The line graph shows the proportion of total exports of clothing in 4 countries in 2000 and 2014.
The graph illustrates data about the amount of clothes exported by four different countries between 2000 and 2014.
Overall, the graph underscores notable upward trends in clothing exports from both China and Asia, while those from the European Union and the USA saw a steady decline over the period in question.
Looking at the details, China’s exports started at under 15 in 2000 and then there was a sharp increase throughout the period, rocketing to over 35 in 2014. This meant that China was the largest exporter of clothes among the four countries in that year. In the case of Asia’s clothing exports, it commenced at a higher point than China’s at the start of the period, followed by a sharp decrease to approximately 18 in 2002. Subsequently, there was a slight rise, with the proportion to 20, but still lower than the initial level.
In contrast, export trends from the EU and the US followed a different trend. Despite starting with the highest trend, the exports of the EU dropped significantly till the end of the period. If we examine the clothing export figures from the United States, there was a fluctuation between 12 and 4 over a 14 year period.
The essay is logically organized and presents a clear overview. The use of cohesive devices is effective, and there is a good balance between paragraphing and information flow.
Suggestions
- Consider using a wider range of linking words and phrases to show more variety in your language use.
The essay uses a wide range of vocabulary and there is evidence of less common and idiomatic usage. The vocabulary is generally used appropriately, with some good use of synonyms and collocations.
The essay uses a wide range of complex structures. There are few grammatical errors, and these do not impede communication.
The essay addresses all parts of the task and presents a clear overview of the main trends, differences or stages. The essay also presents detail information and support this information well.
Suggestions
- Ensure that you fully understand the data and the trends it is presenting before you start writing. This will help to avoid any misunderstandings or misinterpretations of the data.