STATS121-19A (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)

Bob Durrant

Bob Durrant
8334
G.3.31
To be advised
bob.durrant@waikato.ac.nz

Paul Brown

Paul Brown
5279
G.3.30
To be advised
paul.brown@waikato.ac.nz

Lyn Hunt

Lyn Hunt
8338
G.3.21
To be advised
lyn.hunt@waikato.ac.nz

Administrator(s)

: rachael.foote@waikato.ac.nz

Placement Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: debby.dada@waikato.ac.nz
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You can contact staff by:

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  • Extensions starting with 4, 5, 9 or 3 can also be direct dialled:
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    • 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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Paper Description

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STATS121-19A provides an introduction to statistical data collection and analysis for students in statistics, science and technology, computer science and the social sciences. It covers a selection of the statistical tools necessary for the effective use and analysis of data in research and practice.

Topics covered include general principles for statistical problem solving; sampling and experimental design; techniques for extracting information from data; some practical examples of statistical inference; and the study of relationships between variables using regression analysis. The statistical computer software package Minitab is used for most of the statistical computations and graphical displays.

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Paper Structure

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Lectures begin in the week commencing Monday 25 February 2019. There are three one-hour lectures per week and a one-hour tutorial/lab session.

Students should attend all lectures as they provide the background, the theoretical material and general information for the paper.

The course notes booklet should be brought along to lectures each week as it contains notes for the material covered. Extra material may also be covered in lectures.


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Learning Outcomes

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Students who successfully complete the course should be able to:

  • Learning Outcomes
    • Collect and make effective use of data for answering questions within the scope of the techniques taught on this course. The lecture schedule specifies the range of techniques covered.
    • Identify which technique(s) to apply for a particular type of question.
    Linked to the following assessments:
  • Generic Skills

    in addition to the discipline-based learning objectives, the paper aims for students to develop their skills in:

    * manipulating and analysing data using Minitab;

    * critical thinking.

    Linked to the following assessments:
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Assessment

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Final Assessment:

  • This is comprised of two components - your internal coursework and your final exam. The internal coursework : final exam ratio will be (50):(50). However you must achieve at least 40% in both internal coursework and final exam to achieve a clear pass.

Internal Coursework Assessment:

  • Two tests and one one-hour weekly tutorial/lab assessment.

Tutorial Assessment:

  • There will be a total of 10 tutorials/labs - these will be marked on a scale of 0-10. Preparation marks may be assigned for each tutorial. These will be assigned according to how much of the tutorial preparation work you have done. Tutorial exercises will be posted on Moodle on Friday mornings, and will be due for completion and submission during the following week.
  • All tutorial/lab assignments should be completed and handed in for marking by 11am on Fridays in the week that it is due. Tutorial work handed in after the 11am Friday deadline will NOT be marked.
  • Assignments should be submitted in the boxes situated on Level 3 of G Block - on exiting the G block lift at Level 3, turn right.
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Assessment Components

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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. Test 1
5 Apr 2019
11:00 AM
15
2. Test 2
24 May 2019
11:00 AM
15
3. Tutorial Assessment
20
  • Hand-in: Assignment Box (G Block)
4. 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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Required and Recommended Readings

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Recommended Readings

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Mind on Statistics (5th edition) by Utts and Heckard.

Those students with copies of the 4th or 3rd Edition of Mind on Statistics by Utts and Heckard, should find it adequate as a reference book for the topics covered.

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Other Resources

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The course notes booklet is available for purchase from Waikato Print.

The booklet also contains an Introduction to Minitab and some practical exercises.

This booklet is an integral component of the paper and it is highly recommended that students purchase it.

Note that additional material may also be covered in class.

All other course material, such as tutorial exercises and the suggested answers to the practical exercises, can be accessed by logging on to Moodle. (http://elearn.waikato.ac.nz/).

Lectures are recorded on Panopto and a link to each recording is also accessible through the Moodle page. Additional Panopto material may be added from time to time. Tutorial exercises, plus the relevant data sets, will also be available on the R block Lab server in the STATS121 Folder.

Software:

Minitab: Minitab 18 is commercial software. The University of Waikato has purchased a license for Minitab 18 that makes the full version available free of charge for all university staff and students. Note that once you leave the university, or if you want to use Minitab for commercial purposes, you will need to purchase your own copy from http://www.onthehub.com/minitab/.

To install your free copy of Minitab, see the top of the Moodle page for this course for instructions. You will need to check a box saying you have read and understood the conditions of use for the software before downloading the license file.

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Online Support

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Online support will be provided via Moodle and Panopto recordings.
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Workload

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Students should expect to spend a minimum of about 10 hours per week on this paper. This includes the 5 contact hours mentioned above (lectures, workshop and tutorial).
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Linkages to Other Papers

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Prerequisite(s)

Prerequisite papers: MATHS168, MATH168; or 18 credits at Level 2 in NCEA Mathematics; or 14 credits at Level 3 in NCEA Statistics, Calculus or Mathematics.

Corequisite(s)

Equivalent(s)

Restriction(s)

Restricted papers: STAT111, STAT160, STATS111 and STAT121

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