Chapter 8

Question 1

What is the difference between Data and Information?

Answer 1

Data is raw facts, numbers or transitions that are not yet processed.

Information is data which has been processed in such a way that it is meaningful.

NB: The ‘process’ could be a simple sorting or summarising process.

Question 2

What are the characteristics on good information

Answer 2

ACCURATE

Accurate
Complete
Cost effective
Understanable
Relevant
Authoritative
Timely
Easy to use

Question 3

Characteristic: Accurate

Answer 3

Information should be precise enough to allow the appropriate decision to be made

Question 4

Characteristic: Complete

Answer 4

Information should contain all relevant facts

Question 5

Characteristic: Cost effective

Answer 5

It must be more valuable than the cost of producing it

Question 6

Charactiersic: Understandble

Answer 6

Information should be clearly presented so that it is easily and quickly understood

Question 7

Characteristic: Relevant

Answer 7

The information ust be pertinent to the user and within the control of the responsible party

Question 8

Characteristic: Authoritative

Answer 8

The information must be based on trustworthy sources

Question 9

Characteristic: Timely

Answer 9

The information should be available within any relevant time periods

Question 10

Characteristic: Easy to use

Answer 10

The information should be accessible

Question 11

What is Quantitative data?

Answer 11

Data that can be measured (e.g. age,

Question 12

What is Qualitative data?

Answer 12

Data that cannot be measured (how blue are your eyes

Question 13

What is Discrete data

Answer 13

values/observations are distinct and separate - they can be counted
the number of blah in blah etc

Question 14

What is continuous data

Answer 14

values/observations may take on any value within a finite or infinite interval.
You can count, order and measure continuous data,
height, weight, temperature, time

Question 15

What is Primary data

Answer 15

Data that has been gathered for a specific purpose by the user

This could be via interviews, questionaires etc

Question 16

What is Secondary data

Answer 16

Data gathered by someone else for another purpose but that you are using for your purpose

e.g. financial statements ror statistics

Question 17

What are the different sampling techniques?

Answer 17

1) Random
2) Stratified random
3) Systematic
4) Cluster
5) Multistage
6) Quota

Question 18

Sampling technique: Random

Answer 18

-Items are picked at random from the sampling frame until the sample is complete

Question 19

Sampling technique: Stratified Random

Answer 19

In a stratified sample, the sampling frame is divided into non-overlapping groups or strata . A random sample is then taken from each stratum
-eg, geography, age group, gender

Question 20

Sampling technique: Systematic

Answer 20

Every nth item in the sampling frame is taken for the sample

Question 21

Sampling technique: Cluster

Answer 21

Cluster sampling divides the population into groups, or clusters. A number of clusterse are selected randomly to respresent the population and then all unites within selected clusters are included in the sample

Question 22

Sampling technique: Quota

Answer 22

sample of ‘x’ items is taken
There may be bias in the sample
e.g. a street interviewer

Question 23

Sampling technique: Multistage

Answer 23

Multi-stage sampling is like cluster sampling, but involves selecting a sample within each chosen cluster, rather than including all units in the cluster. Thus, multi-stage sampling involves selecting a sample in at least two stages. In the first stage, large groups or clusters are selected. These clusters are designed to contain more population units than are required for the final sample.

-In the second stage, population units are chosen from selected clusters to derive a final sample. If more than two stages are used, the process of choosing population units within clusters
continues until the final sample is achieved.

Question 24

what is sampling?

Answer 24

When data is gathered from a sampling frame (numbered list of all items in the population

Question 25

What is grouped frequency distribution? exmaple

Answer 25

A table of data with various ranges identified and a frequency column indicating the number of items in each range

akak data = ages of 20 students
Age (range) | Number of students (Frequency)
19-21
Ungrouped frequency distribution =
Age| Frequency

Question 26

What are the different types of bar charts?

Answer 26

Simple bar chart
Multiple bar chart
component bar chart
percentage compnent bar chart

Question 27

What do bar charts show?

Answer 27

Data is shown by bars of equal width, the height of which corresponds to the value of the data

Question 28

What is a histogram?

Answer 28

A histogram is a frequenct distribution where the frequency of occurrence is represented by the area of the bars not the height of the bars.

In CIMA, intervals will be of equal width, allowing you to calculate the height of the bar using the formula
Heigh = frequency of the interval

Question 29

Histogram with unequal widths - what to do

Answer 29

You may see a histogram where the bars are unequal widths. This reflects the fact that the frequency is demonstrated by area, not height. Height of bar = Frequency × Standard class width/Actual class width
For example, if the width of the block is one and a half times the standard width, we must divide the
frequency by 1.5, i.e. multiply by 0.67 (1/1.5).

Question 30

What is an Ogive?

Answer 30

An ogive is a cumulative frequency curve which shows the total number of items less than a certain value

We can now use the ogive to estimate the number of people receiving below a certain amount

Question 31

What are the three characteristics of big data

Answer 31

Using 3V’s: Volume, Velocity, Variety

V: Volume: More data than ever before is being collected,
-This is driven by social media, transactional-based data recorded by large organisations and internal systems

V: Velocity: refers to the speed at which data is being streamed into the organisation, in real time.
-Transactions may be constant, particularly for multi-national organisations and those with a significant ecommerce presence

V: Variety: Big data includes data from many different systems which will be in many different formats.
Structure data - transaction files, unstructured data - include social media posts, emails etc
Making sense of these many different sources and formats may require significant investment

Question 32

What are the three characteristics of big data

Answer 32

Using 3V’s: Volume, Velocity, Variety

V: Volume: More data than ever before is being collected,
-This is driven by social media, transactional-based data recorded by large organisations and internal systems

V: Velocity: refers to the speed at which data is being streamed into the organisation, in real time.
-Transactions may be constant, particularly for multi-national organisations and those with a significant ecommerce presence

V: Variety: Big data includes data from many different systems which will be in many different formats.
Structure data - transaction files, unstructured data - include social media posts, emails etc
Making sense of these many different sources and formats may require significant investment

Question 33

How is big data used?

Answer 33

-Companies who identified the potential of big data ahead of competitiors have obtained competitive advantage.

-Big data can be used to identify and/or analyse opportunities to increase revenues and improve product offerings, or reducing costs through process efficiencies

-Organisations can build a more complete picture of their customer gained from multiple sources

-Big data can be used to identify/analyse opportunities to save costs (inc, improving logistics, reducing the cost of fraud)

-Big data is big and complex, systems need to ensure information is able to be made available and acted upon quickly.

Question 34

What is big data?

Answer 34

Big data involves capturing and processing data on a vast scale and converting it into information that is able to be utilised by the organisation.
Analysis of big data can uncover unexpected relationships and provide new insights into business performance,

Question 35

What does big data include?

Answer 35

-Big data includes data collected from many previously seperate systemes. The data includes both structured data and unstructured data.

Unstructured data may be tagged using metadata

Question 36

What is meta data?

Answer 36

Metadata is data that describes other data, aka what time a photo was taken etc.

Question 37

What is meta data?

Answer 37

Metadata is data that describes other data, aka what time a photo was taken etc.