Recent Question/Assignment

4 MARKING CRITERIA
Students are advised to read the marking rubric provided on Moodle as well as detailed marking
criteria based on this rubric.
5 DEDUCTION, LATE SUBMISSION AND EXTENSION
Late submission penalty: - 5% of the total available marks per calendar day unless an extension is
approved. This means 0.75 marks (out of 15 marks) per day.
For extension application procedure, please refer to Section 3.3 of the Subject Outline. Please do
NOT email the lecturer or tutor to seek an extension, you need to follow the procedure described in
the Subject Outline.
6 PLAGIARISM
Please read Section 3.4 Plagiarism and Referencing, from the Subject Outline. Below is part of the
statement:
-Students plagiarising run the risk of severe penalties ranging from a reduction through to O marks for a first
offence for a single assessment task, to exclusion from KOI in the most serious repeat cases. Exclusion has
serious visa implications.'
-Authorship is also an issue under Plagiarism — KOI expects students to submit their own original work in both
assessment and exams, or the original work of their group in the case of a group project. All students agree to a
statement of authorship when submitting assessments online via Moodle, stating that the work submitted is
their own original work.
The following are examples of academic misconduct and can attract severe penalties:
Handing in work created by someone else (without acknowledgement), whether copied from another
student, written by someone else, or from any published or electronic source, is fraud, and falls under
the general Plagiarism guidelines.
Students who willingly allow another student to copy their work in any assessment may be considered
to assisting in copying/cheating, and similar penalties may be applied. -'
BUS708 2019...
BUS708 Statistics and Data Analysis
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Inferential Statistics Report
Assignment 2 (Assessment 4) — Individual Word Report — Trimester 3, 2019
1 OVERVIEW OF THE ASSIGNMENT
This assignment will test your skill to present and summarise data as well as to make basic statistical
inferences in a business context. You will use the results and any feedback given in Assignment I
(Assessment 3, Excel Report) and produce a single report in a word document. You will need to
construct interval estimates, perform suitable hypothesis tests and regression analysis and make
conclusion and suggestion for management action.
Your report should be written in a word document and should be submitted to Turnitin following the
requirement explained below.
2 TASK DESCRIPTION
There are two datasets involved in this assignment: Dataset I and Dataset 2, which are the same
datasets used in Assignment I (Excel Report). All data processing should be performed in Excel or
Statkey (http://www.Iock5stat.com/StatKev). Specific instruction as to which tools should be used
for each section will be given during tutorials.
Your tasks are to answer the following research questions given in Section 2 to Section 6 below using
dataset I or dataset 2 as indicated in each section. To answer each question, you will need to first
present the relevant numerical summary (summary statistics) and graphical display and perform
suitable statistical analysis to provide a statistical conclusion.
I.
2.
3.
Section I: Introduction
Provide a brief and clear introduction about the report (e.g. the objective of the
report, the datasets involved, etc.). Find relevant articles (minimum one article,
maximum 3 articles) and write a proper literature review which includes in-text
citation.
Section 2: Is 40% a plausible value for the proportion of private room in Airbnb room type?
Using Dataset I, first provide both numerical summary as well as graphical display
that easily shows the proportions of different room types. Then construct a 95%
confidence interval of the population proportion of private rooms. Finally, answer the
research question using the confidence interval.
Section 3: After an iteration of outlier removal, is the price of private room more than
$70?
Using Dataset I, perform one iteration of outlier detection on the price of priv
room using the method described in the lecture notes. After removing those
outliers, describe the price distribution of private room using both numerica
graphical summary which shows the remaining outliers, if any.
Perform suitable hypothesis test to answer the research question above at 5% I
of significance.

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