Statistical Management Report: Evaluation and Application of Data

This report delves into the core aspects of statistical management, emphasizing data analysis, business planning, and effective communication. It begins by exploring the evaluation of business and economic data, differentiating between qualitative and quantitative data, and analyzing key economic indicators like CPI, CPIH, and RPI. The report then progresses to the evaluation of raw business data, including a comparison of samples and populations, along with various sampling techniques. Furthermore, it demonstrates the use of scatter diagrams to illustrate relationships between variables and calculates the correlation coefficient. The application of statistical methods in business planning, along with justifications for their use, is also discussed. Finally, the report addresses the importance of using appropriate charts and tables to effectively communicate findings, providing a comprehensive understanding of statistical management principles and their practical application in business contexts.

Statistical Management

Table of Contents
INTRODUCTION...........................................................................................................................1
ACTIVITY 1....................................................................................................................................1
P1 Evaluation of business and economic data........................................................................1
P2 Data from variety of sources using various methods of analysis......................................4
M1 Analysis of price indices other than Office of National Statistics...................................6
D1 Differentiation between the exploratory, confirmatory and descriptive analysis with
examples.................................................................................................................................6
ACTIVITY 2....................................................................................................................................7
P3 Evaluation of raw business data using a number of statistical methods...........................7
M2 Assessment of different statistical application...............................................................11
ACTIVITY 3..................................................................................................................................12
P4 Application of statistical methods in business planning.................................................12
M3 Justification and use of statistical methods....................................................................13
D2 Explanation and recommendation for activity 3.............................................................13
ACTIVITY 4..................................................................................................................................14
P5 Using of appropriate charts finding communicate..........................................................14
M4 Graphical representation assessed in activity one and second.......................................18
D3 Use of tables and graphical representations in activity 1 and 2......................................18
CONLUSION................................................................................................................................18
REFERENCES..............................................................................................................................20

INTRODUCTION
Statistical management is the process of formulating right decisions so that uncertainties
can be faced appropriately in future. It is used in financial analysis, auditing, production,
econometrics and operations that are performed to modify services and market research. The
procedure of statistical management involves collection and scrutinisation of business data.
Managers of the organisations need to collect quantitative history of occurrence elements on
optimal repairs and procedures. It helps to forecast the use of material in every sector of the
business so that the shortage can be ignored. It is very important for a business entity as it can
help to ensure quality, make connections and for provide effective judgements.
This report covers various topics such as evaluation of business, economic data, raw
business data by using a number of statistical methods, application of statistical methods in
business planning, communication of findings by using appropriate charts and tables.
ACTIVITY 1
P1 Evaluation of business and economic data
Nature of data and information can help to manipulate them by different techniques of
statistical analysis. There are two different types of data these are qualitative and quantitative.
First one is qualitative that includes characteristics and the another type contain the data in
numeric format. Data can be turned into information and information in to knowledge (Carlson
and Wu, 2012). Data is unprocessed facts and figures that are recorded without interpretation
when the recorded data get interpreted than it will become information. Knowledge is the
combination of different type of information.
A. & B. CPI, CPIH and RPI by using office of national statistics website and
appropriate tables and graphs for all of them:
 CPI and CPIH: Consumer price index is used to measure the changes ion the price level
of the market and CPIH is a new addition in the CPI in which housing cost of owner
occupiers is measured. CPIH rate was 2.2% in September 2018 which has been decreased
as compare to 2.4% which is for August 2018 (Chen and et. al., 2012). consumer price
index rate was 2.4% in September 2018 which has been decreased as compare to August
which is 2.7%. the rate has been decreased because prices of food, non alcoholic
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beverage, transport, recreation, culture and clothing sector has declined between the
month of August and September.
CPI:
From the above chart it can be summarised that there is frequent fluctuation in the CPI of
UK as in year 2007 it was 4.3% and now after 10 years has reduced up to 3% which is related to
year 2017 (Office of national statistics, 2018).
RPI: Retail price index is a measure of inflations that are monthly published by Office
for national statistics. It represents the changes in the cost of retail goods and services. RPI rate
has been decreased in month of September in year 2018. it was 3.5% in August month and
declined up to 3.3% in September (Dezső, Ross and Uribe, 2016).
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C. Difference between CPI, CPIH and RPI:
CPI CPIH RPI
It is consumer price index. It is consumer pricing index
for housing.
It is retail price index.
It is used to measure the
changes in prices of the
market.
It is a new measure which is
used to measure housing cost
of owner occupiers.
It is used to measure the
inflations that are published
monthly by Office for National
Statistics.
It is government preferred
measure of inflations.
It represents the changes in
average residential rates.
It helps to analyse the changes
in the cost of retail goods or
services.
D. Calculation of inflation rate with the help of consumer price index:
3

Inflation rate is calculated with the help of consumer price index which is shown by
Office of national statistics on monthly basis. If the CPI is continuously decreasing than it will
affect the inflation rate of the nation and will also result in fluctuation of inflation rates. The
changed rate is converted to the percentage to calculate inflation (Easterby-Smith, Thorpe and
Jackson, 2012). For example, as CPI of year 2017 has increased up to 132 from 129 which is for
year 2016. The total difference is 2% which has resulted in the increment of inflation rate.
E. Why it is important to have information of Inflation:
For every organisation it is very important top have information of inflation rate as it
directly affect the efficiency of executing business operations. It helps to plan for upcoming
year's activities so that, this may not result adversely. If the managers of the companies are
having proper information of inflation than they may formulate effective strategies to perform
their operational activities efficiently at the time of increased or decreased inflation rate. Inflation
rate of UK is 2% that affects the purchasing power of customers and also affect the CPI and RPI
because it changes with the fluctuation in inflation.
P2 Data from variety of sources using various methods of analysis
CPI:
Year Total
2007 105
2008 108
2009 111
2010 114
2011 120
2012 124
2013 126
2014 128
2015 128
2016 129
2017 132
4

From the above chart it can be analysed that CPI is continuously increasing sine year
2007 to year 2017. It has increased up to 132 which is for 2017 as compare to year 2007.
RPI:
Year Total
2007 207
2008 215
2009 214
2010 224
2011 235
2012 243
2013 250
2014 256
2015 259
2016 263
2017 272
5

From the above chart it has been analysed that RPI rate is increasing with the year. In
year 2017 it is 272 which has been increased as compare to prior 10 years.
M1 Analysis of price indices other than Office of National Statistics
In UK the organisation are paying less compensation to the female staff as compare to
male staff because the employers think that they are not able to work productively as compare to
male. It has been identified that 8 out of 10 companies are paying less to the female staff as
compare to male staff. The pay gap according to the data the median pay gap is 9.8% between
men and women.
D1 Differentiation between the exploratory, confirmatory and descriptive analysis with examples
Descriptive Exploratory Confirmatory
It can be defined as the
structured method which is
concerned with capabilities
and qualities of subject.
It is used to analyse that what
type of information will be
required for the break down
and the way in which it will be
outlined for the effective
business execution.
It is apart of data or content
assessment which is used by
formal and factual tendencies
which includes summarising,
certainty etc.
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ACTIVITY 2
P3 Evaluation of raw business data using a number of statistical methods
Difference between sample and population:
Basis Sample Population
Meaning Sample is the sub group of total selected
population selected for a particular
research.
Population is the collection of all the
factors processing same characteristics
that reflects universe.
Measurem
ent
It is measured in statistic. It is measured in parameter.
Focus It is focused wit5h making inferences
regarding the population.
It is focused with identifying the
characteristics.
Method of
data
collection
Data is collected by sample survey or
sampling process.
Data is collected by complete recites or
census.
Techniques of sampling: There are two different sampling techniques that can be used
by a researcher while the research program. Both the methods are described below:
 Probability sampling: This techniques of sampling is based on random sample of the
selected population for research purpose. It make sure that every element of the
population get an equal chance to be the part of the sample so that an accurate result can
be received. It is also known as random sampling (Fleming and et. al., 2013).
 Non Probability sampling: It does not depends upon the random selection of sample
form the selected population. It is more dependent upon the researcher's cognition to
select elements for a sample. It is also known as non random sampling technique. There
is possibility that the outcome of this method can be biased and make it difficult for all
the factors of selected population to be the part of sample evenly.
A. Scatter diagram to show relation between hot drink sale and average weekly
temperature.
Use of scatter plots: It can be defined as the use of multidimensional data measurement
and visualisation in which the data has been presented upon a chart in the form of dots and all of
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them show the fluctuations in the data. In this report scatter diagrams are used to analyse the
relationship between average temperature and hot drink sales. From the diagram it can be
identified that there is positive or negative relation between both of the elements. In this diagram
there is a positive relation between both the factors as the sales increases or decreases with the
changes in temperature (Froeschl, 2013). If the temperature increases than it has resulted in the
increment in the sales. Decrease in average temperature has been resulted in the decreased
amount of sales.
Week Average Temperature
Hot Drinks
Sales
1 18.5 15
2 16 10
3 13 13.5
4 19.5 15
5 20 18
6 19 14
7 15.5 13
8 14 8.5
9 12.5 6
10 15 9
8

From the above scatter diagram it can be analysed that there is a positive relationship
between average temperature and hot drink sales because when the temperature decreased the
sales will also decrease with the same and when the temperature increases than the sales will also
increases with the time. In third week temperature meet the sales and in ninth week the sales has
decreased too much and temperature was also at the lower level.
B. Calculation of correlation coefficient and coefficient of determination:
Correlation coefficient: It is used to analyse relationship between two variables. It is
mainly used in liner regression. If it results in positive 1 than it means that there is a increase in
one variable and increase in fix proportion of other variable and if it shows -1 as a result than it
means than there is a positive increment in one variable and decrease a fixed proportion in other
variable (Ghertman, Obadia and Arregle, 2013). It is denoted by r. Formula to calculate
correlation coefficient is as follows:
Formula= N∑xy - (∑x) (∑y)/ √[N∑x2 - (∑x)2] [N∑y2- (∑y)2]
Here,
N= number of weeks
∑xy= Sum of average temperature and hot drinks sale
9
0 2 4 6 8 10 12
0
5
10
15
20
25
15
10
13.5
15
18
14 13
8.5
6
9
18.5
16
13
19.5 20 19
15.5
14
12.5
15
Average Temperature
Hot Drinks Sales

(∑x)= Sum of average temperature
(∑y)= Sum of hot drink sales
∑x2= Sum of squared average temperature
∑y2= Sum of squared hot drink sales
Calculation is as follows:
Week
Average
Temperature(X)
Hot Drinks
Sales(Y)
1 18.5 15
2 16 10
3 13 13.5
4 19.5 15
5 20 18
6 19 14
7 15.5 13
8 14 8.5
9 12.5 6
10 15 9
Coefficient
correlation 0.80
Determination of
correlation 0.64
Determination of correlation: It is denoted by r2. It is used to measure the way in which
a statistical data model a data. It also specifies the variation in dependent and independent
variables that are shown as x and y. Formula for determination of correlation is as follows:
Formula: (Correlation coefficient)2
from the above table it has been identified that correlation of coefficient for client c is
0.80 and determination of coefficient is 0.64.
c. Equation that may help to predict sales for a upcoming period.
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If client want to estimate sales for a particular temperature which is lower then the
highest temperature on which the sales has been attained than following equation can be
implemented:
Formula: sales of week A+ Sales of week B /2
Here,
Sales of week A= Sales of average temperature below the temperature of desired sales.
Sales of week B= Sales of average temperature above the temperature of desired sales.
When the client is willing to estimate the sales on that temperature which is more than the
higher temperature on which has not yet been achieved by client.
Formula: Sales of the nearest temperature of higher temperature- sales at the higher
achieved temperature* the difference between higher temperature and the desired temperature
(Hipel and Fang, 2013).
D. prediction of the sales at a particular temperature:
Sales at 17oC= sales of week 2 = sales of week 6/ 2
= 10+14/2
= 12
Sales at 25oC= Sales of week 5 – sales of week 6*( Desired temperature- temperature in
week 5)
= 18-14 (25-20)
= 4*5
= 20
From the above calculation it has been estimated that at 17oC estimated sales is 12 hot
drinks for client C and at 25oC temperature is is approximated that sales will be 20 hot drinks.
E. reliability of the predictions
As the prediction that are made are mainly based on past data and it has been estimated
that if the client increase the temperature up to 25oC than the sales will be 20 hot drinks and if
the temperature is 17oC than the sales will be 12. the predictions are reliable as all of them are
made according to the data of past week which has been provided by the client.
Forecasting: It refers to the estimation of possible future conditions that may affect the
operational activities of an organisation. There is an estimation which has been used for client C
to estimate the sales at a particular level of temperature.
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Use of Excel and SPSS: Excel is used to reduce the burden of counting various formulas
and equations help to calculate the appropriate and accurate result. It has also been used while
calculating correlation and Coefficient as there are various formulas that may help to calculate
them easily without wasting time of the calculations of others. SPSS stands for Statistical
Package for the Social Sciences which is a software and used to get appropriate result of the data
which has been inserted by the user (Keller, 2015).
Two different methods are used to analyse the right result for client C. Correlation
coefficient and determination of correlation are used to analyse the relationship between average
temperature and sales of hot drinks. It has also been identified that there is a favourable relation
between both of them.
M2 Assessment of different statistical application
Two separate methods are used to in the example above those are correlation of
coefficients and determination of coefficient. Both are very helpful in the identification of the
relation in hot drinks and temperature. The relation can be identified with the help of scatter
diagram.
ACTIVITY 3
P4 Application of statistical methods in business planning
Statistical methods are the mathematical formulas and equations that are used by the
owner or accountants of an firm to form effective decisions for business. There are two different
techniques are used as the statistical management tools. These techniques are as follows:
 Inventory management: It is the supervision of non capitalized stocks that are used by
manufacturing companies in order to produce goods. It helps the managers to supervise
the supply chain while taking good in warehouses.
 Capacity management: It is a technique which is used to by managers of the companies
to meet current needs to the future so that the operations can be executed effectively.
A. calculation of EOQ:
EOQ: It stands for economic order quantity. Main purpose of this approach is to
minimise variable inventory costs with the help of a formulated equation which is as follows:
EOQ = √2AO/C
Where, A= Annual consumption;
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O = Ordering Cost;
C = Carrying Cost
EOQ = √2*2000*5/2
= 100 Units
B. Reorder level to order t shirts:
Reorder level: It is used to calculated that when the company or firm should order the
stock before the warehouses go out of stock (Murphy, Myors and Wolach, 2014). Formula to
calculate the level is as follows:
Re-order level (ROQ) = (Lead time*daily average usage)+safety stock
= (28*2)+150
= 206 units
Frequency of Re-order = Annual consumption/ ROQ
= 2000/206 = 9.7 or 10 days
Client should order the t shirts in 10 days as it is the reorder level for the client.
C. Calculation of inventory policy cost:
It is the holding cost for the client which is calculated as follows:
Inventory Policy Cost = Purchase cost + Ordering cost + Carrying cost
= 10 + 5 + 2
= £17
The inventory cost is £17 because inventory includes all the cost of maintaining stock.
D. current service level of client:
Service level: The number of quantities delivered in time/ the total quantity of the
demand.
ROL= DL + s
150= 30*4+s
s= 30
s= z σd √L
30= z*15*√4
= 84%
E. Reorder level at desired service level:
Re-order level (ROQ) = (Lead time*daily average usage)+safety stock
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= (28*2)+150
= 206 units
M3 Justification and use of statistical methods
EOQ method is mainly used for the purpose of analysing information which is related to
the stock or inventory which is used by the organisation to manufacture products. Standards
deviation is used in the above example to determine difference between actual and budgeted
requirements of inventory for the production.
D2 Explanation and recommendation for activity 3
As analysed form the above example the Jenny Jones should improve its EOQ so that
inventory requirements can be fulfilled effectively. It has been suggested to the managers of the
company to change the reorder structure so that business can be operated smoothly and issues of
less inventory can be resolved.
ACTIVITY 4
P5 Using of appropriate charts finding communicate.
A) Charts indicating the changes in CPI.
CPI:
Year Total
2007 105
2008 108
2009 111
2010 114
2011 120
2012 124
2013 126
2014 128
2015 128
2016 129
14

2017 132
From the above chart it can be identified that CPI is continuously increasing with the year
in year 2007 it was 105 and in 2017 it has been reached to 132.
RPI:
Year Total
2007 207
2008 215
2009 214
2010 224
2011 235
2012 243
15

2013 250
2014 256
2015 259
2016 263
2017 272
From the above chart it has been analysed that RPI varies year to year and as it was 207
in year 2007 and in 2017 it has increased up to 272.
B) Scatter diagram of hot drinks.
Variables: It is defined as the total number, quantity that increase or decrease over time or it is
related to the changes in the values of product ans services in different situation (Re and et. al.,
2014). In business there are basically some types of variable that are described below:
 Independent variable: These kind of variable are defined as the differentiate values in
any factor that may change the variable of other factors.
 Dependent variable: These type of variable is related to the different changes only in
response to an independent variable.
In every organisation it is necessary for them to accurately analyse the data, as this
process is develop to provide accurate answer through examination and representation of data.
16

The basic step in this analytic process consist of determining problem, ascertain the availability
of appropriate data, analysing that which method would be champion in command to have best
result and applying assorted process and evaluating, compact and communication the result.
There are different kind of analysing and interpretation of collected data within a company that
are described below:
Nominal Variable: It is also called categorical variable, that means it has two or more
parts, but there is no natural order between these categories. They are consider to be the variable
that do not have any numerical values, like occupation or political party pretence. For instance,
gender of any living organising is nominal variable that have two or more categories such as
male and female, at the same time there is no integral value ordering to the categories.
Ordinal Variable: This is also just similar to the nominal or categorical, but it has a
clear ordering of the variable in context. These kind of variable are considers to be in between
that categorical and quantitative variable of economy. For example,in and economic the people
living have various kind of status these are arranged on the basis of different order categories
low, medium and high.
Interval variable: These variable have a cardinal characteristics that could be measured
along a time and they have a quantitative value. Ratio variable are part of interval variable but
has some changes in the recording system that shows that Zero does not have a definite variable
For example, suppose there is an annual income that was measured in dollar and three individual
are supposed to be provided $1000, $15000, $20000 respectively. It is observed that the ordinal
person makes $5,000 much than the first individual and $5,000 less than the 3rd person and the
range of these measure is the identical.
Frequency table: It is a method related to organising of raw material in a compact
manner that display a series of data in ascending or descending order, with a column showing the
frequencies that represent the number of time a single digit occur in the respective data set.
Simple tables: This is related the presentation of selected data in tabular form that is
taken from a large number of people so that proper examine can be done in order to find
something interesting, unique about this group.
Pie chart: It is relate to the presentation of collected and analyse data in the circular form
that is further divided into various segment depending on the information about the group.
17

Division of circle according to data in different slice help in comparison to one another or to the
whole segment (Wheeler, Shaw and Barr, 2013).
Histogram: This is related to an accurate display and presentation of numerical data. It
basically represent the reputation of specific phenomena that lies within a specific range of
value.
Frequency curve: It is related to a smooth curve that react to the confining case
Histogram computed for a frequencies arrangement of a endlessly distribution as the figure of
data became very large.
Week Average Temperature
Hot Drinks
Sales
1 18.5 15
2 16 10
3 13 13.5
4 19.5 15
5 20 18
6 19 14
7 15.5 13
8 14 8.5
9 12.5 6
10 15 9
18

In the above mention scatter diagram, it has been analysed that positive relationship
among temperature and hot drinks sales, because when there is decrease in the temperature the
sales will also go down and vice versa.
M4 Graphical representation assessed in activity one and second
In the above activity graph and scatter diagram are used to analyse the changes in RPI
and CPI and the interrelation between temperature and hot drinks. In activity one different
indexes of CPI and RPI have been used to determine the changes in the inflation rates of UK.
D3 Use of tables and graphical representations in activity 1 and 2
An effective method is required to present the actual data for the business because this
may help to analyse the current position. Bar charts and scatter diagram are used in activity one
and two to get the exact results of both the comparison.
CONLUSION
From the above project report it has been concluded that statistical management can help
an organisation to evaluate all action that needs to be taken in future to enhance profitability and
productivity. Various inventory management techniques can be used by the managers to identify
19
0 2 4 6 8 10 12
0
5
10
15
20
25
15
10
13.5
15
18
14 13
8.5
6
9
18.5
16
13
19.5 20 19
15.5
14
12.5
15
Average Temperature
Hot Drinks Sales

that what amount of inventory is required to retain in the warehouses. It can be calculated by
using economic order quantity, reorder level and other techniques.
20