STATS 101/101G : Introduction to Statistics
Science
2022 Semester Two (1225) (15 POINTS)
Course Prescription
Course Overview
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 degrees 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.
Capabilities Developed in this Course
Capability 1: | Disciplinary Knowledge and Practice |
Capability 2: | Critical Thinking |
Capability 3: | Solution Seeking |
Capability 4: | Communication and Engagement |
Capability 5: | Independence and Integrity |
Capability 6: | Social and Environmental Responsibilities |
Learning Outcomes
- Identify the main components of a statistical investigation. (Capability 1 and 3)
- Identify the characteristics of well-designed studies, critique strengths and weaknesses of study designs and data collections. (Capability 1, 2, 3, 4, 5 and 6)
- Use appropriate tools for exploratory data analysis. (Capability 1 and 3)
- Form and communicate conclusions from basic exploratory analysis. (Capability 1, 2, 4 and 5)
- Apply basic concepts of proportions. (Capability 1 and 3)
- Apply the basic concepts of statistical inference and choose appropriate inferential tools. (Capability 1 and 3)
- Form and communicate the results of statistical analysis output. (Capability 1, 2, 4 and 5)
Assessments
Assessment Type | Percentage | Classification |
---|---|---|
Assignments and online quizzes | 30% | Individual Coursework |
Mid-Semester Online test | 20% | Individual Coursework |
Final Exam | 50% | Individual Examination |
3 types | 100% |
Assessment Type | Learning Outcome Addressed | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | ||||
Assignments and online quizzes | ||||||||||
Mid-Semester Online test | ||||||||||
Final Exam |
Partial plussage applies to the test and exam. If the exam mark is higher than the test, the test counts 10% and the exam counts 60% instead.
Tuākana
Contacts are Susan Wingfield (s.wingfield@auckland.ac.nz) and
Heti Afimeimounga (h.afimeimounga@auckland.ac.nz).
More information can be found at:
https://www.auckland.ac.nz/en/science/study-with-us/maori-and-pacific-at-the-faculty/tuakana-programme.
Key Topics
1 – Exploring Data
Exploratory data analysis: sources of data, types of data, data organisation, types of variables, types of plots, types of numerical summaries, feature spotting, describing and comparing variables, graphical techniques with software. Proportional reasoning: estimates, likely outcomes, conditional situations, independence, relative risk, two-way tables of counts, notation, plots.
2 – Observational Studies and Experiments
Observational studies, experimentation, experimental design.
3 – Randomisation Tests with Experiments
Randomisation tests for medians, means, proportions, differences between medians, differences between means, differences between proportions.
4 – Polls and Surveys
Polls and surveys, random sampling.
5 – Bootstrap Confidence Intervals
Bootstrap confidence intervals for medians, means, proportions, differences between medians, differences between means, differences between proportions.
6 – Confidence Intervals (Normality-based)
Confidence intervals for population means and proportions and differences between means and proportions.
7 – Hypothesis Testing
Tests for population means and proportions. Tests for the difference between two means. Large sample comparisons of two proportions.
8 – Data on Numeric Variables
Integrated treatment of problems involving batches of data. How do tools for exploring data, confidence intervals, and hypothesis tests work together? One-way analysis of variance. Paired comparisons.
9 – Data on Categorical Variables
Chi-square test and graphical methods for two-way tables of counts.
10 – Relationships between Numeric Variables: Regression and Correlation
Fitting straight lines by least-squares. Confidence intervals and tests for slope. Prediction intervals. Residual plots.
Workload Expectations
For this course, you can expect a total of 36 hours of lectures, 66 hours of reading and thinking about the content and 48 hours of work on assignments and/or test preparation (including up to 12 hours of optional tutorials).
Delivery Mode
Campus Experience or Online
Campus Experience
Lectures will be available as recordings.
Attendance on campus is not required for the test but is required for the exam.
The activities for the course are scheduled as a standard weekly timetable.
Online (Recorded lecture only stream.)
Lectures will be only available as recordings.
Attendance on campus is not required for the test BUT IS required for the exam.
The activities for the course are scheduled as a standard weekly timetable. Recorded lectures will be uploaded at the start of each week.
Students can still access any on-campus support such as assistance room, lab support and optional tutorials.
This course is available for remote students.
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.
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.
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 against online source material 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.