Statistics
Te Tari Pāngarau me te Tatauranga
Department of Mathematics & Statistics

## STAT241 Regression & Modelling 1

 First Semester
18 points
From 2019 this will be replaced by STAT210

Regression and modeling, the “core techniques” of modern statistical analysis, appear regularly in the research journals of many fields ranging from the health sciences, nutrition, epidemiology, ecology, environmental science, zoology and botany to sociology, marketing, economics and finance. In many settings there is a response or outcome being researched and a number, often quite large, of potential causal factors. A regression analysis develops equations which assist in identifying important influences on an outcome measure. The regression procedures allow correction for potential confounding effects as well as suggesting hypotheses for future investigation with designed experiments. The paper uses the statistical packages SPSS 22 and R.

This paper is central for the advanced study of statistics and biostatistics. It is the first in a regression sequence which extends from second to fourth year in statistics. It is an excellent paper for a minor in statistics as well as the Diploma for Graduates endorsed in statistics. It is a prerequisite for the applied time series paper at third year level.

### Paper details

Regression summarises (or models) complex data in a compact way and identifies factors which explain variability in an outcome measure. The data are frequently observational but some designed studies are also analysed. Economists use regression for forecasting, ecologists employ regression to study the effects of tourism on dolphin behaviour, sociologists build regression based causal models, a nutrition scientist models dietary factors which inhibit and enhance iron storage levels in newborn babies, epidemiologists investigate factors which influence cot death. These studies involve the systematic assessment of various exposure variables on an outcome of interest and make adjustments for covariates or confounders which affect both the outcome and possibly some exposure variables in the model. The methods developed are covered and involve simple linear, multiple linear and logistic regression procedures along with conditions required for the correct use of these methods.

### Potential students

All students who intend to major in statistics or biostatistics should take this paper. It is a key paper for a minor in Statistics, for the DipGrad endorsed in Statistics or for a double major. The paper is useful as an advanced-service statistics paper for all students majoring in any of the subjects listed above. There is no mathematics prerequisite and the paper can be taken with a background of either STAT 110 or STAT 115. It is the first in a regression sequence that extends from second to fourth year in statistics. The paper is also useful as an advanced service statistics paper for all students majoring in any of the subjects listed above or for postgraduates in many other subjects. The paper uses the statistical package SPSS as well as R. It leads into the third year STAT 341, STAT 352 and STAT 380 as well as being helpful for Stat 342. These four papers can also be taken without mathematics prerequisites.

### Prerequisites

STAT 110 or STAT 115

### Main topics

• Simple linear regression
• Multiple linear regression
• Model building and model diagnostics
• Outliers and influential points
• Dummy variables, categorical predictors
• Factorial experiments and interactions
• Two factor unbalanced experiments
• Sequential data and interrupted time series
• Logistic regression for binary data
• Comparison of logistic models
• Confidence intervals for odds ratios
• Adjustments for covariates and confounders
• Binomial responses and overdispersion
• Multinomial logistic regression

### Required text

None, course notes will be available for purchase at the University Print Shop.

### Lecturers

Assoc Professor John Harraway, Room 238, Science III

Dr Tilman Davies, Room 222, Science III

### Lectures

Tuesday ( OBSG17 ), Thursday ( R7N10 ) and Friday ( OBSG17 ) at 1pm.

We will sometimes alternate between all three and only two lectures a week; students will be informed well in advance. Total of 33 lectures.

### Tutorials

One hour per week at times to be arranged. The tutorials begin in week 2 of the semester and are scheduled for 2pm on Monday, Wednesday or Thursday. They are all held in B21 Science III.

### Internal Assessment

Nine or ten exercises contributing 50 marks.

A mid semester test in week 11 of the semester contributing 50 marks.

### Exam format

A three-hour written examination worth 100 marks.

### Final mark

Your final mark F in the paper will be calculated according to this formula:

F = max(E, (4E + A + T)/6)

where:

• E is the Exam mark
• A is the Assignments mark
• T is the Test mark

and all quantities are expressed as percentages.

### Students must abide by the University’s Academic Integrity Policy

Academic integrity means being honest in your studying and assessments. It is the basis for ethical decision-making and behaviour in an academic context. Academic integrity is informed by the values of honesty, trust, responsibility, fairness, respect and courage.

Academic misconduct is seeking to gain for yourself, or assisting another person to gain, an academic advantage by deception or other unfair means. The most common form of academic misconduct is plagiarism.

Academic misconduct in relation to work submitted for assessment (including all course work, tests and examinations) is taken very seriously at the University of Otago.

All students have a responsibility to understand the requirements that apply to particular assessments and also to be aware of acceptable academic practice regarding the use of material prepared by others. Therefore it is important to be familiar with the rules surrounding academic misconduct at the University of Otago; they may be different from the rules in your previous place of study.

Any student involved in academic misconduct, whether intentional or arising through failure to take reasonable care, will be subject to the University’s Student Academic Misconduct Procedures which contain a range of penalties.

If you are ever in doubt concerning what may be acceptable academic practice in relation to assessment, you should clarify the situation with your lecturer before submitting the work or taking the test or examination involved.

Types of academic misconduct are as follows:

#### Plagiarism

The University makes a distinction between unintentional plagiarism (Level One) and intentional plagiarism (Level Two).

• Although not intended, unintentional plagiarism is covered by the Student Academic Misconduct Procedures. It is usually due to lack of care, naivety, and/or to a lack to understanding of acceptable academic behaviour. This kind of plagiarism can be easily avoided.
• Intentional plagiarism is gaining academic advantage by copying or paraphrasing someone elses work and presenting it as your own, or helping someone else copy your work and present it as their own. It also includes self-plagiarism which is when you use your own work in a different paper or programme without indicating the source. Intentional plagiarism is treated very seriously by the University.

#### Unauthorised Collaboration

Unauthorised Collaboration occurs when you work with, or share work with, others on an assessment which is designed as a task for individuals and in which individual answers are required. This form does not include assessment tasks where students are required or permitted to present their results as collaborative work. Nor does it preclude collaborative effort in research or study for assignments, tests or examinations; but unless it is explicitly stated otherwise, each students answers should be in their own words. If you are not sure if collaboration is allowed, check with your lecturer..

#### Impersonation

Impersonation is getting someone else to participate in any assessment on your behalf, including having someone else sit any test or examination on your behalf.

#### Falsiﬁcation

Falsiﬁcation is to falsify the results of your research; presenting as true or accurate material that you know to be false or inaccurate.

#### Use of Unauthorised Materials

Unless expressly permitted, notes, books, calculators, computers or any other material and equipment are not permitted into a test or examination. Make sure you read the examination rules carefully. If you are still not sure what you are allowed to take in, check with your lecturer.

#### Assisting Others to Commit Academic Misconduct

This includes impersonating another student in a test or examination; writing an assignment for another student; giving answers to another student in a test or examination by any direct or indirect means; and allowing another student to copy answers in a test, examination or any other assessment.

Further information

While we strive to keep details as accurate and up-to-date as possible, information given here should be regarded as provisional. Individual lecturers will confirm teaching and assessment methods.

Concern about iron deficiency in New Zealand infants and toddlers initiated a large-scale survey in the South Island by the University’s Department of Human Nutrition. The impact of breast feeding compared with use of cows milk is assessed after correcting for infections which can confound the result in both diet groups.

Is there support or lack of support in a community to an expensive project using public funds? How do we carry out the survey and analyse the data? The profile of the Dunedin ratepayers who supported the building of the Dunedin covered stadium are identified from a postal survey which produced about 1800 respondents.
Habitat selection by wild animals is a major issue in environmental science, in particular in protecting the habitat of endangered species to ensure the survival of such a species

The New Zealand Hector’s dolphin is an endangered animal and a study is being carried out to establish factors which may determine a preferred habitat. These factors include water temperature, water clarity and water depth, as well as seasonal effects and prey abundance. Regression analysis identifies those factors that influence the dolphins’ choice of habitat. A set of data based on an investigation of 980 sites around the South Island, half the sites having dolphins present, is analysed in this paper. Some seasonal effects have been identified.