STAT110 Statistical Methods

Descriptive statistics, probability distributions, estimation, hypothesis testing, regression, analysis of count data, analysis of variance and experimental design. Sampling and design principles of techniques to build on in the implementation of research studies.

This is a paper in statistical methods for students from any of the sciences, including students studying biological sciences, social sciences or sport science, as well as those studying mathematics and statistics. The paper provides an introduction to the use of statistical methods for the description and analysis of data, use of computer software to carry out data analysis, and the interpretation of the results of statistical analyses for a range of research studies.

Paper title Statistical Methods STAT110 Statistics 0.15 18 points Summer School (On campus) Semester 1 (On campus) \$913.95 \$4,073.40
Restriction
STAT 115, (BSNS 102 or BSNS 112), QUAN 101
Schedule C
Arts and Music, Science
Eligibility
Suitable for students of all disciplines with an interest in the quantitative analysis of data. There are no formal mathematical or statistical prerequisites for this paper, but students who have not done mathematics or statistics at NCEA Level 3 are encouraged to make use of the online and tutorial resources available as part of the paper.
Contact
stat110@maths.otago.ac.nz
Teaching staff

Summer School Course Co-ordinator: Dr Tilman Davies and Megan Drysdale

Semester 1: Dr Phillip Wilcox and Megan Drysdale

Paper Structure

The paper covers:

• Data: where does it come from and how should we collect it?
• Probability
• Binomial and normal distributions
• Sampling distributions
• Confidence Intervals and estimation
• Hypothesis testing and power
• Contingency tables for categorical data
• Analysis of variance
• Regression including simple linear and multiple linear with confounding discussion.
Teaching Arrangements

Four 1-hour lectures per week, plus cafeteria-style (voluntary attendance) tutorials each week for assistance with course material and exercises.

Textbooks

There is no set text. Copies of all lecture slides area available at the start of the course either in electronic or paper form.

Interdisciplinary perspective, Scholarship, Communication, Critical thinking, Information literacy.
Learning Outcomes
Demonstrate awareness of and proficiency in the basics of objective statistical data analysis.

Timetable

Summer School

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Other

Lecture

Stream Days Times Weeks
Attend
L1 Monday 10:00-11:50 2-5, 7
Tuesday 10:00-11:50 2-7
Wednesday 10:00-11:50 2-7
Thursday 10:00-11:50 2-7

Semester 1

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Other

Lecture

Stream Days Times Weeks
Attend one stream from
A1 Monday 10:00-10:50 9-13, 15-16, 18-22
A2 Monday 08:00-08:50 9-13, 15-16, 18-22
AND one stream from
B1 Tuesday 10:00-10:50 9-13, 15-22
B2 Tuesday 08:00-08:50 9-13, 15-22
AND one stream from
C1 Wednesday 10:00-10:50 9-13, 15-22
C2 Wednesday 08:00-08:50 9-13, 15-22
AND one stream from
D1 Thursday 10:00-10:50 9-13, 15-22
D2 Thursday 08:00-08:50 9-13, 15-22

Descriptive statistics, probability distributions, estimation, hypothesis testing, regression, analysis of count data, analysis of variance and experimental design. Sampling and design principles of techniques to build on in the implementation of research studies.

This is a paper in statistical methods for students from any of the sciences, including students studying biological sciences, social sciences or sport science, as well as those studying mathematics and statistics. The paper provides an introduction to the use of statistical methods for the description and analysis of data, use of computer software to carry out data analysis, and the interpretation of the results of statistical analyses for a range of research studies.

Paper title Statistical Methods STAT110 Statistics 0.15 18 points Summer School (On campus) Semester 1 (On campus) Tuition Fees for 2022 have not yet been set Tuition Fees for international students are elsewhere on this website.
Restriction
STAT 115, (BSNS 102 or BSNS 112), QUAN 101
Schedule C
Arts and Music, Science
Eligibility
Suitable for students of all disciplines with an interest in the quantitative analysis of data. There are no formal mathematical or statistical prerequisites for this paper, but students who have not done mathematics or statistics at NCEA Level 3 are encouraged to make use of the online and tutorial resources available as part of the paper.
Contact
stat110@maths.otago.ac.nz
Teaching staff

Summer School Course Co-ordinator: Dr Tilman Davies and Megan Drysdale

Semester 1: Dr Matthew Schofield and Megan Drysdale

Paper Structure

The paper covers:

• Data: where does it come from and how should we collect it?
• Probability
• Binomial and normal distributions
• Sampling distributions
• Confidence Intervals and estimation
• Hypothesis testing and power
• Contingency tables for categorical data
• Analysis of variance
• Regression including simple linear and multiple linear with confounding discussion
Teaching Arrangements

Four 1-hour lectures per week, plus cafeteria-style (voluntary attendance) tutorials each week for assistance with course material and exercises.

Textbooks

There is no set text. Copies of all lecture slides area available at the start of the course either in electronic or paper form.

Interdisciplinary perspective, Scholarship, Communication, Critical thinking, Information literacy.
Learning Outcomes
Demonstrate awareness of and proficiency in the basics of objective statistical data analysis.

Timetable

Summer School

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Other

Lecture

Stream Days Times Weeks
Attend
L1 Monday 10:00-11:50 2-5, 7
Tuesday 10:00-11:50 2-7
Wednesday 10:00-11:50 2-7
Thursday 10:00-11:50 2-7

Semester 1

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Other

Lecture

Stream Days Times Weeks
Attend one stream from
A1 Monday 10:00-10:50 9-15, 18-22
A2 Monday 08:00-08:50 9-15, 18-22
AND one stream from
B1 Tuesday 10:00-10:50 9-15, 17-22
B2 Tuesday 08:00-08:50 9-15, 17-22
AND one stream from
C1 Wednesday 10:00-10:50 9-15, 17-22
C2 Wednesday 08:00-08:50 9-15, 17-22
AND one stream from
D1 Thursday 10:00-10:50 9-15, 17-22
D2 Thursday 08:00-08:50 9-15, 17-22