The pie charts illustrate the proportion of citizens working in three categories in two Towns in two different years, 1960 and 2010.
It is evident that the number of people working in sales was largest in both towns in 1960. Besides, Town A and town B both saw a tremendous increase in the percentage of manufacturing.
While the figure of manufacturing in town A rose significantly from 29% in 1996 to 64% in 2010, that of sales decreased enormously from the highest number of 41% in 1996 to nearly a half in 2010. There was a small fall in the data of people working in services from 30% in 1996 to around 15% in 2010.
In town B, the statistic of manufacturing grew slightly from 10% in 1996 to a quarter in the following 40 years, as opposed to that of sales with a plummet from 70% in 1960 to 50% in 2010. There was a minimal change in the number of people working in services from 20% in the initial year to 22% in the final year.
The pie charts illustrate the proportion of citizens working in three categories in two Towns in two different years, 1960 and 2010.
It is evident that the number of people working in sales was largest in both towns in 1960. Besides, Town A and town B both saw a tremendous increase in the percentage of manufacturing.
While the figure of manufacturing in town A rose significantly from 29% in 1996 to 64% in 2010, that of sales decreased enormously from the highest number of 41% in 1996 to nearly a half in 2010. There was a small fall in the data of people working in services from 30% in 1996 to around 15% in 2010.
In town B, the statistic of manufacturing grew slightly from 10% in 1996 to a quarter in the following 40 years, as opposed to that of sales with a plummet from 70% in 1960 to 50% in 2010. There was a minimal change in the number of people working in services from 20% in the initial year to 22% in the final year.
- The table illustrates the amount of money which is allocated in the US EU and other nations used in support of technology by charities over the period from 2006 to 2010 Overall it is evident that most of the countries experienced an increase during the gi 56
- The bar charts compare how many people in urban and rural areas were affected by noise pollution from four sources during daytime and nightime in 2007 Overall it is clear that more people in cities experienced all types of noise pollution compared with ru 67
- The pie charts illustrate the proportion of citizens working in three categories in two Towns in two different years 1960 and 2010 It is evident that the number of people working in sales was largest in both towns in 1960 Besides Town A and town B both sa 67
- The table illustrates how much money was donated to the developing countries in the period from 2006 to 2010 by the US UK charities to support technological development Overall it is evident that most of the countries experienced an increase during the gi 73
- The pie charts compare the water usage of various sectors of the economy in Sydney in two years 1997 and 2007 Overall it is clear that the sector which used the highest percentage of water was the food industry The percentage of total water use by the ser
Grammar and spelling errors:
Line 2, column 1, Rule ID: WHITESPACE_RULE
Message: Possible typo: you repeated a whitespace
Suggestion:
...in two different years, 1960 and 2010. It is evident that the number of people ...
^^^
Line 4, column 1, Rule ID: WHITESPACE_RULE
Message: Possible typo: you repeated a whitespace
Suggestion:
...se in the percentage of manufacturing. While the figure of manufacturing in tow...
^^^
Line 6, column 1, Rule ID: WHITESPACE_RULE
Message: Possible typo: you repeated a whitespace
Suggestion:
...rom 30% in 1996 to around 15% in 2010. In town B, the statistic of manufacturin...
^^^
Transition Words or Phrases used:
besides, if, while
Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments
Performance on Part of Speech:
To be verbs : 4.0 7.0 57% => More to be verbs wanted.
Auxiliary verbs: 0.0 1.00243902439 0% => OK
Conjunction : 2.0 6.8 29% => More conjunction wanted.
Relative clauses : 3.0 3.15609756098 95% => OK
Pronoun: 4.0 5.60731707317 71% => OK
Preposition: 50.0 33.7804878049 148% => OK
Nominalization: 1.0 3.97073170732 25% => More nominalizations (nouns with a suffix like: tion ment ence ance) wanted.
Performance on vocabulary words:
No of characters: 769.0 965.302439024 80% => OK
No of words: 178.0 196.424390244 91% => More content wanted.
Chars per words: 4.3202247191 4.92477711251 88% => OK
Fourth root words length: 3.65262427087 3.73543355544 98% => OK
Word Length SD: 2.61974309949 2.65546596893 99% => OK
Unique words: 85.0 106.607317073 80% => More unique words wanted.
Unique words percentage: 0.477528089888 0.547539520022 87% => More unique words wanted or less content wanted.
syllable_count: 216.0 283.868780488 76% => OK
avg_syllables_per_word: 1.2 1.45097560976 83% => OK
A sentence (or a clause, phrase) starts by:
Pronoun: 2.0 1.53170731707 131% => OK
Article: 2.0 4.33902439024 46% => OK
Subordination: 2.0 1.07073170732 187% => OK
Conjunction: 0.0 0.482926829268 0% => OK
Preposition: 1.0 3.36585365854 30% => More preposition wanted as sentence beginning.
Performance on sentences:
How many sentences: 7.0 8.94146341463 78% => Need more sentences. Double check the format of sentences, make sure there is a space between two sentences, or have enough periods. And also check the lengths of sentences, maybe they are too long.
Sentence length: 25.0 22.4926829268 111% => OK
Sentence length SD: 39.8886204426 43.030603864 93% => OK
Chars per sentence: 109.857142857 112.824112599 97% => OK
Words per sentence: 25.4285714286 22.9334400587 111% => OK
Discourse Markers: 2.57142857143 5.23603664747 49% => More transition words/phrases wanted.
Paragraphs: 4.0 3.83414634146 104% => OK
Language errors: 3.0 1.69756097561 177% => OK
Sentences with positive sentiment : 4.0 3.70975609756 108% => OK
Sentences with negative sentiment : 0.0 1.13902439024 0% => More negative sentences wanted.
Sentences with neutral sentiment: 3.0 4.09268292683 73% => OK
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.553530461798 0.215688989381 257% => OK
Sentence topic coherence: 0.293649874215 0.103423049105 284% => Sentence topic similarity is high.
Sentence topic coherence SD: 0.215269149179 0.0843802449381 255% => The coherence between sentences is low.
Paragraph topic coherence: 0.388687053343 0.15604864568 249% => OK
Paragraph topic coherence SD: 0.20626642329 0.0819641961636 252% => More connections among paragraphs wanted.
Essay readability:
automated_readability_index: 11.6 13.2329268293 88% => Automated_readability_index is low.
flesch_reading_ease: 79.94 61.2550243902 131% => OK
smog_index: 3.1 6.51609756098 48% => Smog_index is low.
flesch_kincaid_grade: 8.3 10.3012195122 81% => OK
coleman_liau_index: 8.07 11.4140731707 71% => OK
dale_chall_readability_score: 7.36 8.06136585366 91% => OK
difficult_words: 28.0 40.7170731707 69% => More difficult words wanted.
linsear_write_formula: 11.0 11.4329268293 96% => OK
gunning_fog: 12.0 10.9970731707 109% => OK
text_standard: 12.0 11.0658536585 108% => OK
What are above readability scores?
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Rates: 67.4157303371 out of 100
Scores by essay e-grader: 6.0 Out of 9
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Note: the e-grader does NOT examine the meaning of words and ideas. VIP users will receive further evaluations by advanced module of e-grader and human graders.