CSMAX101-22B (HAM)

The World of Data

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)

David Chan

David Chan
9068
G.3.09
See Moodle
david.chan@waikato.ac.nz

Lecturer(s)

Administrator(s)

: maria.admiraal@waikato.ac.nz

Placement/WIL Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

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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Paper Description

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This course will focus on some of the fundamental ideas and tools for data analysis and statistics, and will also look at some of the current issues surrounding data. The ideas and skills learnt will be useful for both practical applications and quantitative research.

This paper is designed to provide an appreciation of statistical tools. The emphasis is on interpretation and critical reasoning from
statistical analyses, not so much on the technical details and mathematics of the analyses. There will be some basic data handling and analyses done using iNZight Lite and Microsoft Excel. No previous statistical or mathematical knowledge is assumed beyond the numeracy requirements to enter university.

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Paper Structure

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Three lectures a week. All lectures are recorded using Panopto and are uploaded onto Moodle for students to view.

Supplementary videos (such as Excel instruction videos) will also be uploaded onto Moodle as required.

Dedicated computer lab times are available for students to use, however, these will be unsupervised.

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Learning Outcomes

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Students who successfully complete the paper should be able to:

  • Understand and interpret data summaries and graphs
    Linked to the following assessments:
  • Understand different data types, and how they may be distributed
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  • How to collect data, depending on the type of study you are performing and the questions you are trying to answer
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  • Understand different sampling methods, and their advantages/disadvantages over other methods
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  • Describe the relationships between two variables and understand the measures that are used to describe them
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  • Analyse hypothesis tests for means and proportions
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  • Understand what a confidence interval is, and how to interpret it
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  • Perform some elementary data analyses using Microsoft Excel
    Linked to the following assessments:
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Assessment

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The assessment will consist of:

Two tests, each worth 25% of your final mark,

Two assignments, each worth 15% of your final mark,

One admin quiz, worth 2% of your final mark,

Twelve weekly quizzes, worth 18% of your final mark. The best nine out of twelve quizzes will contribute to this 18% of your final mark.

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Assessment Components

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The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam. The final exam makes up 0% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0 or 0:0, whichever is more favourable for the student. The final exam makes up either 0% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Admin Quiz
29 Jul 2022
11:30 PM
2
  • Online: Submit through Moodle
2. Weekly Quizzes
18
  • Online: Submit through Moodle
3. Assignment 1
16 Sep 2022
5:00 PM
15
  • Online: Submit through Moodle
4. Assignment 2
28 Oct 2022
5:00 PM
15
  • Online: Submit through Moodle
5. Test 1
26 Aug 2022
9:00 AM
25
  • In Class: In Lecture
6. Test 2
21 Oct 2022
9:00 AM
25
  • In Class: In Lecture
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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Seeing Through Statistics 4th edition by Jessica Utts (Cengage)
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Online Support

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All lectures and lecture materials will be provided on Moodle.

iNZight will be used during the lectures and throughout the weekly quizzes. We will be using the "Lite" version of iNZight which is a web browser application and can be accessed through the following link:

https://lite.docker.stat.auckland.ac.nz/

Microsoft Excel is needed to perform data analysis tasks, and Microsoft Word (or equivalent) will be required to prepare the two assignments. Microsoft Office 365 is available and free to all enrolled University of Waikato students. Instructions to download can be found through the following link:

https://www.waikato.ac.nz/ict-self-help/guides/free-microsoft-office-suite-download

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Workload

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Students are expected to spend around 10 hours a week on this course. This includes lectures, time spent on weekly quizzes, studying for assignments and tests, and your own self-directed study.
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Linkages to Other Papers

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For further study in data analysis and statistics (such as STATS221), students should aim for a mark of a B- or better in this course.

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Prerequisite(s)

Corequisite(s)

Equivalent(s)

Restriction(s)

Restricted papers: (STATS111 or DATAX111) and (STATS121 or DATAX121)

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