Analyzing Research Papers

This assignment involves analyzing a provided list of research papers across diverse fields. Students are tasked with summarizing each paper's key findings, methodology, and contributions. The analysis should highlight the relationships between different papers, identifying common themes, trends, or areas of divergence in research approaches.

Statistics for management

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
TASK 1............................................................................................................................................1
A. Determining the differences between men and women earning in public sector..............1
B. Analysing the variation in the private sector earnings of men and women.......................2
C. Drafting a time chart for group A during 2009-2016........................................................3
D. Identifying the annual growth rate of four group in table A with the help of above
presented chart........................................................................................................................4
TASK 2............................................................................................................................................5
Section A..........................................................................................................................................5
2.1 Presenting the data in the form of Diagram......................................................................5
2.2 Analysing the average marks obtained by students as well as their strength and weakness
................................................................................................................................................6
2.3 Drafting report which contains the informations relevant with the performance of students
................................................................................................................................................8
Section B..........................................................................................................................................9
2.4 Determining the average weights of children with the help of line of best fit.................9
TASK 3..........................................................................................................................................10
A Analysing the numbers of deliveries currently made in each year...................................10
B Determining the numbers of deliveries for olive oil bottles.............................................11
C Implication of the proper statistical formula for EOQ measurement...............................11
TASK 4..........................................................................................................................................12
4.1 Presenting each data with the help of various charts......................................................12
4.2 Analysing the relationship between prices of house and bedrooms in the three streets.14
CONCLUSION..............................................................................................................................15
REFERENCES..............................................................................................................................16

INTRODUCTION
To have the successful organisational operations there is need to have proper statistics
and measurement of the findings, which will be helpful for accurate decision-making. In the
present report there will be discussion based on various analysis, which are relevant with the
public and private sector earning capacity of men and women. There will be graphical
presentation of various data or information, which will be helpful for clear observations and
understanding.
TASK 1
A. Determining the differences between men and women earning in public sector
Hypothesis 0: It can be said that there is no such differences in the earning capacity of men and
women employees.
Hypothesis 1: This said that there would be differences between earning capacity of men and
women employees in the public sector.
Particulars
Men earnings in
Public sector
Women earnings in
Public sector
2009 30638 25224
2010 31264 26113
2011 31380 26470
2012 31816 26663
2013 32541 27338
2014 32878 27705
2015 33685 27900
2016 34011 28053
Average 32276.625 26933.25
Variance 1449962.27 977868.41
Observations 8 8
Hyp. Average differences 0 0
Differences 13
T statistics 9.71
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P(T<=t) one-tail 1.2709E-07
t Critical one-tail 1.770933396
P(T<=t) two-tail 2.54179E-07
t Critical two-tail 2.160368656
Interpretation: In accordance with the above mentioned report it can be said that, there is
no such differences in the earning capacity of men and women it can be understand as per
1.27>0.05. Therefore, such analysis present that there is no such difference in their earning
capacity. Thus, it can be said that the ratio of their remuneration acquisition is same as per the
increment in the level of education and the reduction of dependency of women over men's. There
may be fewer numbers of women employees are available in the environment but they have the
adequate revenue generation which is balancing the ratio (Jimenez, Miller and Bridle, 2017).
B. Analysing the variation in the private sector earnings of men and women
Particulars
Men earnings in
Private sector
Women earnings in
Private sector
2009 27632 19551
2010 2700 19532
2011 27233 19565
2012 27705 20313
2013 28201 20698
2014 28442 21017
2015 28881 21403
2016 29679 22251
Average 28062.875 20541.25
Variance 840242.6964 988729.9286
Observations 8 8
Hyp. Average differences 0
Differences 14
T statistics 15.73088181
P(T<=t) one-tail 1.35387E-10
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t Critical one-tail 1.761310136
P(T<=t) two-tail 2.70773E-10
t Critical two-tail 2.144786688
Interpretation: In accordance with the above listed table, it can be said that, the earning
capacity of men and women employees in the private sector has been analysed as per the
statistical measurements. Thus, it can be said that there will be fruitful advancement in case of
women employees because there is also no such differences in these sectors as compared with
the public sector. In accordance with the mean of both the categories, which represents 28062.88
for men and 20541.25 for women, which does not have that, must variations. In context with the
standard deviations of both the categories, do not have that many differences (Olson and Wu,
2017). Thus, it can e said that the currently women are being capable of making the adequate
revenue retention as well as have the favourable earning capacity.
C. Drafting a time chart for group A during 2009-2016
In accordance with the pictorial presentation of the growth in income, capacity of men
and women in the public and private sector can be analyse and measured. Therefore, such
determining explanations that there has been appropriate development and growth in the public
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and private sectors as per the increment in the level of earning form women employees (Shah
and Tarfaoui, 2017). However, in accordance with the public sector income of men employees
has risen as 30638 in 2009 to 34001 in 2016 while in the respect to the same the women workers
as 25224 in 2009 while in 2016 it reaches to 28053. In terms with the private sector, earning
capacity of men worker it was 27632 in 2009 while in 2016 it reaches to 29679 while the rise in
the income retention of women employees has growth such as 19551 in 2009, which increases to
22251 in 2016.
D. Identifying the annual growth rate of four group in table A with the help of above
presented chart.
Basis 2010 2011 2012 2013 2014 2015 2016
Men employees in public sector 2.0% 0.4% 1.4% 2.3% 1.0% 2.5% 1.0%
Women Employees in public sector 3.5% 1.4% 0.6% 2.6% 1.3% 0.7% 0.5%
Men employees in private sector -1.3% 0.9% 1.7% 1.8% 0.9% 1.5% 2.8%
Women employees in private sector -0.1% 0.2% 3.8% 1.9% 1.5% 1.8% 4.0%
Pictorial presentation of the percentage change in income capacity:
Interpretation: To analyse the percentage change in the income capacity of men and
women workers in both the sectors it can be said that there has been fluctuation in each year as
some time it has the positive outcomes while sometime it reflects the negative results (Cutiva
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and et.al., 2017). In accordance with the changes in the percentage of men employees in public
sectors, it has changes of 2.0% to 1.0% until 2016. In accordance with the women employees in
public sector, that has been changes as 3.5% to 0.5% until 2016. On the other side the percentage
variation in private sector men employees as -1.3% to 2.8% while in context with women
employees it has -0.1% to 4%. Thus, as per such analysis this can be said that, there is
appropriate development of employments and income capacity of both the categories of
employees. In comparison, with the public sector the private sector has rapid growth in the
revenue retention from women employees (Grohmann, 2017).
TASK 2
Section A
2.1 Presenting the data in the form of Diagram
In accordance with the marks scored by students can be seen in the diagram, which helps
in analysing the variations of fluctuations of their level of marks obtained. There has been
attainment of maximum marks by the students is 72 while the lowest score has been obtained as
20. In accordance with analysing the average marks, which has been obtained by such students,
is between 40-50. However, in consideration with the making the fruitful improvements in the
performance of students there is need to implicate various changes in the teaching style and
improvements in the learning capacity of students (Caracoglia, Giaccu and Barbiellini, 2017).
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The efforts must be made by school in terms of improving such results at least at 60% level of
marks must be obtained by students.
2.2 Analysing the average marks obtained by students as well as their strength and weakness
Numbers Marks scored by students
1 20
2 72
3 60
4 41
5 37
6 32
7 43
8 46
9 45
10 62
11 64
12 30
13 39
14 58
15 75
16 45
17 58
18 56
19 39
20 40
21 21
22 29
23 68
24 59
25 54
26 42
27 37
28 30
29 70
30 45
31 46
32 36
33 43
34 33
35 48
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36 39
37 41
38 48
39 44
40 57
41 52
42 55
43 32
44 46
45 40
46 48
47 68
48 40
49 48
50 56
Average 46.74
Mode 48
STDEV 12.82187226
Interpretation: On the basis of above measurements of marks scored by 50 students.
Therefore, the average performance of all the students in the school has 46.74. In accordance
with the maximum marks and lowest marks, it can be said that the average numbers of students
have obtained quite favourable marks. The medium or mode score made by such scholars is 48
and the standard deviation has been measured as 12.821872260.
Mean strength and weaknesses:
Strength
 It considered all the data and
information to find the answers
(Advantages and disadvantages of
mean, median and mode, 2014).
 There will be influence of both the
continues of discrete numeric
information
Weaknesses
 There will be variations in the
outcomes as per the very large or small
numbers has been considers while
measuring it.
 The analysis cannot be made if the
information were not be summarised or
added.
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Mode strength and weaknesses:
Strength
 If the data is not facilitated in the data
set then the average will be considered
as the mode.
 It can be analysed based on numerical
and categorical data apart from median
and mode.
Weaknesses
 The analyses can representatives’ more
than one outcome.
 If there is no same data or equal rang
series than mismeasurement will not
took place (Statistical Language -
Measures of Central Tendency, 2013).
 There will be less accuracy in terms of
outcomes.
Analysis the measure of dispersion:
In accordance with this concept, it can be said that such measurements represents the zero
balance of the outcomes as well as reflect the non-negative outcomes from any data set. It can be
said that if there is high values in the deviation which will affect in the rapid increment in the
rate while the rate is low that the estimation lies of the reduction in the fluctuation of the
deviations (Mujtaba and et.al., 2017). However, as per the above analysis the deviation can be
analysed as 12.82187226, which facilitate that the rate is comparatively high and favourable.
2.3 Drafting report which contains the informations relevant with the performance of
students
To: Director of KCB school
Date: 18 January 2018
Subject: Analysing the performance of students as per the various statistical tools
Sir,
The marks obtained by various students in the school will be analysed based on
statistical tools. Thus, there has been favourable outcomes were gained based on such
operations.
Mode and Mean:
In accordance with the measurements, it can be said that there has been scoring of
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market with the average of 46.74 while the mode of such data set is 48. There is no such
variation in both of the results. Therefore, in comparison with the maximum marks obtained and
the lowest score which are 20 and 72. Thus, the mean and mode is having the favourable
outcomes.
Standard deviation:
In accordance with the standard deviation the outcomes are being obtained by such
operations is as 12.82187226, which indicate the high rate. Thus, the high rate means high
profitability and the favourable performance of the students. However, in these regards it will
be suggested that there is need to pay attention over rising the performance of students. It can be
done through appointing the skilled and qualified teachers to teach them (Du and et.al., 2017).
Section B
2.4 Determining the average weights of children with the help of line of best fit
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Interpretation: In accordance with the above listed table, it can be interpreted that value
of intercepts and beta is 7.65 and 2.15, which indicates that there will be changes in the age
variable weights for approx. 2.15 points as if the independent variable remains same and
unchanged. However, if the age of child in 7 months than the average weight would be 9.155, 8
moth children will have 9.37 and the 9-month child will have 9.58. In these regards, it can be
said that the changes in their weights will have proportionate rise in their weights.
TASK 3
A Analysing the numbers of deliveries currently made in each year
To have the property information which are relevant with the total numbers of deliveries
has been made by the firm during the period can be analysed on the basis of assuming whole
sales value is relevant with the firm (Khoshsima, Hosseini and Toroujeni, 2017). However, the
numbers of deliveries will be 450000. Thus, the same value is used as to analyse the whole
measurement.
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B Determining the numbers of deliveries for olive oil bottles
Particulars Amount
Yearly requirements 450000
No. Of trips 30
No. Of bottles to be delivered 15000
Interpretation: As per analysing the total numbers of bottles to be delivers in 30 trips it
can be measured as analysing the total requirements obtained by firm in the year thus, in
accordance with these case there has been total demand of the bottles is 450000 in a year while
in accordance with the 30 trips it can be said that each trip delivers 15000 bottles.
C Implication of the proper statistical formula for EOQ measurement
Interpretation: In accordance with the analysis, it can be said that the firm need to spend
6000 for purchasing the quantity of goods. Thus, it will be beneficial for the operations of the
organisation, which will be fruitful in terms of enhancing the productivity and efficiency of the
business. The motive behind analysing the EOQ is to examine the firm's efficiency as well as the
product marketability in terms of acquiring the re-order level.
Comparison of Cost to EOQ
Interpretation: In terms of analysing the EOQ as per various carrying cost per order,
which bring the outcomes and reflect the reduction in the order level. Therefore, at the rate of 0.5
the EOQ was 1897.37, at 0.52 it is 1860.521, at 0.54 it is 1825.74, at 0.56 it is 1792.84 and at the
rate of 0.58 it was 1761.66. Thus, it is to be measured that if the carrying value of goods will
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increase it will definitely have increase in the value of the product and reciprocally it will reduce
the order level or requirements in the market.
Total variable cost:
TASK 4
4.1 Presenting each data with the help of various charts
Bar chart diagram
Pie chat diagram
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In accordance with the findings made by professional on the basis of numbers of
bedrooms in a house at various locations as to analyse the current trend and preferences of
individuals (Gerlach and et.al., 2017). Therefore, in accordance with the single bedroom house
there are 8 houses in Green Street, 6 Houses in Church Lane and 4 Houses in Eton Avenue. On
the other side, there are majority of houses, which include 2 and 3 bedrooms in all this areas. The
2 bedroom houses in Green Street is 28 houses, in Church Lane it is 18 while in Eton Avenue it
is 20. The 3 bedroom houses in all the segmentations that Green Street has 37, Church lane has
24 while Eton Avenue has 32. Therefore, it can be said that the current requirements and the
preferences of the society lies over the 3 bedroom houses.
4.2 Analysing the relationship between prices of house and bedrooms in the three streets
Table of Correlation:
Pictorial presentation:
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In accordance with the above analysis, it can be said that there is favourable relationship
between numbers of bedrooms and the prices of houses. Thus, in consideration with such
observations the correlation of all the location represents 1. This indicates that the value of
houses is adequate as per the bedrooms.
CONCLUSION
Based on above report it can be said that to analyse the accurate outcomes the implication
of various statistical tools which has represented the adequate results. In terms of analysing the
EOQ level, it can be said that the firm is having demands in the market as per the carrying costs
of such goods. Further, there will be favourable relationship was analysed over the prices of
houses and the numbers of bedrooms in a house.
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REFERENCES
Books and Journals
Caracoglia, L., Giaccu, G. F. and Barbiellini, B., 2017. Estimating the standard deviation of
eigenvalue distributions for the nonlinear free-vibration stochastic dynamics of cable
networks. Meccanica. 52(1-2). pp.197-211.
Cutiva, L. C. C. and et.al., 2017. Four-day follow-up study on the self-reported voice condition
and noise condition of teachers: relationship between vocal parameters and classroom
acoustics. Journal of Voice. 31(1). pp.120-e1.
Du, S. C., and et.al., 2017. An optimal Ensemble Empirical Mode Decomposition method for
vibration signal decomposition. Journal of Vibration and Acoustics. 139(3). p.031003.
Gerlach, J. Q. and et.al., 2017. Urinary nanovesicles captured by lectins or antibodies
demonstrate variations in size and surface glycosylation profile. Nanomedicine. (0).
Grohmann, C., 2017. Comparison of roving-window and search-window techniques for
characterising landscape morphometry.
Jimenez, M., Miller, B. and Bridle, H. L., 2017. Efficient separation of small microparticles at
high flowrates using spiral channels: Application to waterborne pathogens. Chemical
Engineering Science. 157. pp.247-254.
Khoshsima, H., Hosseini, M. and Toroujeni, S. M. H., 2017. Cross-Mode Comparability of
Computer-Based Testing (CBT) Versus Paper-Pencil Based Testing (PPT): An
Investigation of Testing Administration Mode among Iranian Intermediate EFL Learners.
English Language Teaching. 10(2). p.23.
Mujtaba, A. and et.al., 2017. Thoughts on the scatter seen in cyclic Mode I fatigue delamination
growth in DCB tests. Composite Structures. 160. pp.1329-1338.
Olson, D. L. and Wu, D. D., 2017. Value at Risk Models. In Enterprise Risk Management
Models (pp. 75-87). Springer Berlin Heidelberg.
Shah, O. R. and Tarfaoui, M., 2017. Determination of mode I & II strain energy release rates in
composite foam core sandwiches. An experimental study of the composite foam core
interfacial fracture resistance. Composites Part B: Engineering. 111. pp.134-142.
Online
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Advantages and disadvantages of mean, median and mode. 2014. [Online]. Available
through
:<http://www.bbc.co.uk/schools/gcsebitesize/maths/statistics/measuresofaveragerev6.shtml
>.
Statistical Language - Measures of Central Tendency. 2013. [Online]. Available
through :<http://www.abs.gov.au/websitedbs/a3121120.nsf/home/statistical+language+-
+measures+of+central+tendency>.
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