MAIN ARTICLE
Background information
Article name: “The Fashion E-commerce market report in Vietnam”
(Fashion- Vietnam | Statista Market Forecast )
Author: Statista, Statista Global Consumer Survey
From which article: Fashion Ecommerce report 2022 - Statista
Purpose of the article
The report presents key statistics on Vietnam's eCommerce Fashion sector, encompassing Clothing, Shoes, and Bags & Accessories sold through digital channels like desktop computers and mobile devices It highlights users as individuals who have purchased at least one Fashion item in the past year.
12 months Well-known online shops for Fashion products are Asos, Zalando, and Macy's.
Survey respondents
● Survey sample distributed by gender : The percentage of female and male respondents accounted for 54,3% and 45,7% respectively
The survey sample is categorized into five primary age groups, revealing that individuals aged 25-34 constitute the largest segment at 31.9% In contrast, the age group of 55-64 years represents only 7.7%, highlighting a significant disparity where the younger demographic is four times more prevalent than the older cohort.
Methodology: Descriptive Statistics
This article focuses on data related to B2C enterprises, specifically analyzing the sales of physical goods through digital channels to private consumers, including purchases made on desktop computers and mobile devices Various forecasting techniques are employed, tailored to the behaviors of the specific market The market data is refreshed biannually to reflect any changes in market dynamics, taking into account the localized effects of the COVID-19 pandemic and the Russia/Ukraine conflict.
II/ Analysis of the technique used in the article
Descriptive statistics, specifically frequency table bar chart line chart, , and cross tabulation are applied in this article for the following purposes:
Frequency tables
Figure 1.1 Fashion Ecommerce users by gender in Vietnam
It is not surprising that women spent more on fashion products online than men, with 54.3% compared to men’s 45.7%.
Figure 1.2 Fashion Ecommerce users by age groups in Vietnam
Meanwhile, the middle-age class from 25 to 34 years old has the highest number of users among 5 age groups, with approximately 32 percent.
Bar charts
● A bar chart is often used to display frequencies
● Applications of bar charts in the article sales channels :
Syllabus Gesis Summer School 2020 C5 Applied Multiple Imputation
Economic Statistics None ôn th ố ng kê - Statistic destroyed my life
Statistic-exercise - An exercise in our 4th week of lecture
Figure 2.1 Fashion Ecommerce users by desktop or mobile groups in Vietnam
The graph illustrates the trend of survey respondents selecting either Desktop or Mobile devices for fashion product purchases from 2017 to 2027 Notably, the data indicates a consistent rise in the number of individuals opting for mobile devices to shop for fashion items over this 10-year span.
Figure 2.2 Fashion shopping methods in Vietnam
In 2017, a significant majority of customers (91.3%) preferred purchasing fashion products offline, compared to just 8.7% online Over the subsequent years, the percentage of online shoppers steadily increased, indicating a shift in the market driven by technological advancements Nevertheless, by the end of the 2027 cycle, offline shopping still accounted for double the percentage of online purchases, emphasizing that many customers still prefer to try on fashion items in person to ensure they find the right fit.
Figure 2.3 Fashion Ecommerce’s revenue in terms of 3 segments in Vietnam
Revenue from three key segments—Accessories, Apparel, and Footwear—has seen a significant increase from USD 0.57 billion to USD 2.36 billion in 2023, with projections indicating further growth to USD 3.73 billion by 2027.
Figure 2.4:Proportion of fashion product’s buyers by income
The pie chart illustrates that high-income buyers represent 40% of online fashion commodity purchasers, while both medium and low-income buyers account for 30% each.
Figure 2.5: Average revenue per user by segment
The clothing market stands out as the most profitable segment, with revenue soaring from 20 million in 2017 to 41.31 million by 2021, before experiencing a slight decline to 34.34 million in 2022, followed by a steady recovery Accessories show a similar growth pattern, while the footwear sector has maintained stability with minimal growth over the years.
● The reason of applying bar charts in this research
This study utilizes bar charts to effectively display numerical data related to various categories, enhancing the reader's comprehension of the information By employing bar charts, readers can quickly identify and compare the relative sizes of the categories, making the data more accessible and easier to understand.
Cross tabulation
Figure 3.1: Comparable estimates revenue of fashion product worldwide
The fashion market has experienced significant revenue growth over the years, rising from $0.44 billion in 2017 to an anticipated $1.25 billion by 2026, indicating a trend towards increased profitability in this sector.
Figure 3.2: Revenue of fashion e-commerce platform from 2017-2021
The data in this table shows the top company's earnings in the fashion industry
In 2021, Amazon and Walmart are projected to lead the retail market with impressive sales figures of $469.80 billion and $572.80 billion, respectively Following them is JD Company, expected to generate $108.10 billion in revenue in 2020, securing the third position The market share of other companies listed is significantly lower, ranging from $5.44 billion to $20.31 billion.
3.1 Why should cross tabulation be used in this circumstances:
Cross-tabulation simplifies data analysis by breaking down large data sets into manageable subgroups, making it easier to understand complex information This method reduces the risk of errors during examination, leading to more effective time management and clearer insights.
-In this example, there are years and companies as variables which can cause some complexity Therefore using cross tabulation can clarify data and make them more understandable
Additional sources
Article 2: Grade Point Average for Undergraduates in North Dakota State University
- Topic: Grade Point Average for Undergraduates
- Journal name: North Dakota State University
- Field of application: Job performance
- Purpose of the article: Study the undergraduates’ performance of North Dakota State University in fall terms.
Among these colleges, the freshmen class has an average GPA from 2.84 to 2.93 Only in Health Profession and Arts and Humanities and Social Sciences does the GPA exceed 3
Almost in every college, GPA is higher than 3 Engineering is the only college which has average GPA below 3, at 2.87
All colleges have GPA higher than 3, with 3.12 (Agriculture, Food System and Natural Resources) is the lowest and 3.37 (Business) is the highest.
None of the colleges have GPA below 3.3 and higher than 3.55
● The reason for using bar chart :
Bar charts effectively visualize the distribution of GPA values across various ranges, allowing users to easily identify the number of students within each GPA range They facilitate comparisons of GPA distributions across different categories, including college, major, and semester Additionally, the incorporation of color coding in the bar charts enhances the clarity and visual appeal of the data representation.
From 2013 to 2020, the starting GPA consistently increased across all classifications, from freshmen to seniors, before experiencing a decline in 2021.
2022 saw a rise in all classification
The reason for using line charts
Line charts effectively illustrate the trend in average GPAs over time, enabling users to track changes and identify patterns in the data By employing color coding, these charts differentiate between various colleges and majors, facilitating easier comparisons across categories.
Application of multiple bars chart
Compare the Credit Completion Ratio by College and Classification in Fall 2022
In general the Freshman of colleges have the lowest credit completion ratio while the figures for the Senior of most colleges are highest.
- The reason for using multiple bar chart applying for this information:
Bar charts effectively visualize the distribution of GPA values across various ranges, allowing users to easily identify the number of students within each GPA category They facilitate comparisons of GPA distributions across different factors, including college, major, and semester Additionally, the incorporation of color coding in these charts enhances the clarity and impact of the data presentation.
This chart shows the GPA of undergraduates students in each colleges in Fall
The Health Professions program boasts the highest average GPA among all colleges at 3.30, closely followed by Arts, Humanities, and Social Sciences, which also has an average GPA of 3.30 Business ranks slightly lower with an average GPA of 3.26.
The lowest GPA among all colleges is in the Human Sciences and Education with an average of 3.21.
The GPA tends to increase as the classification progresses, with Seniors having the highest average GPA among all classifications.
The difference in GPA between Freshmen and Seniors is significant in some colleges, such as the Human Sciences and Education and Health Professions
● The reason of applying cross tabulation in this research:
Cross-tabulation simplifies the analysis of large data sets, reducing confusion and the potential for errors By breaking down extensive data into representative subgroups, crosstabs allow for easier interpretation at a manageable scale, ultimately enhancing efficiency in data analysis.
● Name: Student Mental Health Data Sheet Fall 2020
● Author: Active Minds, a nonprofit organization focusing on mental health advocacy for college students.
● Article from: The data sheet was released by Active Minds and is available on their website.
This data sheet aims to present statistics and insights regarding student mental health in the United States, serving as a valuable resource to guide discussions and decisions aimed at enhancing mental health support and resources for college students.
The data sheet provides information from a variety of sources, including national surveys and research studies Some of the sources of data include:
● The National College Health Assessment (NCHA) survey collects information on student health behaviors and concerns.
● The Healthy Minds Study, surveys college students about their mental health and experiences with mental health services.
● The American College Health Association (ACHA), conducts research on health issues affecting college students.
The data sheet provides descriptive statistics, summarizing the results of various surveys and studies The statistics include:
● Prevalence rates for mental health issues such as anxiety and depression, as well as rates of suicide and suicide attempts.
● Information about student experiences with mental health services, including wait times for appointments and satisfaction with care.
● Data on the impact of the COVID-19 pandemic on student mental health.
● Information about stigma and help-seeking behaviors, such as the percentage of students who feel uncomfortable discussing their mental health with others.
Overall, the data sheet provides a comprehensive overview of the state of student mental health in the United States and highlights areas where improvements are needed.
A significant majority of survey participants, accounting for 62.26% or 1,277 individuals, were pursuing a bachelor's degree In contrast, those with a GED or high school equivalency represented only 1.02%, while participants not seeking a degree comprised 1.37% of the total respondents.
Nearly all participants across various categories reported a decline in their mental health due to COVID-19 Interestingly, a significantly higher proportion of high school students indicated that their mental health actually improved during the pandemic compared to other student groups.
Anxiety, isolation, and financial setbacks are common challenges faced by students at all educational levels, including college and high school Notably, high school students experienced less impact from relocation compared to their college counterparts According to statistics, only 4.24% of all students, 8.89% of college students, and 2.66% of high school students felt that their lives were unaffected by the COVID-19 pandemic.
Feeling disconnected from friends and loved ones emerged as the most stressful experience for both college and high school students Notably, high school students exhibited significant differences in meeting their basic needs and faced challenges in participating in special activities.
3.1 Parents were whom the majority of participants had most interaction with
On the contrary, educators had the lowest percentage.
4.1 Virtual interaction with friends were the most popular coping strategies among three categories, then came in- person interaction with friends and being around pets
A significant majority of participants expressed varying levels of hope regarding their academic goals, with only 1.71% of all students, 1.10% of college students, and 3.11% of high school students reporting a complete lack of hope.
The reason why should we applied that tables to the article:
Tables are a powerful tool for presenting student mental health information, as they organize large amounts of data clearly and effectively By using tables, readers can easily compare and contrast various data points and trends, making complex information more accessible and understandable.
Table 2.3 illustrates the varying feelings among three types of students, revealing that 21.06% of all students experience a sense of disconnection from their friends This disconnection is notably present in 20.20% of college students and 24.44% of high school students.
Utilizing tables to present information on student mental health enhances clarity and conciseness in data communication They effectively highlight key findings and trends, facilitating easier identification and comprehension of essential information for readers.
DATA ANALYSIS
A study conducted by university staff in Melbourne, Australia, aimed to investigate the prevalence and impact of sleep problems on various aspects of life Participants completed a questionnaire addressing their sleep behavior, including average hours slept per night and specific sleep issues such as difficulty falling asleep The findings revealed that sleep problems significantly affect work performance, driving safety, and personal relationships The study included 271 respondents, with a gender distribution of 55% female and 45% male, and an age range of 18 to 84 years.
Survey respondents : 271 staffs from a university in Melbourne,
The data consists of 271 respondents including 150 female (55.4%) and 121 male (44.6%) The difference is not remarkable
The table shows that most of the respondents has been married and account for 69.4 % in the survey while single, divorced and widowed respondents only contribute for 19.9%,7.7% and 3% respectively
Cumulativ e Percent Valid yes 34 12,5 12,6 12,6 no 236 87,1 87,4 100,0
In this table, only a small amount of people who have taken the survey smoke 12.6% and the rest of them do not smoke
●Do respondents have problems falling asleep
Cumulativ e Percent Valid yes 106 39,1 39,4 39,4 no 163 60,1 60,6 100,0
This data shows that among all of the respondents, 39.4% of them answered that they have problems falling asleep.
●Do respondents wake up during nights ?
Frequen Percen Valid Cumulativ cy t Percent e Percent
In this table almost 80% of the respondents answered that they wake up during nights which cancel their sleeping period
●Quality of sleep (from ‘very poor’ to ‘excellent’)
Valid very poor 11 4,1 4,1 4,1 poor 25 9,2 9,3 13,4 fair 75 27,7 28,0 41,4 good 90 33,2 33,6 75,0 very good 57 21,0 21,3 96,3 excelle nt 10 3,7 3,7 100,0
According to the chart, the majority of individuals rate their sleep quality as fair (28%), good (33.6%), or very good (21.3%) Nevertheless, a small percentage of respondents report experiencing very poor (4.1%) or poor (9.3%) sleep quality.
● Do Respondents have problem with sleep?
In this table, 43.5% agree that they have problems with sleep and 56.1% state that they have no issues
●Do respondents suffer from hardship while breathing
Cumulativ e Percent Valid yes 22 8,1 8,4 8,4 no 241 88,9 91,6 100,0
Stop breathing is a serious and rare symptom so it is reasonable why there are only 8.4% of the respondents answered that they have this symptom.
●Do respondents feel sleepy while driving
Cumulativ e Percent Valid yes 31 11,4 12,4 12,4 no 218 80,4 87,6 100,0
In this data, 12.4% answered that they fell sleepy while driving
●Did respondents cause accidents when they feel sleepy while driving
Cumulativ e Percent Valid yes 23 8,5 9,2 9,2 no 227 83,8 90,8 100,0
In the last table,12.4% answered that they fell sleepy while driving so it is no doubt that there will be around 9.2% of respondents have accidents due to sleepiness
●Number of alcoholic drinks per day
●Number of caffeine drinks per day
Despite low alcohol consumption among respondents, many consume a substantial amount of caffeine, averaging 2 to 4 caffeinated beverages daily Notably, a smaller group drinks between 6 to 9 cups per day, which is significantly higher than typical consumption levels.
●Hour of sleep per night
In this data , almost all respondents usually sleep 6-8 hours at night This is really good for their health.
Overall, most of people who have taken the survey rated their satisfaction with sleep around 3 to 4 which is not very satisfied and 8 to 9 which is satisfied with their sleep
The majority of survey respondents rated their sleep quality between 3 and 5, indicating that they generally experience good sleep Conversely, a small number of participants reported difficulties with their sleep.
● How does mood affect sleep ?
In this histogram , it can be seen that many people mark their mood 7 or 8 on the scale to 10 which is a positive sign
According to this data , having a good sleep is vitally contributed to a high energy level , which help people to work more efficientlly during the day.
●Effect on memory (From 1 to 10 ;1 is insignificant, 10 is significant)
In this diagram , many people agree that sleep have some impact on their memory Most of them mark the impact of sleep on memory from 6 to 8 out of
In this data , statistics have shown that the mean is computed to be 4.82 which stated that sleep only have some impact on their relationships but not at a significant amount
The graph illustrates a positive skew, indicating a range of anxiety levels from 0 (no anxiety) to 21 (severe anxiety) Despite this range, the mean anxiety score is 6.34, suggesting that sleep has a minimal impact on individuals' anxiety levels.
● Do Poor quality sleep in a long period leads to depression ?
The data ranges from 0, indicating no depression, to 12, representing a high level of depression However, the mean value is only 3.5, suggesting that sleep has a minimal impact on the development of mental health disorders, particularly depression.
Both male and female respondents generally report that their sleep quality is fair to very good, with only a small percentage indicating that their sleep is poor or very poor.
The multiple bar chart indicates that most survey respondents aged under 37 and between 38-50 experience good quality sleep In contrast, individuals over 51 years old are more likely to encounter sleep issues This trend highlights a significant difference in sleep quality across age groups, with younger respondents reporting better sleep outcomes.
The multiple bar chart reveals that the majority of respondents are married, which is reflected in the highest representation on the graph Additionally, both single and married individuals report a very good quality of sleep In contrast, divorced and widowed respondents experience a significantly poorer quality of sleep compared to their married and single counterparts.
The graph illustrates a strong correlation between sleep quality and weekly sleep hours among respondents It is evident that increased sleep duration leads to improved sleep quality, with those sleeping 7-8 hours per week experiencing the highest quality of rest This optimal sleep duration positively impacts their productivity at work.
The graph illustrates a clear correlation between sleep quality and weekly sleep hours among respondents It indicates that an increase in weekly sleep hours leads to improved sleep quality Notably, those who sleep between 7 to 8 hours per week experience the highest quality of sleep, which positively affects their work productivity.