DATA401-24S1 (C) Semester One 2024

Introduction to Data Science

15 points

Details:
Start Date: Monday, 19 February 2024
End Date: Sunday, 23 June 2024
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 3 March 2024
  • Without academic penalty (including no fee refund): Sunday, 12 May 2024

Description

This course covers the development of statistical concepts and their application to complex systems.

An introduction to the ideas, techniques and applications of statistics and probability. The emphasis is on applying statistics to problems, selecting sensible techniques, following the methodology and interpreting the results. Understanding the concepts and computer-based solutions are emphasised and applications to commerce, the social sciences, the humanities, science and engineering are considered.

Particular topics include data analysis, summary statistics, probability, statistical distributions, estimation and inference (including confidence intervals, hypothesis tests and modelling) and probability.

As this is a 15 point course students should expect to spend about 150 hours on the course (NZQA guidelines), which comes to 10 hours per week for a 12 week semester on average and an additional 30 hours of study, revision and exam preparation. If you do this, records show you are most likely to pass the course.

Learning Outcomes

Students that complete DATA401 should leave the course with:
A solid conceptual understanding of key statistical concepts and techniques.
The ability and confidence to perform a basic statistical analyses with data, including summarizing data, visualising data and making statistical inferences.
Experience using technology to perform statistical procedures.
An understanding of the importance of data collection and its role in determining the scope of a statistical inference.
The knowledge of which statistical methods to use in which situations and how to interpret their results in context.
A solid statistical foundation for further study in statistics.

University Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attributes specified below:

Employable, innovative and enterprising

Students will develop key skills and attributes sought by employers that can be used in a range of applications.

Engaged with the community

Students will have observed and understood a culture within a community by reflecting on their own performance and experiences within that community.

Globally aware

Students will comprehend the influence of global conditions on their discipline and will be competent in engaging with global and multi-cultural contexts.

Prerequisites

Subject to approval of the Head of School.

Timetable 2024

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Thursday 14:00 - 15:00 Ernest Rutherford 465
19 Feb - 31 Mar
29 Apr - 2 Jun
Lecture B
Activity Day Time Location Weeks
01 Monday 12:00 - 13:00 Ernest Rutherford 465
19 Feb - 31 Mar
22 Apr - 2 Jun
Lecture C
Activity Day Time Location Weeks
01 Tuesday 13:00 - 14:00 F3 Lecture Theatre
19 Feb - 31 Mar
22 Apr - 2 Jun
Tutorial A
Activity Day Time Location Weeks
01 Friday 12:00 - 13:00 Jack Erskine 248 Computer Lab
19 Feb - 24 Mar
22 Apr - 2 Jun
02 Friday 13:00 - 14:00 Jack Erskine 442 Computer Lab
11 Mar - 31 Mar
22 Apr - 2 Jun

Course Coordinator

Robert Culling

Lecturers

Taylor Winter , Speedy Jiang and David Rodda

Indicative Fees

Domestic fee $1,023.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Mathematics and Statistics .

All DATA401 Occurrences