E3 - Using and Manipulating data

Question 1

What are the two data sources?

Answer 1

primary and secondary

Question 2

What is a primary data source?

Answer 2

Original research, from the source, no third party (EG: interviews, questionnaires, sensors, measurements)

Question 3

What are the advantages of a primary data source?

Answer 3

• Up to date and valid
• relevant: direct data gathering to find 1 precise data
• reliable

Question 4

What is a secondary data source?

Answer 4

3rd party gathered data (EG: census data, textbooks, web info, official statistics

Question 5

What are the advantages of a secondary data source?

Answer 5

• cheaper
• quicker
• isn’t subject to organisation’s bias

Question 6

What is the criteria for a reliable data source?

Answer 6

Completeness - all data for investigation is included
Accuracy - consistent and can be repeated with the same results, data gathered matches the true value/source
Methods for a good survey - avoid using jargon (professional words), avoid language bias (leading questions), used closed answer questions (easy to analyse)

Question 7

What are the 3 main data collection methods?

Answer 7

• Questionnaire
• Focus Groups
• Interview

Question 8

What is a focus group?

Answer 8

group asked questions on a topic (product, service, ad…)

Question 9

What are the positives and negatives of Focus Groups?

Answer 9

+ can build on eachothers answers = detailed answers
+ wider group than interview meaning it’s cost effective
+ can alter questions to fit ongoing conversations for more detail

• respondents can influence eachother’s answers
• qualitative data produce, hard to analyse
• organising a group for same time = difficult

Question 10

What is a Questionnaire?

Answer 10

It consists of closed format questions for statistical / personal info from respondents

Question 11

What are the positives and negatives of Questionnaires?

Answer 11

+ good for data from large groups in short time ( more data = more reliable)
+ everyone answers same questions = not bias & more consistent
+ can be done anonymously meaning more honey answers

• poorly worded questions = bias results
• no in-depth answers as questions are closed & follw-up questions can’t be asked
• poor response rates ( busy users )

Question 12

What is an Interview?

Answer 12

It is a 1 on 1 conversation with another person & can ask follow up questions

Question 13

What are the positives and negatives of Interviews?

Answer 13

+ good for detailed responses, provide more clarity & ensures questions are fully understood
+ more honesty as there is good personal contact

• more time consuming for data from more people
• qualitative data meaning its harder to analyse

Question 14

Ensuring Data Accuracy

Answer 14

Reasons for Ensuring Data Accuracy:
- PCs have no common sense
( GIGO, run out of stock )

Methods for Ensuring Data Accuracy
Validation
-> ensures data is sensible, but no accurate
Date of Birth - dd/mm/yyyy, ensure data is in the past

Verification
-> ensure data entered matches original source of data
-> proofreading, double entry checking

Question 15

Extracting & Sorting Data

Answer 15

• Queries, allow us to retrieve the data we want

2 key abilities of queries:
> Extracting - select precise fields of data (first name)
> Sorting - ascending/descening order

• Makes it easier to use data gathered

Question 16

Numerical & Data Modelling

Answer 16

Numerical Modelling
- math calculations to analyse data & make future predictions ( weather, stock levels etc )

Data Modelling
- process to plan the structure of a database to ensure its stored in the most organised & efficient way

-> table with fields, each field has certaind ata type & properties ( next length )
-> = efficient storing, processing & extracting of data

Question 17

Presenting Data & Results

Answer 17

Tabular :
- text presentation of data in a table meaning precise & detailed info for qualitative data

Graphical :
- data presented as chart/diagram = quickly interpret data (spotting trends)

Question 18

Different Implications of User Interfaces for Data Collection ( 7 )

Answer 18

• Ease Of Use
• Accessibility
• Error Reduction
• Intuitiveness
• Functionality
• Performance
• Compatibility

Question 19

Implications of User Interfaces for Data Collection (Ease Of Use)

Answer 19

• Easy interface = good labelling (input boxes), different input options for different types of data to simplify input (data pick, drop-down)

Question 20

Implications of User Interfaces for Data Collection (Accessibility)

Answer 20

• clear & simple interface
• navigation can be performed with different inputs (mouse..)
• more contrast scheme so key elements can be identified
• don’t just use colours for visual uses
• support changing size of icons, text

Question 21

Implications of User Interfaces for Data Collection (Error Reduction)

Answer 21

• poor labelling = confusion
• add validation, verification, input masks to indicate format data should be entered in ( postcode - LLN NLL)
• CLEAR warning messages

Question 22

Implications of User Interfaces for Data Collection (Intuitiveness)

Answer 22

• use without training
• good labelling, clear navigation
• online should match paper forms that data is transferred from meaning its easier for inputter

Question 23

Implications of User Interfaces for Data Collection (Functionality)

Answer 23

• performing certain queries & producing report
• results displayed in useful way
• if its difficult for user to perform functionality = less productivity

Question 24

Implications of User Interfaces for Data Collection (Performance)

Answer 24

• data collection and processing is faster
• less steps to do tasks = less confusion and less errors

Question 25

Implications of User Interfaces for Data Collection (**Compatibility**)

Answer 25

- compatible with other systems which means easily imported - spreadsheet to data .;. export/import as a CSV file (generic)