Statistics for Management Project

This project examines the use of statistics in business management, analyzing consumer price index (CPI) and retail price index (RPI) data, evaluating different statistical analysis techniques, and demonstrating their application in business planning, inventory management, and capacity management. The project also includes graphical representations of data and a conclusion summarizing the findings.

STATISTICS
FOR
MANAGEMENT

Table of Contents
INTRODUCTION...........................................................................................................................3
ACTIVITY 1....................................................................................................................................3
P1 The nature and process of business and economic data and information from a range of
different published sources.........................................................................................................3
P2 Evaluate data from a variety of sources after analysing from different methods..................5
M1 Sources of national statistics with regard to the gender pay gap..........................................8
D1 Difference between descriptive, exploratory and confirmatory analysis..............................8
ACTIVITY 2....................................................................................................................................8
P3 Analysis of qualitative and quantitative raw business data using appropriate statistical
methods.......................................................................................................................................8
M2 Assessment of different statistical application...................................................................12
ACTIVITY 3..................................................................................................................................12
P4 Statistical methods used in business planning, inventory management and capacity
management ............................................................................................................................12
M3 Justification and use of Statistical techniques....................................................................13
D2 Explanation and recommend judgement for activity..........................................................14
ACTIVITY 4..................................................................................................................................14
P5 Use of adequate tables and charts to execute the findings for several variables.................14
...................................................................................................................................................16
M4 Graphical representations assessed in activity one and second..........................................18
D3 Use of graphical and table representation in activity one and two......................................18
CONCLUSION..............................................................................................................................18
REFERENCES..............................................................................................................................20

INTRODUCTION
Statistical Analysis is a element of collection of data, investigation, summarisation,
handling and representation of quantitative data to observe its integral reason, relationships,
partners and trends. It is using in management to manage various tools and methods that are
important for operations (Ajiboye, 2014). Statistical analysing helping to management and
individual in representing the data and information in graphical manner. The report consist of
different types activities and these activities are related to consumer price index and retail price
index. Evaluate of business and economic data that are related to published sources. For
statistical methods using raw material data and these methods are applying on business planning.
For showing these information using appropriate charts and tables.
ACTIVITY 1
P1 The nature and process of business and economic data and information from a range of
different published sources
a) Price Indices from the office of National Statistics
Consumer price indices
A CPI is a measures of retail price level of market goods and services used by particular
population group such as food, transportation and medical care. CPI is broadly used as a
macroeconomic indicator for inflation or deflation, as a tool by governments and central banks
for inflation targeting and for monitoring price stability and as deflators in the national accounts.
It is statistical predication conception using for prices of a sample that are representative items
whose prices are clustered period of time. The consumer price index number measures changes
only in one of the factors, prices. Price. This price index is a important economic indicator that
are used for calculate inflation barometer (Caulcutt, 2014). The CPI generally calculated
periodically such as monthly or quarterly. It is used for measure effect of inflation on salaries,
pensions and value of wages. The Consumer prices index including owner occupier's housing
costs (CPIH) become new measuring tool that are helping to measure inflation. CPIH is using as
comprehensive measure of inflation such as council tax, owners occupier's housing costs, which
are not including in CPI.
Statistical data in terms of CPI index

From the above table Consumer price index presents data of changes in inflation from
2007 to 2017. There is taking official national statistics from different variable quantity and
counts. In this shows that price index increasing continuously with rate of 3.5% (approximate).
From the table of total price index from 2007 to 2017 changes are not much more.
Retail price index
It is a measure of inflation that considers what people expend on basic goods and
services. It is measured by taking the normal of modification in price of goods and services
complied by the suitable government authority. RPI shows the changes in cost of living because
it reflects the movement of prices in a range of goods and services used continuously such as
food, bus fares, heating house, petrol and household goods (Dutta, 2016). RPI mostly computed
on monthly basis, but an annual rate is also published which serves as a standard for modify
inflation indexed salaries and wages, tax allowances and pensions. RPI including some

components that are not including by CPI like as mortgage interest payments related to owner
occupied housing.
Statistical data in terms of RPI index
From the above mentioned table of RPI presents the data of retail price index from 2007
to 2017. These collective data are taken from office national statics to show the changes in price
index. After measurement of the prices of retail result is coming that price index increased
continuously with the rate of 3.5% (approximate).
P2 Evaluate data from a variety of sources after analysing from different methods
CPI annual values
Year CPI Total
2007 105 1256.4
2008 108 1301.8
2009 111 1330

2010 114 1373.7
2011 120 1435.3
2012 124 1484.9
2013 126 1513.5
2014 128 1535.6
2015 128 1536.3
2016 129 1546.5
2017 132 1587.6
RPI annual value
Year RPI Total
2007 207 2478.6
2008 215 2577.9
2009 214 2564.2
2010 224 2682.7
2011 235 2822.2
2012 243 2912.7
2013 250 2999.5

2014 256 3072.4
2015 259 3102.5
2016 263 3156.6
2017 272 3269.7
Differences between these indices
CPI CPIH RPI
Consumer price index using to
calculate average price of
products and services.
It is using as new measuring tool
that calculate taxes and in this
those items included that are not
included in CPI.
Retail price index mainly
calculated prices related to
basic goods and services.
CPI measures by the consumer
price index that are related to
inflation.
It is settled by CPI which
measures housing costs of goods
and services buy by final
consumers (Fayol, 2016).
It shows changes in cost of
living such as food, petrol,
house hold goods.
Consumer price index method
is mostly used by regulatory
This type of tool is used by ONS
(Office for National Statistics) for
It is mostly used by
government, business, and

bodies to find out changes in
price of specific products.
business enterprise to show high
rate of indices which is also
called the consumer price index.
economists for the rising
prices rate.
d) Used of collected data from consumer price index to determine annual inflation
Annual inflation rate calculate for deciding changes in the prices related to particular
products and services providing by regulatory agencies (Ross, 2017). These inflation rate are
calculating with the help of consumer price index because of its track to fluctuations in the
prices. This would help to decide expansion of an organisation. From the above statical data
present that in 2017 price index is 1587.6 and in 2016 was 1546.5 so it was approximately 2%
increased.
Significance of calculating inflation rate
Inflation is a numerical portion of rate at which normal value derive with several products
and services. Measuring changes in average price levels for using index that are showing
inflation rate how to increases and how to decrease with significant rate. It is not possible to keep
all data in accurate way for every good and services in the economy at all times (Haimes, 2015).
To calculate the fluctuation in prices of products and services and analysing the spending
capacity of consumers. Inflation rate need to calculate because it showing economy of the
country and it is decide the cost of delivered products and services.
M1 Sources of national statistics with regard to the gender pay gap
It is examined that in UK organizations are not paying equally to female staff compare to
male staff. They are pay less to female staff that is effected to consumer price index and it is
showing low inflation rate of the economy. After analysis it is getting that 885 cases are related
to sexual orientation pay hole.
D1 Difference between descriptive, exploratory and confirmatory analysis
Descriptive Exploratory Confirmatory
This analysis are using as a
procedure in corporates
regarding to capacities and
qualities. With the help of this
specific reasons are utilized
This analysis helping to know
which kind of information
wants when prices are up
down and it will underlined
that route for better
It is a helping to analysis
provide information and these
information are utilized for
factual devices like state of

through probability. performance (World Health
Organization, 2014).
mind, critically and surmise.
ACTIVITY 2
P3 Analysis of qualitative and quantitative raw business data using appropriate statistical
methods
a) O-give curve to determine median
In statistics, O- give graph is a plot that are used in statistics to show the cumulative
frequencies. With the help of this curve know no of observation and quickly determine equal to a
particular value.
More than O-give curve
Hourly earning in
Euro
(Class Interval)
No. of Leisure central
staff
(f)
More than O-give Cumulative frequency
Below 10 4 More than 0 50
10 but under 20 23 More than 10 46
20 but under 30 13 More than 20 23
30 but under 40 7 More than 30 10
40 but under 50 3 More than 40 3
Total 50
Less than O-give Curve
Hourly earning in
Euro
(Class Interval)
No. of Leisure central
staff
(f)
Less than O-give Cumulative frequency
Below 10 4 Less than 10 4
10 but under 20 23 Less than 20 27

20 but under 30 13 Less than 30 40
30 but under 40 7 Less than 40 47
40 but under 50 3 Less than 50 50
Total 50
From the above graphical chart presented that median acquire is approximate £19.0 for
hourly earning for leisure centre staff of London area while determiner range of interquartile.
b) Mean and standard deviation for hourly earnings of London area
Mean
Simple or arithmetic average of a range of values or quantities are calculating by the no
of values dividing by the total of all values (Zhou and Luo, 2015). After that getting result is
mean as average and it is also known as arithmetic mean. It is mostly using to calculate mid
point of the set values and it is use to drive central tendency. With the help of this method know
accurate conclusion and interpretation of statistical data.
Median
It is a statistical term that is one way of finding the average of a set of data points.
Median means middle that quantity or value falls halfway between a set of values arranged in an
rising or downhill order (Jayakumar, Solairaju and Sulthan, 2014). It is very easy to calculate and
Below 10
10 but under 20
20 but under 30
30 but under 40
40 but under 50
Total
0
10
20
30
40
50
60
No. of Leisure central staff
(f)
More than O-give
Cumulative frequency
Less than O-give
Cumulative frequency

easily understand. It will be using to track location of large descriptive statistics. From the set of
numbers identify median in systematic way like from small to large value. It is calculating if odd
number is there is observation, then middle value is median. Whereas if even number is there is
observation, then average after that result is as median related to middle value.
Standard deviation
It can be calculated as square root of variance and standard deviation helping to
measuring extended of data about mean value. Standard deviation divided into two parts first one
is sample and second one is population standard deviation. It is related to statistical population,
probability distribution and random variable.
Hourly
earning in
Euro
(Class
Interval)
No. of Leisure
central staff
(f)
Middle data
(x) (F*x)
Middle data
(x2) (F*x2)
Below 10 4 5 20 25 100
10 but under
20
23 15 345 225 5175
20 but under
30
13 25 325 625 4225
30 but under
40
7 35 245 1225 8575
40 but under
50
3 45 135 2025 6075
Total 50 1070 24150
Working notes:
Mean = ∑Fx / ∑F
= 1070/50
= 21.4

Standard deviation = √ (∑Fx2 / ∑F) - (∑Fx / ∑F)2
= √(24150/50) – (21.4)2
= √483 – 457.96
= √25.04
= 5. 0 (approx)
Comparison of earning of London and Manchester area
Hourly earning for leisure centre staff in Manchester area -
Median £14.00
Mean £16.50
Interquartile Range £7.50
Standard Deviations £7.00
Median £19.00
Mean £21.40
Interquartile Range £14.00
Standard Deviations £5.00
M2 Assessment of different statistical application
According to activity 2 there are two typical techniques are used for know required
quantitative figures. Coefficient correlation and standard deviation are analysed according to
time period like quartiles and hourly profit to know standard deviation and mean factors. These
factors are showing by graphical representation through. In this explained subjective data for
quantitative figures.
ACTIVITY 3
P4 Statistical methods used in business planning, inventory management and capacity
management
a) Economic Order Quantity

It is recognised as order quantity that minimise the sum of total keeping costs and
ordering costs that are related to inventories such as raw materials or product related inventories.
In the other words the economic order quantity is the optimal amount of goods to be buy at one
time in order to decrease the annual total costs of carrying and ordering or keeping items in
inventory (Keller, 2015). This technique helping to an organization for decreasing stock
expenses and boost its benefits.
Formula: EOQ = √(2 x demand x cost per order) / cost of holding per unit of inventory)
EOQ = √( 2 x D x Co / C)
Where, D = Demand per year;
Co = Cost per order;
C = Cost of holding per unit of inventory
In this present case, Demand of t-shirt is 2000 and
Cost per t-shirt = £5
Cost of holding = 2
EOQ = √2*2000*5/2
= 100 Units
b) Re - Order tee-shirts
The re order level related to the stock of the business to re order point through which
organisations can control inventories as well as can fulfil demand of customers on time. It is
understand by an example if a company runs out of its inventory so level of stock then it leads to
cause deficiency in cost (Zyphur and Oswald, 2013).
c) Calculations of inventory policy cost
Inventory Policy Cost = Purchase cost + Cost per order + Carrying cost
= 10 + 5 + 2
= £17
The inventory cost is £17 because inventory includes all the cost of maintaining stock.
d) Current service level to customers
Current Level of service = Demand per week x Availability of t-shirt
150 = 30*4 + s
s = 30
s = z*σ²*√

30 = z*15*√4
z = 1
Service level approx = 84%
e) Work out the re-order level to achieve desired service level
Re-order level (ROQ) = (Lead time x daily average usage) + safety stock
= (28 x 2) + 150
= 206 units
M3 Justification and use of Statistical techniques
In activity three using economic order quantity for analysed techniques to measure of
reorder and management stages. Standard deviation statistics technique is utilized to analysis of
difference between standard perquisite and genuine interest of t-shirts. These techniques are
using powerful terms foe examine to clients.
D2 Explanation and recommend judgement for activity
After analysis result will be come that there is required to modify of financial order
request amount met the administration dimensions of jenny Jones's shop. It is settled to re-order
level according to structure for additional cost.
ACTIVITY 4
P5 Use of adequate tables and charts to execute the findings for several variables
Consumer price index
Year Total
2007 1257.3
2008 1300.7
2009 1324
2010 1367.7
2011 1437.4
2012 1479.8
2013 1520.4

2014 1537.4
2015 1530.2
2016 1542.4
2017 1579.5
Retail price index
Year Total
2007 2467.4
2008 2576.7
2009 2564.2
2010 2682.7
2011 2822.2
2012 2912.7
2013 2999.5
2014 3072.4
2015 3102.5
1 2 3 4 5 6 7 8 9 10 11
0
500
1000
1500
2000
2500
Year
Total

2016 3156.6
2017 3269
1
2
3
4
5
6
7
8
9
10
11
0
1000
2000
3000
4000
Year
Total
b) Data used form activity 2 to produce an ogive for cumulative % of staff vs hourly
earnings

O- give curve

Below 10
10 but under 20
20 but under 30
30 but under 40
40 but under 50
Total
0
10
20
30
40
50
60
No. of Leisure central staff
(f)
In percentage form
More than O-give
Cumulative frequency
Less than O-give
Cumulative frequency
M4 Graphical representations assessed in activity one and second
For presenting information of activity 1 & 2 using graphical form with charts and graph.
There is a use of column charts and bar charts to showing accurate calculations with appropriate
methods and clarifying all the information that is summarises of business in effective form.
Column charts mainly used for consumer price index and retail price index form office of
national statistics.
D3 Use of graphical and table representation in activity one and two
A proper Statistical procedure required for present information and data in systematic
way and easy to understand. There is proper use information to find out of conditions and
balances with creating changes in terms of activity one and second. The column charts and bar
charts are constructed in terms of presenting the information and statistical data in effective
formatting.
CONCLUSION
From the above discussion it is concluded that statistics for management is important
because it helping to know accurate data and business information. These are summarised by
analytical data and published sources. Consumer price index and retail price index helping to
know up and downs of the prices and how to effect it on inflation rate. Techniques of statistics

helping to business for management along with helping to manage inventories. These statistical
analysis are showing by charts and tables.

REFERENCES
Books and Journals
Ajiboye, A. S., 2014. Evaluating an ATM Service Using Queue Theory. Journal of Statistics and
Management Systems. 17(5-6). pp.519-527.
Brewster, C. and Hegewisch, A. eds., 2017. Policy and practice in European human resource
management: The Price Waterhouse Cranfield survey. Taylor & Francis.
Caulcutt, R., 2014. Statistics in research and development. Chapman and Hall/CRC.
Dutta, A., 2016. Reassessing the long-term performance of Indian IPOs. Journal of Statistics and
Management Systems. 19(1). pp.141-150.
Fayol, H., 2016. General and industrial management. Ravenio Books.
Haimes, Y. Y., 2015. Risk modeling, assessment, and management. John Wiley & Sons.
Jayakumar, G. D. S., Solairaju, A. and Sulthan, A., 2014. A Multivariate Generalized Double
Exponential Family of Distribution of Kind-1. Journal of Statistics and Management
Systems. 17(5-6). pp.445-478.
Keller, G., 2015. Statistics for Management and Economics, Abbreviated. Cengage Learning.
Ross, J. E., 2017. Total quality management: Text, cases, and readings. Routledge.
World Health Organization, 2014. World health statistics 2014: a wealth of information on
global public health. World health statistics 2014: a wealth of information on global
public health.
Zhou, Q. and Luo, J., 2015. The risk management using limit theory of statistics on extremes on
the big data era. Journal of Computational and Theoretical Nanoscience. 12(12).
pp.6237-6243.
Zyphur, M. J. and Oswald, F. L., 2013. Bayesian probability and statistics in management
research: A new horizon. Journal of Management. 39(1). pp.5-13.