STATS 101/101G : Introduction to Statistics

Science

2024 Semester Two (1245) (15 POINTS)

Course Prescription

Intended for anyone who will ever have to collect or make sense of data, either in their career or private life. Steps involved in conducting a statistical investigation are studied with the main emphasis being on data analysis and the background concepts necessary for successfully analysing data, extrapolating from patterns in data to more generally applicable conclusions and communicating results to others. Other topics include probability; confidence intervals, statistical significance, t-tests, and p-values; nonparametric methods; one-way analysis of variance, simple linear regression, correlation, tables of counts and the chi-square test.

Course Overview

An ability to gain insight from data enables organisations and individuals to inform their decisions, make predictions and generate new knowledge. Advances in technology allow us new ways of thinking and reasoning in the physical and social sciences, and finance. The purpose of this course is to introduce students to statistical investigation and analysis, and equip them with the skills and confidence needed to navigate the modern world of data. 

This is a core course in all majors/pathways for Statistics. It is also a supporting course for many other subjects (e.g. Psychology, Economics, Finance, Mathematics, Computer Science, Geography, Biology, Sociology,…).

The course covers some material similar to NCEA statistics but at a higher level and more advanced material is also covered. While some Year 13 statistics or mathematics is helpful, we do not assume or require that you have any formal background in statistics or mathematics. If you have a limited background in mathematics, you may want to consider STATS 100 as an alternate course or as preparation before taking this course.

Course Requirements

Restriction: STATS 102, 107, 108, 191

Capabilities Developed in this Course

Capability 1: People and Place
Capability 2: Sustainability
Capability 3: Knowledge and Practice
Capability 4: Critical Thinking
Capability 5: Solution Seeking
Capability 6: Communication
Capability 7: Collaboration
Capability 8: Ethics and Professionalism
Graduate Profile: Bachelor of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Recognise different purposes and motivations for making data-based decisions and the consequences of those decisions for affected communities. (Capability 2 and 5)
  2. Describe ethical, responsible, and culturally-responsive data practices, acknowledging Māori Data Sovereignty. (Capability 1 and 8)
  3. Use data generated from a range of sources, considering how decisions made affect its quality, diversity, and quantity. (Capability 1 and 8)
  4. Develop models using data, representations and critical reasoning, considering the applicability and generalisability of models and model-based claims. (Capability 3)
  5. Select and apply appropriate technology to analyse data, considering automated and reproducible approaches. (Capability 4)
  6. Produce written summaries that communicate the uncertainty associated with data, and interpret and critique communications produced by others. (Capability 6 and 7)

Assessments

Assessment Type Percentage Classification
Online tasks and quizzes 30% Individual Coursework
Online test 20% Individual Coursework
Final Exam 50% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6
Online tasks and quizzes
Online test
Final Exam
A minimum of 45% is required in the exam to pass, in addition to a minimum of 50% in your overall mark.

Tuākana

Tuākana Science is a multi-faceted programme for Māori and Pacific students providing topic specific tutorials, one-on-one sessions, test and exam preparation and more. Explore your options at
https://www.auckland.ac.nz/en/science/study-with-us/pacific-in-our-faculty.html
https://www.auckland.ac.nz/en/science/study-with-us/maori-in-our-faculty.html

Statistics has a Tuākana Programme where there is a workspace and a social space shared with Science Tuakana students. Tutorials and one-to-one assistance are available. Tuākana tutors/mentors work alongside the lecturer to support students with assignments and revision for the quizzes and exams. For more information and to find contact details for the Statistics Tuākana coordinator, please see https://www.auckland.ac.nz/en/science/study-with-us/maori-and-pacific-at-the-faculty/tuakana-programme.html
Contacts are Susan Wingfield (s.wingfield@auckland.ac.nz) and Heti Afimeimounga (h.afimeimounga@auckland.ac.nz).

Key Topics

  • Module 1: Modern data technologies and responsibilities (Datafication, Classification, Prediction, Randomisation)
  • Module 2: Making and evaluating claims or decisions based on data (Estimation, Quantification, Confirmation, Explanation)
  • Module 3: Designing and communicating about data (Variation, Distribution, Regression, Generalisation)

Special Requirements

The online test will be held during the evening.

Choosing your course:
If you are studying for a BCom, BProp, BPlan or BArch you should enrol in STATS 108.
If you are studying for a BSc, BA or other degree you should enrol in STATS 101.
If you are eligible, you may be able to take STATS 101 as a General Education course. In which case enrol in STATS 101G. Check the General Education regulations for more details.
If you have a limited background in mathematics, you may want to consider STATS 100 as an alternate course or as preparation before taking this course.

Workload Expectations

This course is a standard 15-point course and students are expected to spend 12.5 hours per week involved in each 15-point course that they are enrolled in.
For this course, a typical weekly workload includes:
  • 3 hours of lectures
  • Regular drop-in help sessions
  • 5-6 hours of reading and thinking about the content
  • 4 hours of work on tasks, quizzes and/or test preparation (including up to 1 hour of optional drop-in help sessions).

Delivery Mode

Campus Experience

Lectures will be available as recordings. Other learning activities including drop-in help sessions will not be available as recordings.
The course will include live online events including lectures.

The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Access to a custom online coursebook is provided via Canvas. 

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

For example, student feedback has been considered when decisions have been made regarding: updating the learning resources for the course, spreading out assessment workload as weekly chapter tasks, and changing assessment due times to be later in the day.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed for potential plagiarism or other forms of academic misconduct, using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Copyright

The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

The delivery mode may change depending on COVID restrictions. Any changes will be communicated through Canvas.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.