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Data Collection & Analysis Guide

This document provides answers to a tutorial sheet on data collection and tables. It includes examples of different data types, potential variables to collect from restaurants, methods for random sampling, and examples of tables with percentages of ice cream preferences by county. The key points are: 1) It defines different data types like nominal, discrete, ordinal, and continuous and provides examples. 2) It discusses random sampling methods like simple random sampling and stratified random sampling, noting their advantages and limitations. 3) It evaluates examples of tables showing percentages of last takeaway purchases and ice cream preferences by county, noting useful insights and inaccuracies.

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29 views2 pages

Data Collection & Analysis Guide

This document provides answers to a tutorial sheet on data collection and tables. It includes examples of different data types, potential variables to collect from restaurants, methods for random sampling, and examples of tables with percentages of ice cream preferences by county. The key points are: 1) It defines different data types like nominal, discrete, ordinal, and continuous and provides examples. 2) It discusses random sampling methods like simple random sampling and stratified random sampling, noting their advantages and limitations. 3) It evaluates examples of tables showing percentages of last takeaway purchases and ice cream preferences by county, noting useful insights and inaccuracies.

Uploaded by

Lex
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as DOCX, PDF, TXT or read online on Scribd
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120MP Tutorial Sheet Answers Week 5

DATA COLLECTION

1) a) Nominal
b) Discrete
c) Ordinal,
d) Continuous
e) Continuous
f) Ordinal

2) a) Restaurant name
b) Hygiene Rating
c) Number of employees
d) Annual turnover

or similar

3) a) Obtain a numbered membership list. Use a random number generator to select


100 people from the list. Random, so likely to be representative. They will be all over
the country so due to cost it would probably use telephone/letter/email. Not face to
face so response rate and quality of data may not be as high

b) Use the membership list again. Randomly generate a number between 1 and 80
as the starting point, then select every 80th member in the list after that. Not really
any advantage over simple random sampling here (unless the list is ordered
alphabetically say, and you thought that you think you need a spread of different
lettered surnames to truly represent the student population)

c) Aim is to save cost. No obvious saving if survey is by mail or phone. If face to


face interviews then randomly select a postcode and choose 100 members in that or
adjacent post code. This may not be truly representative of the whole country.

d) Select a random sample of 75 males from the 6000, and a random sample of 25
females from the 2000. This would reflect the gender split in the population. Useful if
you think that the genders may give different answers from each other.

PTO
TABLES

1) Car Owner
No Yes
Burger King 22% 78% 100%
Last KFC 40% 60% 100%
Purchased McDonalds 39% 61% 100%
Pizza Hut 30% 70% 100%
Other 40% 60% 100%
37% 64% 100%

Car Owner
No Yes
Burger
8% 17% 14%
King
Last KFC 16% 13% 14%
Purchased
McDonalds 61% 56% 58%
Pizza Hut 2% 3% 3%
Other 13% 11% 12%
100% 100% 100%

Not accurate because data was only from students, not all users
Not useful because most had a car, wherever they ate. (64% owned a car overall)

Better eg’ ‘McDonalds was the restaurant visited most, with 58% of the students surveyed
having purchased their last takeaway there.’ ‘The restaurant with the highest car ownership
amongst student was Burger King, with 78% of student customers owning a car’.

2)
Favourite Ice cream
Vanilla Strawberry Chocolate Other None
Warwickshire 14% 22% 29% 19% 16% 100%
Leicestershire 16% 15% 31% 9% 29% 100%
County
Worcestershire 22% 27% 12% 22% 18% 100%
Northamptonshire 27% 11% 34% 9% 18% 100%
21% 18% 27% 14% 21% 100%

Favourite Ice cream


Vanilla Strawberry Chocolate Other None
Warwickshire 13% 22% 19% 25% 14% 18%
Leicestershire 19% 21% 29% 17% 36% 25%
County
Worcestershire 26% 37% 11% 38% 22% 24%
Northamptonshire 42% 21% 41% 21% 28% 32%
100% 100% 100% 100% 100% 100%
Chocolate was the most popular flavour overall with 27% of respondents saying it was their
favourite.
However in Worcestershire it was the least favourite of the 3 choices with only 12% selecting it.
29% of those surveyed in Leicestershire inferred that they didn’t like ice cream!

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