The table shows the population of three cities in 1990, the population forecast of 2000 and the actual of 2000.
The tabular representation reveals the information about generation of distinct cities such as: Sao Paulo, Jakarta, and Shanghai in year 1990 as well as it shows, predicted growth rate and the acutual population during year 2000. It is clearly and coherently representation.
It is lucid, Sao Paulo had 15 million popultion in year 1990, it is highest ratio as compared to teo other cities. As well as, Jakarta and Shanghai was respectively 9.5 million and 13.5 million in 1990. However, in predicted year the generation of all cities would increase significantly like, Sao paulo had 24 million, Shanghai 17 million and Jakarta had the least populatiob which was 14 millon.
Moreover, in year 2000 the actual growth rate of Sao Paulo was more as to Jakarta and Shanghai but it was lesser than expected. While Jakarta had been more than expected value, and Shangai had lesser to prediceted rate as for as actual population in 1990, which was 12.5 million in actual year 2000.
Overall, it is clearly seen that Sao paulo had highest populated city and jakarta was follow to Sao paulo while Shanghai had lowest populated city. The prediction of all cities was proved wrong in actual year.
| Post date | Users | Rates | Link to Content |
|---|---|---|---|
| 2022-05-18 | Jocelyn | 89 | view |
| 2021-04-25 | yashu_5219 | 56 | view |
| 2019-02-20 | Kudrat | 76 | view |
| 2018-07-14 | kaur randhawa | 82 | view |
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Grammar and spelling errors:
Line 2, column 66, Rule ID: THE_SUPERLATIVE[2]
Message: A determiner is probably missing here: 'is the highest'.
Suggestion: is the highest
...d 15 million popultion in year 1990, it is highest ratio as compared to teo other cities. ...
^^^^^^^^^^
Line 4, column 44, Rule ID: THE_SUPERLATIVE[2]
Message: A determiner is probably missing here: 'had the highest'.
Suggestion: had the highest
...rall, it is clearly seen that Sao paulo had highest populated city and jakarta was follow t...
^^^^^^^^^^^
Line 4, column 87, Rule ID: BEEN_PART_AGREEMENT[1]
Message: Consider using a past participle here: 'followed'.
Suggestion: followed
... highest populated city and jakarta was follow to Sao paulo while Shanghai had lowest ...
^^^^^^
Line 4, column 122, Rule ID: THE_SUPERLATIVE[2]
Message: A determiner is probably missing here: 'had the lowest'.
Suggestion: had the lowest
... was follow to Sao paulo while Shanghai had lowest populated city. The prediction of all c...
^^^^^^^^^^
Transition Words or Phrases used:
but, however, if, moreover, well, while, as for, as to, such as, as well as
Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments
Performance on Part of Speech:
To be verbs : 12.0 7.0 171% => OK
Auxiliary verbs: 1.0 1.00243902439 100% => OK
Conjunction : 10.0 6.8 147% => OK
Relative clauses : 3.0 3.15609756098 95% => OK
Pronoun: 7.0 5.60731707317 125% => Less pronouns wanted
Preposition: 19.0 33.7804878049 56% => More preposition wanted.
Nominalization: 9.0 3.97073170732 227% => Less nominalizations (nouns with a suffix like: tion ment ence ance) wanted.
Performance on vocabulary words:
No of characters: 989.0 965.302439024 102% => OK
No of words: 200.0 196.424390244 102% => OK
Chars per words: 4.945 4.92477711251 100% => OK
Fourth root words length: 3.76060309309 3.73543355544 101% => OK
Word Length SD: 2.63586323621 2.65546596893 99% => OK
Unique words: 98.0 106.607317073 92% => More unique words wanted.
Unique words percentage: 0.49 0.547539520022 89% => More unique words wanted or less content wanted.
syllable_count: 291.6 283.868780488 103% => OK
avg_syllables_per_word: 1.5 1.45097560976 103% => OK
A sentence (or a clause, phrase) starts by:
Pronoun: 4.0 1.53170731707 261% => Less pronouns wanted as sentence beginning.
Article: 2.0 4.33902439024 46% => OK
Subordination: 2.0 1.07073170732 187% => OK
Conjunction: 2.0 0.482926829268 414% => Less conjunction wanted as sentence beginning.
Preposition: 2.0 3.36585365854 59% => More preposition wanted as sentence beginning.
Performance on sentences:
How many sentences: 9.0 8.94146341463 101% => OK
Sentence length: 22.0 22.4926829268 98% => OK
Sentence length SD: 57.8659583503 43.030603864 134% => OK
Chars per sentence: 109.888888889 112.824112599 97% => OK
Words per sentence: 22.2222222222 22.9334400587 97% => OK
Discourse Markers: 8.33333333333 5.23603664747 159% => OK
Paragraphs: 4.0 3.83414634146 104% => OK
Language errors: 4.0 1.69756097561 236% => Less language errors wanted.
Sentences with positive sentiment : 7.0 3.70975609756 189% => OK
Sentences with negative sentiment : 1.0 1.13902439024 88% => OK
Sentences with neutral sentiment: 1.0 4.09268292683 24% => More facts, knowledge or examples wanted.
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.196700149834 0.215688989381 91% => OK
Sentence topic coherence: 0.0954907358138 0.103423049105 92% => OK
Sentence topic coherence SD: 0.0735170771757 0.0843802449381 87% => OK
Paragraph topic coherence: 0.149291107508 0.15604864568 96% => OK
Paragraph topic coherence SD: 0.0625920031303 0.0819641961636 76% => OK
Essay readability:
automated_readability_index: 13.0 13.2329268293 98% => OK
flesch_reading_ease: 57.61 61.2550243902 94% => OK
smog_index: 8.8 6.51609756098 135% => OK
flesch_kincaid_grade: 10.7 10.3012195122 104% => OK
coleman_liau_index: 11.73 11.4140731707 103% => OK
dale_chall_readability_score: 8.44 8.06136585366 105% => OK
difficult_words: 47.0 40.7170731707 115% => OK
linsear_write_formula: 12.0 11.4329268293 105% => OK
gunning_fog: 10.8 10.9970731707 98% => 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.