The pie charts below show the average household expenditures in Japan and Malaysia in the year 2010.
The charts compare the average household spending in Japan and Malaysia in terms
of five important categories in 2010.
Overall, it is clear that householders in both countries spent the largest proportion of their income on just three categories – housing, food and other goods and services. The percentage figures for spending on transport and healthcare in Japan were double those for Malaysia.
In Malaysian households, the highest category was housing, which represented 34%
of the total expenditure. Whereas this was higher than in Japan, with just 21% spent on housing, Japanese householders spent the highest proportion of a range of other goods and services, at 29%. This was slightly more than in Malaysia. In terms of food, the figures for both countries were similar, at 27% and 24% for Malaysia and
Japan respectively.
Expenditure on health care was the lowest category. In Japan, this accounted for 6% of the total, while 20% of household spending went on transport. These figures were exactly double those shown for Malaysia.
Post date | Users | Rates | Link to Content |
---|---|---|---|
2019-12-20 | Chayacp | 56 | view |
2019-12-17 | Jesslynindah | 67 | view |
2019-12-17 | thanhthanh211 | 67 | view |
2019-12-15 | Zulph_ | 84 | view |
2019-12-11 | faraj27 | 73 | view |
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Grammar and spelling errors:
Line 1, column 81, Rule ID: WHITESPACE_RULE
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Suggestion:
... spending in Japan and Malaysia in terms of five important categories in 2010. O...
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...of their income on just three categories – housing, food and other goods and serv...
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...ods and services. The percentage figures for spending on transport and healthca...
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...es. The percentage figures for spending on transport and healthcare in Japan w...
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Message: Possible typo: you repeated a whitespace
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... figures for spending on transport and healthcare in Japan were double those f...
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Line 3, column 243, Rule ID: WHITESPACE_RULE
Message: Possible typo: you repeated a whitespace
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...pending on transport and healthcare in Japan were double those for Malaysia. ...
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Line 4, column 81, Rule ID: WHITESPACE_RULE
Message: Possible typo: you repeated a whitespace
Suggestion:
...egory was housing, which represented 34% of the total expenditure. Whereas this ...
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Line 5, column 334, Rule ID: WHITESPACE_RULE
Message: Possible typo: you repeated a whitespace
Suggestion:
...similar, at 27% and 24% for Malaysia and Japan respectively. Expenditure on heal...
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Line 7, column 80, Rule ID: WHITESPACE_RULE
Message: Possible typo: you repeated a whitespace
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...t category. In Japan, this accounted for 6% of the total, while 20% of household ...
^^
Transition Words or Phrases used:
whereas, while
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 : 7.0 6.8 103% => OK
Relative clauses : 2.0 3.15609756098 63% => OK
Pronoun: 9.0 5.60731707317 161% => 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: 885.0 965.302439024 92% => OK
No of words: 168.0 196.424390244 86% => More content wanted.
Chars per words: 5.26785714286 4.92477711251 107% => OK
Fourth root words length: 3.60020574368 3.73543355544 96% => OK
Word Length SD: 2.78015700261 2.65546596893 105% => OK
Unique words: 92.0 106.607317073 86% => More unique words wanted.
Unique words percentage: 0.547619047619 0.547539520022 100% => OK
syllable_count: 259.2 283.868780488 91% => 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.
Interrogative: 0.0 0.114634146341 0% => OK
Article: 4.0 4.33902439024 92% => OK
Subordination: 1.0 1.07073170732 93% => OK
Conjunction: 0.0 0.482926829268 0% => OK
Preposition: 8.0 3.36585365854 238% => Less preposition wanted as sentence beginnings.
Performance on sentences:
How many sentences: 10.0 8.94146341463 112% => OK
Sentence length: 16.0 22.4926829268 71% => The Avg. Sentence Length is relatively short.
Sentence length SD: 43.2158535725 43.030603864 100% => OK
Chars per sentence: 88.5 112.824112599 78% => OK
Words per sentence: 16.8 22.9334400587 73% => OK
Discourse Markers: 1.4 5.23603664747 27% => More transition words/phrases wanted.
Paragraphs: 6.0 3.83414634146 156% => Less paragraphs wanted.
Language errors: 9.0 1.69756097561 530% => Less language errors wanted.
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: 6.0 4.09268292683 147% => OK
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.20758595722 0.215688989381 96% => OK
Sentence topic coherence: 0.0916880552045 0.103423049105 89% => OK
Sentence topic coherence SD: 0.0921992787641 0.0843802449381 109% => OK
Paragraph topic coherence: 0.127068597436 0.15604864568 81% => OK
Paragraph topic coherence SD: 0.114910308654 0.0819641961636 140% => OK
Essay readability:
automated_readability_index: 11.8 13.2329268293 89% => Automated_readability_index is low.
flesch_reading_ease: 63.7 61.2550243902 104% => OK
smog_index: 8.8 6.51609756098 135% => OK
flesch_kincaid_grade: 8.4 10.3012195122 82% => OK
coleman_liau_index: 12.99 11.4140731707 114% => OK
dale_chall_readability_score: 8.19 8.06136585366 102% => OK
difficult_words: 40.0 40.7170731707 98% => OK
linsear_write_formula: 11.5 11.4329268293 101% => OK
gunning_fog: 8.4 10.9970731707 76% => OK
text_standard: 9.0 11.0658536585 81% => OK
What are above readability scores?
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Maximum four paragraphs wanted.
Rates: 56.1797752809 out of 100
Scores by essay e-grader: 5.0 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.