Summer Internship Project Report | The Fundamental of Digital Marketing | Lov...Kodexhub
Summer Internship Project Report on ✨The Fundamental of Digital Marketing ✨ With 6% Plagiarism | MRX.
Submitted in Lovely Professional University Jalandhar, Punjab.
✨ 9 October 2021 ✨
This Report Contain are these Things:-
Abstract
Introduction
Why Digital Marketing
Online Marketing
Website
Site design improvement:
Google Search Console/Google website admin
Slithering and Indexing
Web-based Media Marketing:
Web-based Media Marketers' Platform Usage Trends
Google Analytics
AdWords
AdSense
Pay-per-click (PPC)
How the PPC Model Works
Marketing is Future
Project on Facebook Ads
Reference
Pfizer office of the future case study Mohamed Zaid
Pfizer office of the future case study
Structure Implications
Role of organizational structure in organization effectiveness and efficiency
Pfizer CSR
SWOT
Summer Internship Project Report | The Fundamental of Digital Marketing | Lov...Kodexhub
Summer Internship Project Report on ✨The Fundamental of Digital Marketing ✨ With 6% Plagiarism | MRX.
Submitted in Lovely Professional University Jalandhar, Punjab.
✨ 9 October 2021 ✨
This Report Contain are these Things:-
Abstract
Introduction
Why Digital Marketing
Online Marketing
Website
Site design improvement:
Google Search Console/Google website admin
Slithering and Indexing
Web-based Media Marketing:
Web-based Media Marketers' Platform Usage Trends
Google Analytics
AdWords
AdSense
Pay-per-click (PPC)
How the PPC Model Works
Marketing is Future
Project on Facebook Ads
Reference
Pfizer office of the future case study Mohamed Zaid
Pfizer office of the future case study
Structure Implications
Role of organizational structure in organization effectiveness and efficiency
Pfizer CSR
SWOT
Using social media strategy in building the corporate brand image is a route a lot of people imagine they know - what with the number of influencers, opinion leaders, trend watchers, and spotters laying claims to so-called virile strategy which generate likes, impressions and conversations. However, that is not all there is to capturing corporate essence in an era of great cynicism. Using Social Media as a route to build corporate stature requires the need to develop and manage strategic partnerships, the monitoring of trends and applications of knowledge from trends in building conversations while measuring the impact of efforts in order to intensify or discontinue a course of action. Beyond this, this presentation attempts a historical perspective of the social media phenomenon as well as platform possibilities looking at the Nigerian context.
Public Relations Management Session 5 Hr And PrMoksh Juneja
Session on public relations, and the over lap between Human Resource Management and Public relations management, Employee relations as an integral part of PR
Online Retailer Digital Marketing Strategy ExampleMike Ncube
This digital marketing strategy for an accessories retailer covers the main areas of marketing audit, analysis, objectives, target markets, competitors, promotions, products and more.
Use it as a guide for your own digital marketing strategy and it will help you achieve online marketing success.
Visit my site www.mikencube.co.uk for more digital marketing resources
Dear student, Cheap Assignment Help, an online tutoring company, provides students with a wide range of online assignment help services for students studying in classes K-12, and College or university. The Expert team of professional online assignment help tutors at Cheap Assignment Help .COM provides a wide range of help with assignments through services such as college assignment help, university assignment help, homework assignment help, email assignment help and online assignment help. Our expert team consists of passionate and professional assignment help tutors, having masters and PhD degrees from the best universities of the world, from different countries like Australia, United Kingdom, United States, Canada, UAE and many more who give the best quality and plagiarism free answers of the assignment help questions submitted by students, on sharp deadline. Cheap Assignment Help .COM tutors are available 24x7 to provide assignment help in diverse fields - Math, Chemistry, Physics, Writing, Thesis, Essay, Accounting, Finance, Data Analysis, Case Studies, Term Papers, and Projects etc. We also provide assistance to the problems in programming languages such as C/C++, Java, Python, Matlab, .Net, Engineering assignment help and Finance assignment help. The expert team of certified online tutors in diverse fields at Cheap Assignment Help .COM available around the clock (24x7) to provide live help to students with their assignment and questions. We have also excelled in providing E-education with latest web technology. The Students can communicate with our online assignment tutors using voice, video and an interactive white board. We help students in solving their problems, assignments, tests and in study plans. You will feel like you are learning from a highly skilled online tutor in person just like in classroom teaching. You can see what the tutor is writing, and at the same time you can ask the questions which arise in your mind. You only need a PC with Internet connection or a Laptop with Wi-Fi Internet access. We provide live online tutoring which can be accessed at anytime and anywhere according to student’s convenience. We have tutors in every subject such as Math, Chemistry, Biology, Physics and English whatever be the school level. Our college and university level tutors provide engineering online tutoring in areas such as Computer Science, Electrical and Electronics engineering, Mechanical engineering and Chemical engineering. Regards http://www.cheapassignmenthelp.com/ http://www.cheapassignmenthelp.co.uk/
The Evolution of Corporate CommunicationsKenny Ong
ABF Annual Corporate Communications and Public Relations Conference
The Evolution Of Corporate Communications
• The evolving role of corporate communications and PR
• Business strategy and corporate communications
• Technology and corporate communications
• Corporate communications as value creator
We're committed to providing 100% plagiarism free academic assignments i.e. Course work, Homework assignments, thesis, dissertations, Oxford Brookes (OBU) BSC Hons Applied Accounting ACCA Thesis (RAP, SLS, PPT), Essays and Term/Research papers etc. Pay in instalments and that too after you receive the first draft. Please visit and like our Facebook page www.facebook.com/assignmentwritingservices/ and website www.ghostwritingmania.com to avail our special discount packages. You can also add me on Skype ghostwritingmania or email me ghostwritingmania@yahoo.com for any further discussion...Looking forward to working together on long term.
Using social media strategy in building the corporate brand image is a route a lot of people imagine they know - what with the number of influencers, opinion leaders, trend watchers, and spotters laying claims to so-called virile strategy which generate likes, impressions and conversations. However, that is not all there is to capturing corporate essence in an era of great cynicism. Using Social Media as a route to build corporate stature requires the need to develop and manage strategic partnerships, the monitoring of trends and applications of knowledge from trends in building conversations while measuring the impact of efforts in order to intensify or discontinue a course of action. Beyond this, this presentation attempts a historical perspective of the social media phenomenon as well as platform possibilities looking at the Nigerian context.
Public Relations Management Session 5 Hr And PrMoksh Juneja
Session on public relations, and the over lap between Human Resource Management and Public relations management, Employee relations as an integral part of PR
Online Retailer Digital Marketing Strategy ExampleMike Ncube
This digital marketing strategy for an accessories retailer covers the main areas of marketing audit, analysis, objectives, target markets, competitors, promotions, products and more.
Use it as a guide for your own digital marketing strategy and it will help you achieve online marketing success.
Visit my site www.mikencube.co.uk for more digital marketing resources
Dear student, Cheap Assignment Help, an online tutoring company, provides students with a wide range of online assignment help services for students studying in classes K-12, and College or university. The Expert team of professional online assignment help tutors at Cheap Assignment Help .COM provides a wide range of help with assignments through services such as college assignment help, university assignment help, homework assignment help, email assignment help and online assignment help. Our expert team consists of passionate and professional assignment help tutors, having masters and PhD degrees from the best universities of the world, from different countries like Australia, United Kingdom, United States, Canada, UAE and many more who give the best quality and plagiarism free answers of the assignment help questions submitted by students, on sharp deadline. Cheap Assignment Help .COM tutors are available 24x7 to provide assignment help in diverse fields - Math, Chemistry, Physics, Writing, Thesis, Essay, Accounting, Finance, Data Analysis, Case Studies, Term Papers, and Projects etc. We also provide assistance to the problems in programming languages such as C/C++, Java, Python, Matlab, .Net, Engineering assignment help and Finance assignment help. The expert team of certified online tutors in diverse fields at Cheap Assignment Help .COM available around the clock (24x7) to provide live help to students with their assignment and questions. We have also excelled in providing E-education with latest web technology. The Students can communicate with our online assignment tutors using voice, video and an interactive white board. We help students in solving their problems, assignments, tests and in study plans. You will feel like you are learning from a highly skilled online tutor in person just like in classroom teaching. You can see what the tutor is writing, and at the same time you can ask the questions which arise in your mind. You only need a PC with Internet connection or a Laptop with Wi-Fi Internet access. We provide live online tutoring which can be accessed at anytime and anywhere according to student’s convenience. We have tutors in every subject such as Math, Chemistry, Biology, Physics and English whatever be the school level. Our college and university level tutors provide engineering online tutoring in areas such as Computer Science, Electrical and Electronics engineering, Mechanical engineering and Chemical engineering. Regards http://www.cheapassignmenthelp.com/ http://www.cheapassignmenthelp.co.uk/
The Evolution of Corporate CommunicationsKenny Ong
ABF Annual Corporate Communications and Public Relations Conference
The Evolution Of Corporate Communications
• The evolving role of corporate communications and PR
• Business strategy and corporate communications
• Technology and corporate communications
• Corporate communications as value creator
We're committed to providing 100% plagiarism free academic assignments i.e. Course work, Homework assignments, thesis, dissertations, Oxford Brookes (OBU) BSC Hons Applied Accounting ACCA Thesis (RAP, SLS, PPT), Essays and Term/Research papers etc. Pay in instalments and that too after you receive the first draft. Please visit and like our Facebook page www.facebook.com/assignmentwritingservices/ and website www.ghostwritingmania.com to avail our special discount packages. You can also add me on Skype ghostwritingmania or email me ghostwritingmania@yahoo.com for any further discussion...Looking forward to working together on long term.
Route development is always governed by two main factors, Supply and Demand, Supply in terms of capacity offered i.e Seats, Demand in terms of Traffic Demand i.e Passengers.
So Airlines are concerned for route development, but if there is no business for certain routes/city, there will be no operation to that city/airport. While airports acts as facilitators for airlines to encourage them to operates for new routes or increase their frequencies. also airports offered a good service at a most convenient cost for airlines. That why each airport in the world is always concerned about the route development, they are publishing the airlines traffic/statistics on monthly bases, exploring the future business potential of existing/operating routes.
I completed this project as part of my internship capstone at Learnbay. The task was to predict the flight fares for multiple flights in India. Visualizing the data helped me find trends and correlations between the independent and target variables. In the following step, I developed a model to predict the price.
Remarks09222018 - Bold section headings enhance the works o.docxcarlt4
Remarks
09/22/2018 - Bold section headings enhance the work's overall organization. Recurring Professional Communication (Articulation) concerns are evident with parts of speech, varying issues such as verb form(s), subject-verb agreement, and sentence fluency, varying issues such as run-on sentences, comma splices. These writing concerns diminish the clarity of the response.
10/7/18 - Financial institutions' use of data is adequately presented as a real-world business situation, yet the summary is lacking details particularly how the business situation can be addressed by data collection and analysis. One specific question or scenario for data analysis could not be located.
For instruction on describing the relevant data collected, please revisit the section titled “The Case for Quantitative Analysis” in the study plan for this course by clicking on the link located in the top left in this rubric item’s name,“B1. Summary of Data.”
9/22/18 - The submission includes an adequate summary of a real-world business situation regarding financial institutions. The provided detail is insufficient as it is unclear how this business situation can be addressed by collecting and analyzing a set of data, and more specifically a research question is not clearly identified.
10/7/18 - The submission provides financial data as relevant data for the analysis. It is unclear whether the described data relates to a relevant business situation. Please review this response for alignment to the business situation once aspect A has been revised
9/22/18 - The submission provides a limited discussion on financial data as relevant data for the analysis. It is unclear whether the described data relates to a relevant business situation. Please review this response for alignment to the business situation once aspect A has been revised.
10/7/18 - The work provides graphics of processes and generalized financial information as a graphical display of the data collected. It is not clear whether this graphical display is appropriate,as the relevancy of the data collected to the business situation could not be verified. Please review the response to this aspect after revising the data collected in aspect B1.
9/22/18 - Two bar graphs are provided as a graphical display. It is unclear whether the provided graphical display is appropriate, as the description of the data collected in aspect B1 is insufficient.
10/7/18 - The submission describes several common techniques in the finance realm as the data analysis techniques. It is not clear whether this is an appropriate technique to be used to analyze the collected data. Please review this response for alignment to the data to be collected once aspect B1 has been revised
9/22/18 - Numerous possible techniques are described. However, it is unclear whether any of these techniques is appropriate for data that is relevant to the business situation.
10/7/18 - The submission provides several examples of how data could be used in fina.
Predicting Air Transport Industry - 2018 Mohammed Awad
Predicting Air Transport Industry based two input parameters - RPKs and ASKs, then using their forecasted results to predicted the Air Transport Industry Performance i.e Load Factor which is simply RPKs/ASKs
Airlines are concerned for route development, but if there is no business for certain routes/city, there will be no operation to that city/airport. While airports acts as facilitators for airlines to encourage them to operates for new routes or increase their frequencies. also airports offered a good service at a most convenient cost for airlines. That is why each airport in the world is always concerned about the route development, they are publishing the airlines traffic/statistics on monthly bases, exploring the future business potential of existing/operating routes.
Steps and Challenges in Analyzing Real Sensor Data from a Productive Press Sh...IJCI JOURNAL
This paper highlights the significance of AI-powered maintenance strategies in modern industry for operational optimization and reduced downtime. It emphasizes the crucial role of sensor data analysis in identifying anomalies and predicting failures. The research specifically examines sensor data from an automotive press shop, addressing questions related to data selection, collection challenges, and knowledge generation. By utilizing unsupervised learning on compressed air data from a press line, the study identifies patterns, anomalies, and correlations. The results offer insights into the potential for implementing an effective predictive maintenance strategy. Additionally, a systematic literature review underscores the importance of data analysis in production systems, particularly in the context of maintenance.
Wsc 2015 modeling customer demand in print service environments usingSudhendu Rai
For simulation modeling, what-if analysis and optimization studies of many service and production operations, demand models that are reliable statistical representations of current and future operating conditions are required. Current simulation tools allow demand modeling using known closed-form statistical distributions or raw demand data collected from operations. In many instances, demand data cannot be described by known closed-form statistical distributions and the raw data collected from operations is not representative of future demand. This paper describes an approach to demand modeling where historical demand data collected over a finite time period is combined with user-input using two-tier bootstrapping to produce synthetic demand data that preserves the statistical distribution of the original data but has overall metrics such as volume, workflow mix and individual task and job sizes that represent projected future state scenarios. When the customer demand data follows highly non-normal distributions, a modified procedure is presented.
Predicting Aviation Industry Performance (L/F) - 2019Mohammed Awad
Developing targets is one of the major issues in the aviation industry. In the recent time, many aviation sources predict different figures, based on their own analysis, and sight for the global aviation market. The dilemma, that, there is no basic rules for the predictors, especially aircrafts manufacture companies.
These articles published in CAMA, having the following titles 1- Accuracy of Forecasting Model (Coefficient of Determinations vs. Signal Tracking ) 2- Head To Head Analysis, A320 Family VS B737NG (Value Analysis) 3- Forecasting by Objectives ( Airport Forecasting ).
Benchmarking data mining approaches for traveler segmentation IJECEIAES
The purpose of this study is proposing a hybrid data mining solution for traveler segmentation in tourism domain which can be used for planning user-oriented trips, arranging travel campaigns or similar services. Data set used in this work have been provided by a travel agency which contains flight and hotel bookings of travelers. Initially, the data set was prepared for running data mining algorithms. Then, various machine learning algorithms were benchmarked for performing accurate traveler segmentation and prediction tasks. Fuzzy C-means and X-means algorithms were applied for clustering user data. J48 and multilayer perceptron (MLP) algorithms were applied for classifying instances based on segmented user data. According to the findings of this study, J48 has the most effective classification results when applied on the data set which is clustered with X-means algorithm. The proposed hybrid data mining solution can be used by travel agencies to plan trip campaigns for similar travelers.
Business communication is the process of communicating with the employees and the organisation. The implementation of the business communication strategies helps to build the communication skills in the employees. In this report the impact, barriers, and solutions to barriers are discussed which help to understand the overall concept of the business communication. For betterment of the organisations improvement of the communication skills is necessary. The effective communication is the management of the employees which help in the management of the employee’s behaviour. Analysis of business communication is essentially effective in determining the potential in professional aspects as well as evaluating personal skills for improvement.
Retail is the kind of market which is the last stop for the supply chain from where customers can access the good and services. Retail market generally purchases the goods from the manufacturer or the middlemen refer to as the Wholesalers. Wholesalers collect the products from the manufacturers worldwide and supply the goods and service to the retailers. So, retailers are the intermediate layer in the supply chain who connects the products from the manufacturer with the targeted customers. Retail market may be offline or online. However, for decades, the online retail market like Flipkart, Amazon etc are grooming faster compared to the offline retail market. The primary reason is the feasibility to the customer as they can view the product from the website by sitting at home and can choose for their purchase. Even they can order for their desired products without going to the physical market. It means such market required the intelligence to attract the customers so that they will buy the product from their market. Generally, customers use to buy their products from such a market where they can find good products, attractive offers and useful recommendations. On the other hand, retailers should keep their inventory management smarter by employing suitable technology so that the supply will be uniform. As this is the era of digital business, retail marketing uses the technology like Data Analytics with the Internet of Things to maintain the inventory, sophistical approach towards checkout system by emphasizing the visibility of the inventory system.
3.0 Project 2_ Developing My Brand Identity Kit.pptxtanyjahb
A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
[Note: This is a partial preview. To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
Sustainability has become an increasingly critical topic as the world recognizes the need to protect our planet and its resources for future generations. Sustainability means meeting our current needs without compromising the ability of future generations to meet theirs. It involves long-term planning and consideration of the consequences of our actions. The goal is to create strategies that ensure the long-term viability of People, Planet, and Profit.
Leading companies such as Nike, Toyota, and Siemens are prioritizing sustainable innovation in their business models, setting an example for others to follow. In this Sustainability training presentation, you will learn key concepts, principles, and practices of sustainability applicable across industries. This training aims to create awareness and educate employees, senior executives, consultants, and other key stakeholders, including investors, policymakers, and supply chain partners, on the importance and implementation of sustainability.
LEARNING OBJECTIVES
1. Develop a comprehensive understanding of the fundamental principles and concepts that form the foundation of sustainability within corporate environments.
2. Explore the sustainability implementation model, focusing on effective measures and reporting strategies to track and communicate sustainability efforts.
3. Identify and define best practices and critical success factors essential for achieving sustainability goals within organizations.
CONTENTS
1. Introduction and Key Concepts of Sustainability
2. Principles and Practices of Sustainability
3. Measures and Reporting in Sustainability
4. Sustainability Implementation & Best Practices
To download the complete presentation, visit: https://www.oeconsulting.com.sg/training-presentations
VAT Registration Outlined In UAE: Benefits and Requirementsuae taxgpt
Vat Registration is a legal obligation for businesses meeting the threshold requirement, helping companies avoid fines and ramifications. Contact now!
https://viralsocialtrends.com/vat-registration-outlined-in-uae/
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
What is the TDS Return Filing Due Date for FY 2024-25.pdfseoforlegalpillers
It is crucial for the taxpayers to understand about the TDS Return Filing Due Date, so that they can fulfill your TDS obligations efficiently. Taxpayers can avoid penalties by sticking to the deadlines and by accurate filing of TDS. Timely filing of TDS will make sure about the availability of tax credits. You can also seek the professional guidance of experts like Legal Pillers for timely filing of the TDS Return.
What are the main advantages of using HR recruiter services.pdfHumanResourceDimensi1
HR recruiter services offer top talents to companies according to their specific needs. They handle all recruitment tasks from job posting to onboarding and help companies concentrate on their business growth. With their expertise and years of experience, they streamline the hiring process and save time and resources for the company.
RMD24 | Retail media: hoe zet je dit in als je geen AH of Unilever bent? Heid...BBPMedia1
Grote partijen zijn al een tijdje onderweg met retail media. Ondertussen worden in dit domein ook de kansen zichtbaar voor andere spelers in de markt. Maar met die kansen ontstaan ook vragen: Zelf retail media worden of erop adverteren? In welke fase van de funnel past het en hoe integreer je het in een mediaplan? Wat is nu precies het verschil met marketplaces en Programmatic ads? In dit half uur beslechten we de dilemma's en krijg je antwoorden op wanneer het voor jou tijd is om de volgende stap te zetten.
Improving profitability for small businessBen Wann
In this comprehensive presentation, we will explore strategies and practical tips for enhancing profitability in small businesses. Tailored to meet the unique challenges faced by small enterprises, this session covers various aspects that directly impact the bottom line. Attendees will learn how to optimize operational efficiency, manage expenses, and increase revenue through innovative marketing and customer engagement techniques.
LA HUG - Video Testimonials with Chynna Morgan - June 2024Lital Barkan
Have you ever heard that user-generated content or video testimonials can take your brand to the next level? We will explore how you can effectively use video testimonials to leverage and boost your sales, content strategy, and increase your CRM data.🤯
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2. How to leverage your testimonials to boost your sales 💲
3. How you can capture more CRM data to understand your audience better through video testimonials. 📊
Premium MEAN Stack Development Solutions for Modern BusinessesSynapseIndia
Stay ahead of the curve with our premium MEAN Stack Development Solutions. Our expert developers utilize MongoDB, Express.js, AngularJS, and Node.js to create modern and responsive web applications. Trust us for cutting-edge solutions that drive your business growth and success.
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Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
2. Executive Summery
Forecasting is the necessary issue in business for better prediction of the available data over
years. Every business needs the forecasting so that they can plan for the future. There are
different prediction strategies are available in the statistics through which the better prediction
can be done. If the prediction for the business is strong enough, the forecasting can be done
with more perfection and thus the growth of the business will be better. So, in this paper, the
better prediction is applied for the prediction and forecasting of the Air Passenger data so that
with the forecasting, the business model can be prepared in better way. As the analysis is
corresponding to the air passengers, so the model will be helpful to the airlines industry to
check the passenger level per year and as per the prediction they can make all kinds of
arrangements for their clients. So, on the way to achieve the success, the data analysis is done
using R Programming and the outcomes of the predictions are discussed in the respective
sections.
3. Table of Contents
Introduction................................................................................................................................ 4
Data Overview............................................................................................................................ 4
Exploratory Data Analysis..........................................................................................................5
Reading Data .......................................................................................................................... 5
Summary of Data.................................................................................................................... 6
Raw Data Overview................................................................................................................ 7
Conversion of the data to Time Series..................................................................................... 8
Decompose Data...................................................................................................................... 9
Decompose........................................................................................................................... 9
Trend................................................................................................................................. 11
Seasonal Components........................................................................................................ 11
Random Components ........................................................................................................ 11
Predictive Model................................................................................................................... 11
ARIMA.............................................................................................................................. 11
Linear Regression.............................................................................................................. 12
Comparison of Models....................................................................................................... 13
Recommendation...................................................................................................................... 13
Conclusion................................................................................................................................ 13
References................................................................................................................................. 15
4. Introduction
Airlines service is the most demanding in the world as the passenger can get the comfort while
their journey and within very short time, they can reach their destination. Apart from the
airways, there are others ways are available like the waterways and the roadways. Those for
the national journey by if someone wish to travel beyond the nation, the airways are most
feasible as it is through the air and there is no interruption (Mao & Xiao, 2019). So, for this
kind of journey, the passengers like to travel through air and thus the industries are grown for
that purpose. In this paper, the data regarding to the airlines passengers is taken as the reference
upon which the analysis will be done to make the predictive model. Different models are
applied on the data and then by checking the comparison, the best model will be accepted for
forecasting purpose (Y. Guo, 2018).
Data Overview
The data for the analysis is collected from the repository which contains two attributes namely,
Month and passengers. With a quick observation of the data, it can be found that the data
containing the records of the passengers travel in the range between 1949 to 1960. Within that
range, the number of the passengers that are travelled are provided in the dataset (Y. Hirata,
2017). With a concurrent analysis of the data it can be seen that in the primary stages, the
passengers are lower and in the last state of the data containing high passengers. The data is
shown below:
Table-1: High Numbers of passengers
Top 10-Months with High Passengers
Month #Passengers
1960-07 622
1960-08 606
1959-08 559
1959-07 548
1960-06 535
1960-09 508
1958-08 505
1958-07 491
1959-06 472
1960-05 472
Table-2: Low Numbers of Passengers
5. Least 10-Months with High Passengers
Month #Passengers
1949-11 104
1949-01 112
1950-11 114
1950-01 115
1949-02 118
1949-12 118
1949-10 119
1949-05 121
1950-05 125
1950-02 126
So, it can be seen that the number of passengers is continuously increasing. In the next section
of the paper, the Exploratory data analysis will be done through which the forecasting of the
data will be made visible (J. M. Amigó, 2016).
Exploratory Data Analysis
Exploratory analysis basically explores the statistical issue within a data. The analysis is well
known the field of statistics and data analytics and hence is used her to explore the insight of
the data (Hu, 2018). Hence the data is collected and the analysis is done using the R
Programming Language. R programming is specific for the analysis of the data and to explore
the statistics within the data and so this is used here for the Exploratory Data Analysis of the
Air Passenger data. The subsections are dealing with the coding overview and the description
of the outcomes (F. Karim, 2018).
Reading Data
Primarily the data is fetched from the device location and the data is read to check the
consistency of the read operation of data.
Fig-1: Reading and checking the data head
6. Hence the data is read and the data is checked using the head function which shows the ve rows
of the data. The outcome of the code section is as follows:
Fig-2: Data Checking
So, here the data is checked.
Summary of Data
To check the summery of the data, firs the required packages are imported so that the methods
under those packages can be used for the Exploratory Data Analysis.
Fig-3: Importing necessary packages
After importing the packages, the summery of the data is checked. This can be checked using
the built-in method summery (). The code snippet is shown below:
7. Fig-4: Checking Summary
After checking the summery, the statistical issues of the data will be obtained as the outcome.
The outcome is shown below:
Fig-5: Summary of the Data
The summary shows the statistical issues of the data. Seen that within that data, the minimum
number of passengers arrived are 104 in the month of January, 1949 and the maximum number
of passengers arrived are 622 in the month of June, 1960. The average number of passengers
arrived use to travel is obtained as 280 as mean and with median it is 265.
Raw Data Overview
In this sub section the raw data overview is observed. The raw data is the data frame and the
plot function are applied to check the overview of the data (M. Fukino, 2016). The code section
is shown below:
8. Fig-6: Checking Raw Data
The outcome of the code is shored in the local directory and that is shown below:
Fig-7: Outcome of the Passenger ay data
The outcome of the data shows the trend of the passengers and hence the output is plotted. For
the convenience of the data understanding, the NaN is checked because if any NaN value will
persist in the data, it cannot be applied in a model and the analysis cannot be one using any
statistical model (Li, 2018).
Conversion of the data to Time Series
The primary objective is to do the analysis of the data for passengers with respect to time. So,
for this case, Time Series data is required. Now, first the type of the data will be checked and
if found that it is not a time series data, it will be converted to time series data (Hu, 2018). The
conde snippet for these actions are as follows:
9. (a) (b)
(c)
Fig-8: Conversion of data frame to time series
As shown in the figure, primarily, that was a data frame on which the time series analysis
cannot be done (Li, 2018). So, the data frame is converted to the Time Series so that the
required operations will be performed.
Decompose Data
In this subsection, the data that is now the time series data will be decomposed to get the trend
of the passengers, to get the seasonal components and also to get the random components of
the data. All ae described below after decomposing it (Mao & Xiao, 2019).
Decompose
Decompose is the operation through which different components of the data can be obtained.
Hence the decomposition is shown below:
10. Fig-9: Decomposing Data
With the decomposition of the data using decompose() method, three components are found
and those are defined below with the output plot as defined in the code section.
Fig-10: Components of Data after decomposing
11. Trend
The trend plot is shown in fig-10 describe the trend of the passenger for the use of the airways
(Y. Guo, 2018). As the trend is shown it can be said that the number of passengers is increasing
the year is progressing which means the passenger number will seem to be increased in future
years.
Seasonal Components
The season effect of the data reflects the insight of the data over a period. The plotting is already
shown in Fig-10 which describe the fact that the ups and downs of the passenger with the
progress of year for airlines (Li, 2018).
Random Components
This is the third component of the time series data. Basically, this is the random plot by taking
random data from the original time series for Air Passenger.
Predictive Model
The time series data shows the number of passengers with respect to the given time. Hence, the
objective, as discussed, is to predict the airlines passenger flow for the future year which are
beyond 1960. This required the predictive analysis and the outcome should be obtained in terms
of future trend (H. Guan, 2017). In this subsection, the prediction is done with help of ARIMA
model and Linear Regression model to predict the traffic passenger flow for the airlines which
will be helpful to predict for the business also. Now, the determination of the best model in
between these two can be done using the valuation of the Root Mean Square Error and the other
error can also be the parameters but for this case, the RMSE is considered (Y. Guo, 2018).
ARIMA
The ARIMA Model is dine using the method auto.arima which transform the time series data
to corresponding time ARIMA model and hence produce the Errors that are obtained by this
model. The code is shown below:
Fig-11: ARIMA Model
Using the ARIMA Model the model error is been found out which will be helpful to determine
the model for the future prediction. Hence, the error related to the ARIMA model is shows
below:
12. Fig-12: Accuracy of ARIMA Model
So, for the forecasting purpose, the ARIMA model RMSE is obtained to be 9.888653. Hence,
this value will be compared to the value of the RMSE of Linear Regression to obtain the high
accurate model. The entire error report to compute the accuracy is:
ME RMSE MAE MPE MAPE MASE ACF1
Training set 0.5256045 9.888653 7.475767 0.1057234 2.870315 0.2437531 0.01
120024
Linear Regression
Linear Regression is another model to predict the trend of the passenger in this paper. Linear
regression is simply following the equation of the straight line and hence it is the simplest one
to deploy the data into model (J. M. Amigó, 2016). Linear Regression is done in this section
with the built-in method called lm. As the data-frame is converted to the time series, to check
out the trend, linear regression is applied on the time series data. The code for linear regression
is shown below:
13. Fig-13: Accuracy of Linear Regression
So, using the Linear Regression model, the RMSE is obtained by 41.57885 which is near about
4 times higher than the RMSE obtained by ARIMA model. The accuracy report of Linear
regression is as follows:
ME RMSE MAE MPE MAPE MASE
Training set 4.274398e-16 41.57885 31.26182 -1.38991 11.87438 0.3482385
Comparison of Models
So, in this section, two models are designed, one is the ARIMA model and another is by Linear
Regression. In these respective codes, the errors are found out to tally the accuracy of the model
(Y. Hirata, 2017). The model accuracy is checked by the built-in method accuracy(model) and
thus the outcome is obtained by in terms of amount of error. It means if the error is lower the
model becomes more efficient (H. Guan, 2017). The forecast will be done on the basis of the
most accurate model. The comparison table is shown below for the errors:
Model Error ME RMSE MAE MPE MAPE MASE
ARIMA 4.27E-16 41.5789 31.2618 -1.3899 11.8744 0.34824
Linear Regression 0.525605 9.88865 7.47577 0.10572 2.87032 0.24375
If the table is observed, it can be seen that most cases, ARIMA attracts lesser error compared
to the Linear Regression model. So, it can be said that, the forecasting of the future trend will
be perfect if it will be done using ARIMA Model (Li, 2018). So, in this subsection, the
forecasting is done using ARIMA Model.
Fig-14: Forecasting using ARIMA (Best fit) model
Recommendation
This analysis is based on the forecasting of the air passenger data. As it is the business issue,
the forecasting model can be applied in any predictive case like forecasting the stock market,
for traffic overviews, weather prediction and others (Hu, 2018). As the model uses the ARIMA,
so the accuracy s higher as the error rate is very low and thus it can predict with efficient
manner and forecast the actual prediction will less error.
Conclusion
In this paper, the data is collected and analysed using R programming. The main analytical
issues drawn here is the timeseries analysis that is to forecast the passenger overview and
prediction for future years so that the business perspective can assume the number of air
14. passenger will be arrived in some particular year (M. Fukino, 2016). All the code shots are
given for the better understanding of the analysis along with the screenshot of the output to
check the consistency of the analysis. Finally, the ARIMA model is chosen for its higher
accuracy and the forecasting is done on the basis of that (Y. Hirata, 2017).
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