# QUANTITATIVE METHODS – UNIT 1 – STATISTICS ASSIGNMENT BRIEF

QUANTITATIVE METHODS – UNIT 1 – STATISTICS ASSIGNMENT BRIEF

Unit

QUANTITATIVE
METHODS Unit 1

Assignment Title

Quantitative
Methods Unit 1 – Statistics Project

Submission Date

Week
commencing Monday 6th January 2014

Word Count

n/a

Assignment Requirements

Compare property prices in two areas of

Collect your own data (min 50 prices from each area). You should quote your data collection source
and data collection methodology in your final report.
State a hypothesis ( e.g. “My hypothesis is that property is
more expensive in than in .”).
Analyse your data by performing statistical calculations and
using diagrams and charts.
Include written comments to explain and interpret your
results/diagrams.
You may use computer software if you wish.

Written

Written comments are in relation to interpreting
the data, calculations and diagrams. These should be on-going throughout the
assignment to describe to the reader the meaning of the various calculations
and diagrams.
This is
VERY IMPORTANT!

on appropriate use of measurements
Compare:
v
Measures of average – mean,
median, mode. Which of these give a useful measure of average for your data?
Why?
v
Measures of spread – range, inter
– quartile range, standard deviation. Which of these are useful measures of the

Discussion
and observations
Comment on:
v
Types of property in each area.
Are types similar for each area?
v
Prices. Are there any particularly
high or low values?
v

Comparisons
v
Compare average house prices
(mean, median and mode) for each area. What do the averages suggest to you?
v
interquartile range, standard deviation) of house prices in each area. What do
these measurements suggest to you?
v
You could include a table e.g.

Watland

Trecklington

Mean

£50 000

£67 500

Median

£45 000

£66 240

Mode

£35 000

£51 000

Comment
whether hypothesis supported/not
State clearly e.g.
‘The
hypothesis is supported’or ‘The hypothesis is not supported’

How
supported/not and Conclusion drawn
v
supported, giving evidence and examples.
v Make sure

Comment on any possible improvements. e.g.
v
Taking a
larger sample from each area
v
Collecting
data from a wider range of sources e.g. estate agents, newspapers, property
magazines, internet
v
Collecting
data over a longer period of time
v
Comparing
more similar types of property from each area
ritten comments are in relation to interpreting the
data, calculations and diagrams. These should be on-going throughout the
assignment to describe to the reader the meaning of the various calculations
and diagrams.
This is
VERY IMPORTANT!

on appropriate use of measurements
Compare:
v
Measures of average – mean,
median, mode. Which of these give a useful measure of average for your data?
Why?
v
Measures of spread – range, inter
– quartile range, standard deviation. Which of these are useful measures of the

Discussion
and observations
Comment on:
v
Types of property in each area.
Are types similar for each area?
v
Prices. Are there any
particularly high or low values?
v

Comparisons
v
Compare average house prices
(mean, median and mode) for each area. What do the averages suggest to you?
v
interquartile range, standard deviation) of house prices in each area. What do
these measurements suggest to you?
v
You could include a table e.g.

Watland

Trecklington

Mean

£50 000

£67 500

Median

£45 000

£66 240

Mode

£35 000

£51 000

Comment
whether hypothesis supported/not
State clearly e.g.
‘The
hypothesis is supported’or ‘The hypothesis is not supported’

How
supported/not and Conclusion drawn
v
supported, giving evidence and examples.
v Make sure

Comment on any possible improvements. e.g.
v
Taking a
larger sample from each area
v
Collecting
data from a wider range of sources e.g. estate agents, newspapers, property
magazines, internet
v
Collecting
data over a longer period of time
v
Comparing
more similar types of property from each area

QUANTITATIVE
METHODS
UNIT 1 STATISTICS PROJECT

CHECKLIST

Assessment Criteria

INTRODUCTION

Hypothesis

4.1

Method
of data collection

4.1/5.2

Description
of two study areas

5.2

on use of measures/tables/graphs

5.1/5.2/7.1

PRESENTATION OF DATA

Tally chart

4.2/5.1/7.1/7.2

Frequency table

4.2/5.1/6.1/6.2/7.1/7.2

Bar chart

4.2/5.1/7.1/7.2

Pie chart (show sector angle calculations)

4.2/5.1/6.1/7.1/7.2

Histogram

4.2/5.1/7.1/7.2

Cumulative frequency graph

4.2/5.1/6.2/7.1/7.2

ANALYSIS OF DATA

Measures of Average

Est. Mean calculated from frequency table

4.3/6.1/7.2

Est Median or Modal/Median Class from frequency table

4.3/6.1/7.2

Est
Median from cumulative frequency graph

4.3/6.2/7.2

Actual
Mean, Median (and Modes) from raw data

4.3

Measures
of Dispersion

Range
from raw data

4.3/6.1/7.2

Est.
Standard deviation calculated from frequency table

4.3/6.1/7.2

IQR
estimated from cumulative frequency graph

4.3/6.1/7.2

INTERPRETATION OF DATA & CONCLUSION

Sheet of Results (show results side by side)

6.2/7.2

Hypothesis
supported/not supported

7.3

Improvements
suggested

5.2

Conclusion
drawn

7.2/7.3

Order your essay today and save 30% with the discount code: KIWI20