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日期：2023-05-17 08:31

ECON10005 Quantitative Methods 1 Assignment Final Submission

Assignment: Final Submission

Assignment Guide

You are submitting this assignment as a part of the data analysis report. This is the final

draft version. This draft assignment should reflect your enhanced ability in data analysis

as we progress in QM1. You are encouraged to keep working within the same group of

no more than three people as for the first draft. You may choose to keep working

individually.

Please consider your marker’s comments on the first draft seriously and critically. Re-

vision based on peer reviews is important for improving your analytic and writing skills.

Incorporating these comments in the final draft is one key factor for its final marks.

Submission

The assignment is due at 2 pm on 18 May. More instructions are delineated on Canvas

along with this file.

The final draft contributes 7% to your final marks.

We use Turnitin, an originality and plagiarism checking tool, to check the similarity

in students’ work. Please ensure you or your group independently write the assign-

ment from the other students and groups and submit your own work. Zero-mark

penalty applies to those who plagiarise.

No extension is allowed. Any assignments not submitted by the due date and time

will incur 10% penalty for each full hour late until the zero mark. Namely, if you

submit your assignment 10 hours later than the deadline, your assignment will not

be marked.

Assignments must be typed and converted into a single PDF document before sub-

mitting online via Canvas. Scanned or handwritten assignments will not be marked.

Figures or tables in a separate Excel file are not accepted.

Please make sure to include a cover page in the assignment. Your Name(s), Group

ID, student ID(s) and your tutor’s name must be included on the cover page.

If working with a group, you must stay in the same group as in the first draft.

Students must preview their assignment after uploading it on Canvas to see if they

have uploaded the correct/complete file and if the formatting matches their origi-

nal document. Any version of the assignment submitted after the deadline due to

formatting issues or submitting an incomplete version will not be accepted.

This draft has a 1000 word limit.

The detailed tasks are on the next page.

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ECON10005 Quantitative Methods 1 Assignment Final Submission

Background

In your initial draft, you described the data of a real estate market in a small city in the

United States to a prospective client. However, for the final submission, you will be using

the same data to showcase your analytical abilities through statistical inference. You should

apply quantitative techniques to substantiate your assertions, and it is essential to include

statistical inferences.

Final Submission Tasks

There is no unique way to write a business report. Similar to the first draft, we provide

some scaffolded tasks for your reference and serve as starting points or simple brainstorm

sparks. You are expected to apply hypothesis testing and/or regression analysis in the final

submission.

However, because of the focus heterogeneity, you are NOT required to chase these

tasks rigidly. These tasks are listed in items instead of enumeration because they are not

necessarily in order.

Your business report should appear as one piece of the story. Namely, you should not

discard the first draft and only show work related to the additive tasks in the final

draft.

– To conform to the word limit, you may condense your initial draft and focus

on the important variables, including the price variable. Additional tables and

figures could go to the appendix.

– Make sure to label your tables and figures properly. For example, write “Figure

1”, do not write “Graph 1” or “Picture 1”. Tables and Figures are labelled

separately.

– It is recommended to have a structure such as Introduction, Data Description,

Data Analysis, and Conclusion. In the middle of the report, you may also have

some sections with a particular name such as “bedroom” if you think the variable

“bedroom” is important and worth more detailed analysis.

Be aware of OpenAI. It is notoriously bad for data analysis and many tasks that

require analytic skills. We have seen beautifully written paragraphs with terrible

statistical logic.

Use the skill of testing one mean. Here are some examples of hypothesis testing, but

it’s important to note that you should provide the context in the data analysis by

justifying why you are conducting these particular tests.

– Is the 3-bedroom houses the major type of the market? This seems a proportion

problem, right? Hint: If a house has 3 bedrooms, then it can be labelled with

value 1 and 0 otherwise.

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ECON10005 Quantitative Methods 1 Assignment Final Submission

– Is the mean house price higher than $200k? There is no reason that you must

use the value of $200k. There is also no reason to use “higher”. One may try

“lower” or “different”. If you have better things to do, there is even no need to

do this test.

– Is the mean price of a house with 3 bedrooms higher than $200k? This seems

like a realistic question from a potential client. Your sample is not the whole

data set now but a subset with 3 bedrooms.

Use the skill of comparing two means.

– If a client wants a “big” house for his family, he expects to pay a premium of

$50k, for example. Is the feature “big” worth $50k or more? Such a question can

be interpreted in multiple ways. For instance, does “big” mean large lot area or

large living area? You may choose one or try both. If one considers the lot area

larger than 10,000 as “big” and the others as “small”, you have split the data into

two subsamples. Comparing their means is a way to tell whether such difference

is larger than $50k statistically.

– How important is the garage? You may split the data into “have garage” and “no

garage” and compare the means of the prices. Always avoid causality statements

without further theory, assumption or model structure.

? Apply simple linear regression. You may find many applications once you use the

regression toolkit.

– How much additional value is an additional bedroom? You may consider a model

Pricei = β0 + β1Bedroomi + ei

– How much additional value is there for more land? You may consider a model

Pricei = β0 + β1LotAreai + ei

– How much additional value is there for a bigger house? You may consider a

model

Pricei = β0 + β1LivAreai + ei

– Or even investigate the building style. For example, do the recent houses have

more bedrooms? You may consider a regression

Bedroomi = β0 + β1Y earBuilti + ei

or practically

Bedroomi = β0 + β1Y earremodAddi + ei

? This guide is mostly technique driven as predicted by QM1 material. However, your

report will be highly appreciated (by the hypothesised client) if it is written in a

problem-driven approach. A client may have some questions and opinions on the

report, including the format. For example, from the first-person perspective,

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ECON10005 Quantitative Methods 1 Assignment Final Submission

– What is the average price and range in this market?

– I have a family. What is the price range for my ideal house?

– When is the best time to buy? When is the “gold” month to enter the market?

Should I wait for next month in order to buy at a lower price?

– I have a budget of $250K,. What can I afford?

– What premium must I pay if I want a recently built house?

To effectively analyse the data, you could begin with a broad overview before delving

into a more detailed analysis of a subset of the data. This should include statistical

inferences and regression analysis to support your conclusions.

One helpful approach is that one of your group members acts as a client to raise

questions. You may find there are more problems than you think. Pick the interesting

ones, answer them and write your report.

Rubrics are on the next page.

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ECON10005 Quantitative Methods 1 Assignment Final Submission

Rubrics

Similar to the first draft, the final draft will also be evaluated aggregately by incorporating

the following four criteria: accuracy, logic, format and discovery. Because reports are

highly heterogeneous, detailed mark split is impractical. You will receive an overall mark

and written feedback on your work.

More detailed guidance is listed below.

1. Accuracy.

Use the correct columns of data to be consistent with your choice in the report.

Use the correct Excel formula. This is hardly testable but will be reflected in

your numeric results. We may request your Excel file for verification.

Use the correct names for descriptive statistics and figures.

Use the correct variable names in your report.

Understand tests and simple linear regression and use precise terminology.

2. Logic.

Sentences and paragraphs must be coherent and cohesive.

Any statement should have data evidence or build on consensus or experience.

Demonstrate that you understand the concepts learned from the subject.

Interpret the testing and regression results correctly.

3. Format

Clear title and section names.

Each paragraph has one clear message. Avoid overlong sentences.

Label figures and tables correctly. For example, you may use Table 1 and Table 2

for tables as in this file. Analogously, use Figure 1, Figure 2 and so on to label

figures.

Label a figure’s X- and Y-axis properly.

Write titles for tables and figures.

Avoid screenshots. Excel figures can be saved properly.

Show page numbers.

Not many grammar mistakes and typos. We expect you to improve in the final

draft with fewer mistakes and typos than in the first draft.

4. Discovery

Show your curiosity by discovering insightful facts from the data.

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ECON10005 Quantitative Methods 1 Assignment Final Submission

Try to link the application to some real-world problem.

Think about the business world and consider what a client desires and if you

may provide such a solution.

Avoid following the guide mechanically. It is a way to inspire, not restrict, your

thoughts.