The presented circle graph compares the percentage of budget that a family spends in Japan and Malaysia in 2010.
Overall, it is evident that housing, transport, food and health care were applied in both nations. Moreover, there were considerable differences in proportion of transport and housing between Malaysia and Japan.
Turning into detail, in 2010, while Malaysian expended 10% of their income on transport, the figure for Japan exactly doubled. In the same way, the average household expenditure on health care in Malaysia was only 3%, whereas that of Japan was 2 times higher. In contrast, Malaysian family spent a quite lot of their budget on housing, which occupied 34%, the number for Japan only accounted for 21%.
Regarding to 2 remaining sectors, there was no significant difference. In comparison with the food paying in Malaysia, which was 27%, that of Japan was 3% lower. Besides, 29% of money that Japanese used for other goods and services, surpassing the figure of Malaysia, which occupied 26%.
- Some people say that to prevent illness and disease governments should focus more on reducing environmental pollution and housing problems To what extent do you agree or disagree 89
- The table below shows the average band scores for students from different language groups taking the IELTS General Test in 2010 Summarise the information by selecting and reporting the main features and make comparisons where relevant 89
- Nowadays, sport is becoming a big business with high earning for professional sportsmen and a lot of companies have involved in financially and in other ways.Is this a positive or negative development? 84
- Some people think that governments should ban dangerous sports, while others think people should have freedom to do any sports or activity. Discuss both views and give your own opinion? 78
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Grammar and spelling errors:
Line 5, column 75, Rule ID: WHITESPACE_RULE
Message: Possible typo: you repeated a whitespace
Suggestion:
...e Malaysian expended 10% of their income on transport, the figure for Japan exact...
^^
Line 5, column 298, Rule ID: A_RB_NN[1]
Message: You used an adverb ('quite') instead an adjective, or a noun ('lot') instead of another adjective.
...er. In contrast, Malaysian family spent a quite lot of their budget on housing, which occup...
^^^^^^^^^^^
Line 7, column 75, Rule ID: SENT_START_CONJUNCTIVE_LINKING_ADVERB_COMMA[2]
Message: Did you forget a comma after a conjunctive/linking adverb?
Suggestion: comparison,
...there was no significant difference. In comparison with the food paying in Malaysia, which...
^^^^^^^^^^
Transition Words or Phrases used:
besides, if, moreover, regarding, so, whereas, while, in contrast, in the same way
Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments
Performance on Part of Speech:
To be verbs : 8.0 7.0 114% => OK
Auxiliary verbs: 0.0 1.00243902439 0% => OK
Conjunction : 5.0 6.8 74% => OK
Relative clauses : 8.0 3.15609756098 253% => Less relative clauses wanted (maybe 'which' is over used).
Pronoun: 8.0 5.60731707317 143% => Less pronouns wanted
Preposition: 26.0 33.7804878049 77% => OK
Nominalization: 2.0 3.97073170732 50% => More nominalizations (nouns with a suffix like: tion ment ence ance) wanted.
Performance on vocabulary words:
No of characters: 863.0 965.302439024 89% => OK
No of words: 165.0 196.424390244 84% => More content wanted.
Chars per words: 5.2303030303 4.92477711251 106% => OK
Fourth root words length: 3.58402463422 3.73543355544 96% => OK
Word Length SD: 2.65433789143 2.65546596893 100% => OK
Unique words: 100.0 106.607317073 94% => More unique words wanted.
Unique words percentage: 0.606060606061 0.547539520022 111% => OK
syllable_count: 254.7 283.868780488 90% => OK
avg_syllables_per_word: 1.5 1.45097560976 103% => OK
A sentence (or a clause, phrase) starts by:
Pronoun: 2.0 1.53170731707 131% => OK
Article: 4.0 4.33902439024 92% => OK
Subordination: 1.0 1.07073170732 93% => OK
Conjunction: 0.0 0.482926829268 0% => OK
Preposition: 5.0 3.36585365854 149% => OK
Performance on sentences:
How many sentences: 9.0 8.94146341463 101% => OK
Sentence length: 18.0 22.4926829268 80% => The Avg. Sentence Length is relatively short.
Sentence length SD: 21.1385786223 43.030603864 49% => The essay contains lots of sentences with the similar length. More sentence varieties wanted.
Chars per sentence: 95.8888888889 112.824112599 85% => OK
Words per sentence: 18.3333333333 22.9334400587 80% => OK
Discourse Markers: 9.11111111111 5.23603664747 174% => OK
Paragraphs: 4.0 3.83414634146 104% => OK
Language errors: 3.0 1.69756097561 177% => OK
Sentences with positive sentiment : 3.0 3.70975609756 81% => OK
Sentences with negative sentiment : 2.0 1.13902439024 176% => OK
Sentences with neutral sentiment: 4.0 4.09268292683 98% => OK
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.144952195857 0.215688989381 67% => OK
Sentence topic coherence: 0.0616446149014 0.103423049105 60% => OK
Sentence topic coherence SD: 0.050368844074 0.0843802449381 60% => OK
Paragraph topic coherence: 0.0875256825156 0.15604864568 56% => OK
Paragraph topic coherence SD: 0.0298574131255 0.0819641961636 36% => Paragraphs are similar to each other. Some content may get duplicated or it is not exactly right on the topic.
Essay readability:
automated_readability_index: 12.4 13.2329268293 94% => Automated_readability_index is low.
flesch_reading_ease: 61.67 61.2550243902 101% => OK
smog_index: 3.1 6.51609756098 48% => Smog_index is low.
flesch_kincaid_grade: 9.1 10.3012195122 88% => OK
coleman_liau_index: 13.05 11.4140731707 114% => OK
dale_chall_readability_score: 8.93 8.06136585366 111% => OK
difficult_words: 46.0 40.7170731707 113% => OK
linsear_write_formula: 8.0 11.4329268293 70% => OK
gunning_fog: 9.2 10.9970731707 84% => OK
text_standard: 9.0 11.0658536585 81% => OK
What are above readability scores?
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Rates: 78.6516853933 out of 100
Scores by essay e-grader: 7.0 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.