ac.nz

You can contact staff by:

  • Calling +64 7 838 4466 select option 1, then enter the extension.
  • Extensions starting with 4, 5, 9 or 3 can also be direct dialled:
    • For extensions starting with 4: dial +64 7 838 extension.
    • For extensions starting with 5: dial +64 7 858 extension.
    • For extensions starting with 9: dial +64 7 837 extension.
    • For extensions starting with 3: dial +64 7 2620 + the last 3 digits of the extension e.g. 3123 = +64 7 262 0123.
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What this paper is about

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DATAX121 introduces a set of statistical methods used in various disciplines for data analysis—see Topics below for further details. These disciplines include statistics, data science, computer science, natural sciences, health sciences, and social sciences. In particular, DATAX121 aims to improve students' understanding of statistical methods and when they can use them.

We use R because of its popularity in academia and industry and RStudio as the preferred integrated work environment. R and RStudio are open-source software and free to download and use.

DATAX121 does not require students to have any prior programming experience to succeed in the paper.

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How this paper will be taught

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Students are expected to attend lectures, workshops, and computer labs.

Lectures
Three lectures per week; see the timetable below for the schedule. The lectures provide the paper's background, theoretical material, and general information.

Workshops
One workshop per week is held in the second hour of the Friday lecture block, that is, from 12pm to 1pm on Fridays. The workshops provide the R programming material for the paper.

Labs
One computer lab per week, starting from the second week of teaching at the R.G.12 computer laboratory. The lab assignments are designed to reinforce the material covered in the previous week's lectures and provide practice in using R for data analysis. Also, statistics demonstrators can help you during scheduled lab times.

Sign-up for computer labs will be available online via Moodle—You should ONLY attend the lab you signed up for all of A trimester.

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You will need to have

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  • A calculator for the tests and the final exam.
  • Access to a computer or laptop that can run R and RStudio.
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Learning Outcomes

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Students who successfully complete the course should be able to:

  • Effectively explore and summarise data.
    Linked to the following assessments:
    Admin Quiz (1)
    Lab Assignments (2)
    Test 1 (3)
    Test 2 (4)
    Final Exam (5)
  • Understand the purposes and limitations of different data collection methods.
    Linked to the following assessments:
    Lab Assignments (2)
    Test 1 (3)
    Test 2 (4)
    Final Exam (5)
  • Understand the principles of statistical inference.
    Linked to the following assessments:
    Lab Assignments (2)
    Test 1 (3)
    Test 2 (4)
    Final Exam (5)
  • Identify an appropriate statistical method to answer a research question given an arbitrary dataset.
    Linked to the following assessments:
    Test 1 (3)
    Test 2 (4)
    Final Exam (5)
  • Communicate the results of statistical data analysis.
    Linked to the following assessments:
    Lab Assignments (2)
    Test 1 (3)
    Test 2 (4)
    Final Exam (5)
  • Apply statistical data analyses by making use of software.
    Linked to the following assessments:
    Lab Assignments (2)
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Assessments

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How you will be assessed

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The assessment items are listed here. For the percentage contributions to the overall mark, see the table below.

  • Admin Quiz
  • Best NINE out of eleven Lab Assignments
  • TWO Tests
  • Final Exam

The "D" rule: The requirements for an unrestricted pass (C-­ or better) are a minimum overall mark of 50% for the whole paper and a minimum mark of 40% for the final exam.

Please note that, as part of any assessment, students may be asked to complete an oral examination (viva voce) at a later date.

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The internal assessment/exam ratio (as stated in the University Calendar) is 50:50. There is no final exam. The final exam makes up 50% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 50:50 or 0:0, whichever is more favourable for the student. The final exam makes up either 50% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Admin Quiz
10 Mar 2023
5:00 PM
2
  • Other: Moodle Quiz
2. Lab Assignments
18
  • Hand-in: In Lab
  • Online: Submit through Moodle
3. Test 1
5 Apr 2023
6:30 PM
15
4. Test 2
31 May 2023
6:30 PM
15
5. Final Exam
50
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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