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Overview

Introduction to types of business decisions and selection of appropriate quantitative or qualitative data gathering techniques. Characteristics of data types, application of tools, interpretations of results and ethical issues.

About this paper

Paper title Interpreting Business Data
Subject Business Studies
EFTS 0.15
Points 18 points
Teaching period(s) Semester 1 (On campus)
Semester 2 (On campus)
Domestic Tuition Fees ( NZD ) $1,053.30
International Tuition Fees Tuition Fees for international students are elsewhere on this website.
Restriction
BSNS 102, STAT 110, STAT 115
Schedule C
Commerce
Notes
This is a required paper for BCom from 2017 (to be taken in place of BSNS102 by students completing under earlier regulations).
Contact

economics@otago.ac.nz

Teaching staff

Semester 1: Mark Millin  (Economics)

Semester 2: Dr Peter Gibbard (Economics)

Textbooks

Selvanathan, E.A., Selvanathan, S., & Keller, G. (2021). Business statistics: Australia/New Zealand. 8th edition. South Melbourne, Victoria: Cengage. [ISBN: 9780170439527]

Graduate Attributes Emphasised
Critical Thinking, Research, Interdisciplinary Perspective, Scholarship, Ethics.
View more information about Otago's graduate attributes.
Learning Outcomes
Students who successfully complete the paper will:
  • Be able to describe different types of business decisions and their associated characteristics
  • Understand the process of business decisions, including the articulation of relevant questions, data collection, data analysis and interpretation
  • Be able to select an appropriate quantitative or qualitative technique to answer a given question, taking into account its strengths and weaknesses and the characteristics of the data
  • Be familiar with some of the tools used to perform quantitative and qualitative data analysis
  • Demonstrate awareness of ethical and privacy issues relating to data collection and analysis
  • Be able to interpret critically the result of data analysis

Timetable

Semester 1

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

Computer Lab

Stream Days Times Weeks
Attend one stream from
A1 Tuesday 10:00-10:50 10-14, 16-18
A2 Tuesday 10:00-10:50 10-14, 16-18
A3 Tuesday 11:00-11:50 10-14, 16-18
A4 Tuesday 11:00-11:50 10-14, 16-18
A5 Thursday 12:00-12:50 10-14, 16-18
A6 Thursday 12:00-12:50 10-14, 16-18
A7 Thursday 13:00-13:50 10-14, 16-18
A8 Thursday 13:00-13:50 10-14, 16-18
A9 Tuesday 14:00-14:50 10-14, 16-18
A10 Tuesday 14:00-14:50 10-14, 16-18
A11 Tuesday 09:00-09:50 10-14, 16-18
A12 Tuesday 09:00-09:50 10-14, 16-18
A13 Friday 08:00-08:50 10-13, 16-18
A14 Friday 08:00-08:50 10-13, 16-18
A15 Wednesday 14:00-14:50 10-14, 16-18
A16 Wednesday 14:00-14:50 10-14, 16-18
A17 Tuesday 13:00-13:50 10-14, 16-18
A18 Tuesday 13:00-13:50 10-14, 16-18
A19 Wednesday 12:00-12:50 10-14, 16-18
A20 Wednesday 12:00-12:50 10-14, 16-18

Lecture

Stream Days Times Weeks
Attend one stream from
A1 Monday 10:00-10:50 9-14, 16-17, 19-22
A2 Monday 11:00-11:50 9-14, 16-17, 19-22
AND one stream from
B1 Wednesday 09:00-09:50 9-14, 16-22
B2 Wednesday 11:00-11:50 9-14, 16-22
AND one stream from
C1 Thursday 10:00-10:50 9-14, 16-22
C2 Thursday 11:00-11:50 9-14, 16-22

Terms Test (Streamed)

Stream Days Times Weeks
Attend one stream from
A1 Tuesday 19:00-19:50 17
A2 Tuesday 19:00-19:50 17
A3 Tuesday 19:00-19:50 17
A4 Tuesday 19:00-19:50 17

Semester 2

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

Computer Lab

Stream Days Times Weeks
Attend one stream from
A1 Tuesday 15:00-15:50 30-35, 37-38
A2 Tuesday 15:00-15:50 30-35, 37-38
A3 Friday 13:00-13:50 30-35, 37-38
A4 Friday 13:00-13:50 30-35, 37-38
A5 Tuesday 10:00-10:50 30-35, 37-38
A6 Tuesday 10:00-10:50 30-35, 37-38
A7 Thursday 09:00-09:50 30-35, 37-38
A8 Thursday 09:00-09:50 30-35, 37-38
A9 Monday 16:00-16:50 30-35, 37-38
A10 Monday 16:00-16:50 30-35, 37-38
A11 Tuesday 16:00-16:50 30-35, 37-38
A12 Tuesday 16:00-16:50 30-35, 37-38

Lecture

Stream Days Times Weeks
Attend
A1 Monday 13:00-13:50 29-35, 37-42
Tuesday 11:00-11:50 29-35, 37-42
Thursday 14:00-14:50 29-35, 37-42

Terms Test (Streamed)

Stream Days Times Weeks
Attend one stream from
A1 Monday 19:00-19:50 35
A2 Monday 19:00-19:50 35

Overview

Introduction to types of business decisions and selection of appropriate quantitative or qualitative data gathering techniques. Characteristics of data types, application of tools, interpretations of results and ethical issues.

About this paper

Paper title Interpreting Business Data
Subject Business Studies
EFTS 0.15
Points 18 points
Teaching period(s) Semester 1 (On campus)
Semester 2 (On campus)
Domestic Tuition Fees Tuition Fees for 2027 have not yet been set
International Tuition Fees Tuition Fees for international students are elsewhere on this website.
Restriction
BSNS 102, STAT 110, STAT 115
Schedule C
Commerce
Notes
This is a required paper for BCom from 2017 (to be taken in place of BSNS102 by students completing under earlier regulations).
Contact

economics@otago.ac.nz

Teaching staff

Semester 1: Mark Millin (Economics)

Semester 2: Dr Peter Gibbard (Economics)

Textbooks

Selvanathan, E.A., Selvanathan, S., & Keller, G. (2021). Business statistics: Australia/New Zealand (8th ed.). South Melbourne, Victoria: Cengage. [ISBN: 9780170439527]

Graduate Attributes Emphasised
Interdisciplinary perspective, Scholarship, Critical thinking, Ethics, Research.
View more information about Otago's graduate attributes.
Learning Outcomes

Students who successfully complete the paper will:

  • Be able to describe different types of business decisions and their associated characteristics.
  • Understand the process of business decisions, including the articulation of relevant questions, data collection, data analysis and interpretation.
  • Be able to select an appropriate quantitative or qualitative technique to answer a given question, taking into account its strengths and weaknesses and the characteristics of the data.
  • Be familiar with some of the tools used to perform quantitative and qualitative data analysis.
  • Demonstrate awareness of ethical and privacy issues relating to data collection and analysis.
  • Be able to interpret critically the result of data analysis.

Timetable

Semester 1

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

Lecture

Stream Days Times Weeks
Attend one stream from
A1 Monday 10:00-10:50 9-12, 15-22
A2 Monday 11:00-11:50 9-12, 15-22
AND one stream from
B1 Tuesday 10:00-10:50 9-12, 15-22
B2 Tuesday 12:00-12:50 9-12, 15-22
AND one stream from
C1 Thursday 12:00-12:50 9-12, 15-22
C2 Thursday 14:00-14:50 9-12, 15-22

Tutorial

Stream Days Times Weeks
Attend one stream from
A1 Thursday 09:00-09:50 10-12, 15-21
A2 Wednesday 13:00-13:50 10-12, 15-21
A3 Tuesday 16:00-16:50 10-12, 15-21
A4 Tuesday 11:00-11:50 10-12, 15-21
A5 Tuesday 15:00-15:50 10-12, 15-21
A6 Wednesday 11:00-11:50 10-12, 15-21
A7 Tuesday 13:00-13:50 10-12, 15-21
A8 Tuesday 14:00-14:50 10-12, 15-21
A9 Wednesday 12:00-12:50 10-12, 15-21
A10 Wednesday 14:00-14:50 10-12, 15-21
A11 Thursday 15:00-15:50 10-12, 15-21
A12 Thursday 13:00-13:50 10-12, 15-21
A13 Tuesday 17:00-17:50 10-12, 15-21
A14 Thursday 17:00-17:50 10-12, 15-21
A15 Tuesday 09:00-09:50 10-12, 15-21
A16 Wednesday 15:00-15:50 10-12, 15-21
A17 Wednesday 16:00-16:50 10-12, 15-21
A18 Wednesday 17:00-17:50 10-12, 15-21
A19 Thursday 16:00-16:50 10-12, 15-21
A20 Thursday 15:00-15:50 10-12, 15-21

Terms Test (Streamed)

Stream Days Times Weeks
Attend one stream from
A1 Tuesday 19:00-19:50 18
A2 Tuesday 19:00-19:50 18
A3 Tuesday 19:00-19:50 18

Semester 2

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

Lecture

Stream Days Times Weeks
Attend
A1 Tuesday 12:00-12:50 28-34, 37-41
Wednesday 15:00-15:50 28-34, 37-41
Thursday 11:00-11:50 28-34, 37-41

Tutorial

Stream Days Times Weeks
Attend one stream from
A1 Thursday 14:00-14:50 29-34, 37-40
A2 Wednesday 13:00-13:50 29-34, 37-40
A3 Tuesday 15:00-15:50 29-34, 37-40
A4 Thursday 16:00-16:50 29-34, 37-40
A5 Wednesday 12:00-12:50 29-34, 37-40
A6 Wednesday 16:00-16:50 29-34, 37-40
A7 Thursday 09:00-09:50 29-34, 37-40
A8 Thursday 15:00-15:50 29-34, 37-40
A9 Thursday 12:00-12:50 29-34, 37-40
A10 Tuesday 10:00-10:50 29-34, 37-40
A11 Tuesday 16:00-16:50 29-34, 37-40
A12 Wednesday 11:00-11:50 29-34, 37-40
A13 Tuesday 11:00-11:50 29-34, 37-40
A14 Wednesday 10:00-10:50 29-34, 37-40

Terms Test (Streamed)

Stream Days Times Weeks
Attend one stream from
A1 Wednesday 19:00-19:50 33
A2 Wednesday 19:00-19:50 33
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