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Types and Sources of business Data, Scales, Unorganised, Raw - Coggle…
Types and Sources of business Data
Data
Singular
Like 'Information'
Informal
Plural
Academic writing
Formal
Meaningful
Information
To learn about
Facts
To analyse
Processed
Evaluating Data
PROMPT
Relevance
Meets the need
Purpose
In context
Timeliness
Relevant or Obsolete?
Ethical
Presentation
Readability
Clear
easy to navigate
Provenance
Reliable
Credibilty
Purpose of the source
Method
Clear
Consistent
Systematic
Objectivity
Unbiased
Free from external influence
Trustworthy
Qualitative Data
Descriptive
Behaviours
Attitudes
Opinions
Perceptions
Non Numerical Values
Provides an in depth Analysis and information related to a specific research problem
Who
What
Why
Where
Interviews
Knowledgeable
Structured
Clear
Gentle
Sensitive
Open
Steering
Critical
Able to remember
Able to interpret
Balanced
Ethically sensitive
Focus Groups
Observations
Nominal Data
Obtained by named variables
Ordinal Data
Describes an order of value
Subjective
Open Ended
Detailed
Quantitive Data
Data that can be counted or measured
Primary sources
original / raw data
Survey data
Secondary sources
Other research
Articles
Books
Publicly available statistics
Numbers
Statistics
Discrete data
Counted
Example: employees, shoes, equipment
Fixed Value
Whole numbers
Static
Unlikely to change over time
Pie or bar chart
Continuous data
Can change over time
Can be broken into parts
Fractions
Line Graph
Measured
Example: temperature, Profit, height
Scales
Ratio Scale
Similar to Interval scale
Can be ranked, counted, added and subtracted
Cannot be negative
True zero point
Ceases to exist
Example: You have zero apples
Ratio of measurement will be meaningful
A car weighing 2000kg is twice as heavy as a car that weighs 1000kg
Provides more information about order and difference
Plus a breakdown of the numerical detail within each data point
Interval scale
Links Nominal and Ordinal
The difference between data points can be quantified
An example is Celsius and Fahrenheit
Quantitative
Discrete or continuous
Can be added or subtracted (not not divided or multiplied)
40°C is not twice as hot as 20°C
Used to understand order and difference between them
Nominal Scale
Categorises data into groups
Gender
Eye colour
City of birth
Non numerical
Are used to label or describe values
Ordinal Scale
Ranking and ordering of data
Satisfaction scale 1 (highest) - 5 (lowest)
To provide information about specific order of the data point
Unorganised
Raw