Data Analysis Report: Excel, SPSS, Data Interpretation and Findings

This report presents a comprehensive data analysis, comparing the capabilities of Excel and SPSS in handling and interpreting data. Part 1 focuses on using Excel for data analysis, including data collection, function application (Vlookup, countif), and graphical representation to analyze crime rates over a 10-year period. Part 2 shifts to a case study involving a survey of 200 students, analyzing ice cream preferences and gender distribution. It explores data inquiry, outcomes, and consequences. The report also includes a detailed comparison of the merits and demerits of both Excel and SPSS, offering insights into their suitability for different data analysis tasks, and discussing their strengths and weaknesses in data handling, statistical analysis, and visualization. The report also uses various excel functions like Vlookup and countif.

DATA ANALYSING

Table of Contents
PART 1............................................................................................................................................3
INTRODUCTION...........................................................................................................................3
Main Body.......................................................................................................................................3
Valuation of use of excel for advance-handling of the data...................................................3
Evaluating of the Data fixed:..................................................................................................3
Indication of the data with the assist of excel purpose:..........................................................4
Graphical Exhibition of the data consuming suitable charts:.................................................4
CONCLUSION................................................................................................................................6
REFERENCES................................................................................................................................7
PART 2............................................................................................................................................8
INTRODUCTION...........................................................................................................................8
Main Body.......................................................................................................................................8
Data enquiry...........................................................................................................................8
Outcomes and consequences................................................................................................11
Argument..............................................................................................................................11
Merits and Demerits of using SPSS.....................................................................................12
Merits and Demerits of Excel...............................................................................................12
Conclusion.....................................................................................................................................13
References......................................................................................................................................14
Appendix........................................................................................................................................15

PART 1
INTRODUCTION
The following case study describes about the collecting of information which is used to
interpret the results which can be derived from the data. It also includes various functions
performed and aids in the plan and aims by the management. The efficiency of the collected data
matters the most which suggest that the outcomes which can be derived from the various forms
of data. In the following report the data is collected of various cases and of the period of last 10
years to compare the increase or decrease in the values in the past 10 years. The data is analysed
in the Excel worksheet which is sorted by using various function of excel such as countif,
Vlookup, etc. which helps in determining the actual relationship which can be accomplished
between the provided set of data. By using Microsoft excel the big data is managed
proportionately well as it cannot be interpreted with any other form of office document (Bécue,
Praça and Gama, 2021).
Main Body
Estimate of use of excel for advance-handling of the facts
The Microsoft Success Calculation Table helps organizations estimate broad definitions in
minutes because it's a better tool for tracking associated consequences. How it is not suitable for
various assessments while being a stable tool for information inspection. With the help of
successful and given information collection, the development process of information will be
more straightforward (Donthu, Kumar and Pandey, 2020). The information given in the survey
lists concerns about the wrongdoing phase for the current year and the past 10 years, as well as
various remaining circumstances, on the basis of which the extent of wrongdoing is exaggerated.
The different elements can be educational stage, cost, southern region, etc. of stage turn:
Assessing of the Data:
In the given information, it has performed expressive measures, including mean, median,
and mode, etc., on the information given in subsequent accounting tables. The wrongdoing rate
has averaged 102.80%, which usually indicates that wrongdoing did occur in the current year,
and the 10-year average is the same. Wrongdoing is estimated at 102.07%, indicating that the
wrongdoing value will be monitored for up to 10 years. It essentially shows that respect for

wrongdoing is upheld. Such elements in country or territory information, costs incurred, size of
the country, etc., all misrepresent the extent of wrongdoing. Expressive measurements make
creative thinking of information humbler and simple, so results can be mediated over a 10-year
span. A small number of factors are equally troubling to achieve the level of respect for
wrongdoing by separating it from that of the populace.
Outset of Data:
Under the creative thinking of information, the presentation of information has been
arranged in a graphic system by means of different outlines, guides and diagrams. These devices
provide an accessible way to shape and understand the twists and turns of events, anomalies, and
fixed information or subtleties of the game plan that have been given. In the production of
massive amounts of information, information conception tools play a key role in discovering that
information-centric decisions can be prepared ahead of time to discover great value in detail. In
the fixed given information, the information has been conceptualized with the help of the reasons
for success, which are carried out on the given information, i.e. turntable and concentration.
Carousels help organize information or details that simplify your business (Doraiswamy and
et.al., 2018).
Suggestion of the data with the assist of excel drive:
Confirmation has been accepted out with the assistance of V look up purpose
(Concealed in Excel spreadsheet)
Graphical Display of the data intense suitable charts:
The graphic display expresses the general findings of the information that has been put into
the successful calculation table, which conveys the wrongdoing for a particular year, and then
joins the information for a 10-year period. The correlation of these two insights is given in the
outline that follows, showing that both have grown in equal value over the years (Virgo, J.,
2021). The over graphs already given express the effects of wrongdoing, which relies on the
information that has been arranged in the country, as the level of schooling plays a key role in
the value of wrongdoing in the country. If the framework of learning is not properly arranged,
the degree of error will increase, and if the education level is incomplete, this change in value
will be transferred domestically (Irfan and et.al., 2019).

CONCLUSION
It can be concluded from the above report that the rate of crime level during the last 10
years. The data helps in finding the outcome which helps in determining the actual findings from
the data available. In the following report various Excel functions are used such as Vlookup and
countif to know the actual results from the data available. The data helps the company in
measuring the actual performance and actual findings of the data. In the following case it can be
improved by using the excel spreadsheet to understand the crime rate of the state. On the
following case of data various functions are applied so that various the purpose can be fulfilled.

REFERENCES
Books and Journals
Bécue, A., Praça, I. and Gama, J., 2021. Artificial intelligence, cyber-threats and Industry 4.0:
Challenges and opportunities. Artificial Intelligence Review, 54(5), pp.3849-3886.
Donthu, N., Kumar, S. and Pandey, N., 2020. A retrospective evaluation of marketing
intelligence and planning: 1983–2019. Marketing Intelligence & Planning.
Doraiswamy, H. and et.al., 2018. Spatio-temporal urban data analysis: a visual analytics
perspective. IEEE computer graphics and applications, 38(5), pp.26-35.
Irfan, R. and et.al., 2019. Ontology learning in text mining for handling big data in healthcare
systems. Journal of Medical Imaging and Health Informatics, 9(4), pp.649-661.
Priyan, M.K. and Devi, G.U., 2019. A survey on internet of vehicles: applications, technologies,
challenges and opportunities. International Journal of Advanced Intelligence
Paradigms, 12(1-2), pp.98-119.
Syam, N. and Sharma, A., 2018. Waiting for a sales renaissance in the fourth industrial
revolution: Machine learning and artificial intelligence in sales research and
practice. Industrial marketing management, 69, pp.135-146.

PART 2
INTRODUCTION
A given report file includes the findings of the information it supports, and will be provided
to the Residents' Association through an inquiry into an assessment containing information on
200 uncommon school students. For pre-determined reports, the re-assessment terms are being
arranged through factors that tolerate frozen yogurt trends, puzzle game sums and computer
game scores (Jain and Rana, 2020).
Main Body
Data enquiry
Ice cream flavour
Frequency Percent Valid Percent Cumulative
Percent
Valid
Vanilla 95 47.5 47.5 47.5
Chocolate 47 23.5 23.5 71.0
Strawberry 58 29.0 29.0 100.0
Total 200 100.0 100.0

From beginning the investigation of even display of information, it tends to have the option to
comprehended that benefit of the absolute pool score of understudies i.e., 200 a considerable lot
of them pick the vanilla taste of ice-cream. The event of understudies who picked vanilla taste
totalled 47.5% which roughly 95 understudies out of the general number of understudies. The
one more favoured taste of the frozen yogurt was conveyed as strawberry it was portrayed
beneath the event of 58 understudies (Kouziokas, 2020).
Gender (Male or Female)
Frequency Percent Valid Percent Cumulative
Percent
Valid
Male 91 45.5 45.5 45.5
Female 109 54.5 54.5 100.0
Total 200 100.0 100.0

After reading the picture above, the accessibility of candidates is often checked. The number
of candidates designated for the exam is definitely 200. Then again, part of the diversity, there
are typical male and female students here. It imitates a given number and likewise checks where
males are 91 years old and females are 109 years old.
Statistics
Ice cream Flavor
N Valid 200
Missing 0
Mean 1.82
Median 2.00

After evaluating the vertical fact and even display, it is well checked that the average
ratio hits 1.82, which pushes the typical absolute value of the factor under check. It is reported
that quite a few Xueba choose strawberry flavour instead of chocolate discussion. In the middle
of the query above it shows the middle value of the information. It can be said that different
types of central values do not occur between similar connecting factors (Naseer and et.al., 2021).
Outcomes and consequences
From the results of the above typical information, it is well accepted that a large number
of researchers chose the vanilla flavour of frozen yogurt. By assessing the level of
comprehension, it can really accept that this is a roughly 200 students are assigned to the
preliminary aspect. One might say that this is almost at the level of men and women in the
preliminary figures. It included 91 men and 109 women. In addition to that, it can be found that a
large number of hopefuls who are substitute students decide to eat vanilla-flavoured frozen
yogurt. Classification focuses on what is said about observational comments, determining the
salience of information. A given review is also known as a departmental survey.
Argument
Reflect various considerations by persuading appropriate details, such as common
information eviction and text evacuation methods that can be used in an organization. These
strategies are thorough in thoughtful detail, social activities, instructions, and more. Different
procedures support well-reflected details for the assessment and identify useful methods under
which relevant nuances and information can be extracted. From the given situation, 200
candidates who are students of the school are selected to take the test. This acknowledges
concerns about breaking down factors and providing similar details, which are important to
organisational bosses (Rauch, Spena and Matt, 2019).
Here are a few different types of good and bad marks for utilizing SPSS and successful
bookkeeping tables that lead to a proper practical outline and current conversation. This allows
the boss of the association to conduct a dynamic survey in the contractor market and, on this
basis, be proficient in discerning whether execution is achievable.

Merits and Demerits of using SPSS
Merits Demerits
Fluctuations in input capacity can be achieved
by using SPSS.
SPSS instruments cannot perform all
achievable measurable loops.
Information recording and planning
capabilities are different strengths used by
SPSS (Rjab and Mellouli, 2018).
The storage default for SPSS archives is
programming points, so it is not ready to move
to individuals without accounting table
programming.
Improve administrative information. The most
fundamental part of any information
investigation is the underlying information
channel. Assuming you enter information
incorrectly, you will not be able to choose to
investigate it properly. Although you have a
wide selection of information sections, it is
often the ideal decision to enter information
into IBM SPSS.
A significant obstacle to SPSS is that it cannot
be used to examine extremely large sets of
information. Scientists often collect large
amounts of information in the fields of
medicine and nursing, so in these fields,
experts mostly use SAS rather than SPSS to
break down clinical information.
IBM SPSS provides a basic calculation table
design for information channels that is intuitive
and easy to use. What's more, IBM SPSS
provides a wide range of information
documents (especially famous people), which
will help you to ensure the consistency of
information channels.
The SPSS graphical user interface (GUI) is
written in Java. It is mainly used for intuitive
and measurable analysis. R is open source free
programming, where the R people make
programming updates very quickly adding new
libraries.
Merits and Demerits of Excel
Merits Demerits
Definitions of equations and intents are done
using Excel to organize the existence.
Controlled and safe unattended stops in
difficult situations with Excel.
The basic test for using successfully saved
information and materials is to use the
The inability of successful bookkeeping table
programming to do anything about extortion or

presence of a successful permission. unethical behaviour masks another mistake in
using success (Roy and et.al., 2018).
The incredible thing of the bookkeeping table
is that the program does all the math for the
client. When an equation is formed and the
program has a fixed order, complex estimation
can easily calculate the connection information
that has been entered.
Calculation tables are not so secure, so more
serious is information devaluation or data
clutter. Records containing sensitive monetary
data may not be protected by programmers,
regardless of password security.
Conclusion
As can be seen from the above report, school students who took the test had an individual
meaning in their choice of frozen yogurt flavour and were therefore genuinely investigated. This
also includes tracking appropriate information related to the determination of the results.

References
Books and Journals
Jain, H.M. and Rana, Y.P., 2020. Techno-Commercial Aspects of Space-Based Startups
Ecosystem in India. In Advances in Small Satellite Technologies (pp. 475-489).
Springer, Singapore.
Kouziokas, G.N., 2020. SVM kernel based on particle swarm optimized vector and Bayesian
optimized SVM in atmospheric particulate matter forecasting. Applied Soft
Computing, 93, p.106410.
Naseer, A. and et.al., 2021. Real-time analytics, incident response process agility and enterprise
cybersecurity performance: A contingent resource-based analysis. International
Journal of Information Management, 59, p.102334.
Rauch, E., Spena, P.R. and Matt, D.T., 2019. Axiomatic design guidelines for the design of
flexible and agile manufacturing and assembly systems for SMEs. International
Journal on Interactive Design and Manufacturing (IJIDeM), 13(1), pp.1-22.
Rjab, A.B. and Mellouli, S., 2018, May. Smart cities in the era of artificial intelligence and
internet of things: literature review from 1990 to 2017. In Proceedings of the 19th
Annual International Conference on Digital Government Research: Governance in
the Data Age (pp. 1-10).
Roy, D.S. and et.al., 2018. A context-aware fog enabled scheme for real-time cross-vertical IoT
applications. IEEE Internet of Things Journal, 6(2), pp.2400-2412.
Schmitt, P.A., 2019. Translation 4.0–Evolution, Revolution, Innovation or Disruption?. Lebende
Sprachen, 64(2), pp.193-229.

Appendix
Agglomeration Schedule
Stage Cluster Combined Coefficients Stage Cluster First Appears Next Stage
Cluster 1 Cluster 2 Cluster 1 Cluster 2
1 198 199 .000 0 0 2
2 2 198 .000 0 1 4
3 196 197 .000 0 0 4
4 2 196 .000 2 3 6
5 193 195 .000 0 0 6
6 2 193 .000 4 5 8
7 187 188 .000 0 0 8
8 2 187 .000 6 7 10
9 182 184 .000 0 0 10
10 2 182 .000 8 9 12
11 178 181 .000 0 0 12
12 2 178 .000 10 11 14
13 172 177 .000 0 0 14
14 2 172 .000 12 13 16
15 167 169 .000 0 0 16
16 2 167 .000 14 15 18
17 162 165 .000 0 0 18
18 2 162 .000 16 17 20
19 158 159 .000 0 0 20

20 2 158 .000 18 19 22
21 156 157 .000 0 0 22
22 2 156 .000 20 21 24
23 154 155 .000 0 0 24
24 2 154 .000 22 23 26
25 148 153 .000 0 0 26
26 2 148 .000 24 25 28
27 145 147 .000 0 0 28
28 2 145 .000 26 27 30
29 143 144 .000 0 0 30
30 2 143 .000 28 29 32
31 139 140 .000 0 0 32
32 2 139 .000 30 31 34
33 137 138 .000 0 0 34
34 2 137 .000 32 33 36
35 133 134 .000 0 0 36
36 2 133 .000 34 35 38
37 128 131 .000 0 0 38
38 2 128 .000 36 37 40
39 124 127 .000 0 0 40
40 2 124 .000 38 39 42
41 122 123 .000 0 0 42
42 2 122 .000 40 41 44
43 111 116 .000 0 0 44
44 2 111 .000 42 43 46
45 105 106 .000 0 0 46
46 2 105 .000 44 45 47
47 2 97 .000 46 0 94
48 89 91 .000 0 0 49
49 5 89 .000 0 48 51
50 83 85 .000 0 0 51
51 5 83 .000 49 50 53
52 75 79 .000 0 0 53
53 5 75 .000 51 52 55
54 73 74 .000 0 0 55
55 5 73 .000 53 54 57
56 70 71 .000 0 0 57
57 5 70 .000 55 56 59
58 66 67 .000 0 0 59
59 5 66 .000 57 58 61

60 61 64 .000 0 0 61
61 5 61 .000 59 60 63
62 59 60 .000 0 0 63
63 5 59 .000 61 62 65
64 55 58 .000 0 0 65
65 5 55 .000 63 64 67
66 53 54 .000 0 0 67
67 5 53 .000 65 66 69
68 50 51 .000 0 0 69
69 5 50 .000 67 68 71
70 48 49 .000 0 0 71
71 5 48 .000 69 70 73
72 42 43 .000 0 0 73
73 5 42 .000 71 72 75
74 40 41 .000 0 0 75
75 5 40 .000 73 74 77
76 34 37 .000 0 0 77
77 5 34 .000 75 76 79
78 28 31 .000 0 0 79
79 5 28 .000 77 78 81
80 25 26 .000 0 0 81
81 5 25 .000 79 80 83
82 22 23 .000 0 0 83
83 5 22 .000 81 82 85
84 20 21 .000 0 0 85
85 5 20 .000 83 84 87
86 12 18 .000 0 0 87
87 5 12 .000 85 86 89
88 10 11 .000 0 0 89
89 5 10 .000 87 88 91
90 8 9 .000 0 0 91
91 5 8 .000 89 90 93
92 6 7 .000 0 0 93
93 5 6 .000 91 92 94
94 2 5 1.000 47 93 0