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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 ) $993.75
    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

    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
    Blackboard

    Computer Lab

    Stream Days Times Weeks
    Attend one stream from
    A1 Tuesday 11:00-11:50 10-16, 18
    A2 Tuesday 11:00-11:50 10-16, 18
    A3 Friday 10:00-10:50 10-16, 18
    A4 Friday 10:00-10:50 10-15, 18
    A5 Thursday 09:00-09:50 10-16, 18
    A6 Thursday 09:00-09:50 10-16, 18
    A7 Monday 14:00-14:50 10-16, 18
    A8 Monday 14:00-14:50 10-16, 18
    A9 Wednesday 16:00-16:50 10-16, 18
    A10 Wednesday 16:00-16:50 10-16, 18
    A11 Friday 13:00-13:50 10-16, 18
    A12 Friday 13:00-13:50 10-15, 18
    A13 Friday 11:00-11:50 10-16, 18
    A14 Friday 11:00-11:50 10-15, 18
    A15 Tuesday 16:00-16:50 10-16, 18
    A16 Tuesday 16:00-16:50 10-16, 18
    A17 Wednesday 15:00-15:50 10-16, 18
    A18 Wednesday 15:00-15:50 10-16, 18
    A19 Thursday 10:00-10:50 10-16, 18
    A20 Thursday 10:00-10:50 10-16, 18

    Lecture

    Stream Days Times Weeks
    Attend one stream from
    A1 Monday 13:00-13:50 9-16, 18-22
    A2 Monday 11:00-11:50 9-16, 18-22
    AND one stream from
    B1 Tuesday 12:00-12:50 9-16, 18-22
    B2 Tuesday 10:00-10:50 9-16, 18-22
    AND one stream from
    C1 Thursday 14:00-14:50 9-16, 18-22
    C2 Thursday 15:00-15:50 9-16, 18-22

    Semester 2

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

    Computer Lab

    Stream Days Times Weeks
    Attend one stream from
    A1 Friday 09:00-09:50 30-35, 37-38
    A2 Friday 09:00-09:50 30-35, 37-38
    A3 Monday 15:00-15:50 30-35, 37-38
    A4 Monday 15:00-15:50 30-35, 37-38
    A5 Tuesday 09:00-09:50 30-35, 37-38
    A6 Tuesday 09:00-09:50 30-35, 37-38
    A7 Monday 14:00-14:50 30-35, 37-38
    A8 Monday 14:00-14:50 30-35, 37-38
    A9 Thursday 10:00-10:50 30-35, 37-38
    A10 Thursday 10:00-10:50 30-35, 37-38
    A11 Monday 13:00-13:50 30-35, 37-38
    A12 Monday 13:00-13:50 30-35, 37-38

    Lecture

    Stream Days Times Weeks
    Attend
    A1 Tuesday 11:00-11:50 29-35, 37-42
    Wednesday 15:00-15:50 29-35, 37-42
    Thursday 15:00-15:50 29-35, 37-42
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