The bar chart below shows the amount of money invested in each category from five organizations.
The bar chart compares how much money invested in machinery, building, staff training and research from five organizations.
Overall, organization B spent much money on staff training, while organization A invested most in building. However, machinery and research was most invested in organization C. Both Organization D and B spent most on building.
Machinery accounted for the largest investment of organization C, with almost 1.3 billion euros. The figure of machinery was equal at approximately 0,9 billion euros in organization B and D. In terms of building investment, organization A spent the most at 1.5 billion euros, while at 1 billion euros was the investment of Organization C, D and E.
The highest figures of staff training and research were recorded in organization B, with about 1.9 billion euros and 1,6 billion euros respectively. In contrast, the figure of staff training in other four organizations was less than 1.4 billion euros. Organization C and A were invested almost 1.3 and 1.1 billion euros in research. Finally, other two organizations spent less than 0.8 billion euros on research.
| Post date | Users | Rates | Link to Content |
|---|---|---|---|
| 2022-09-18 | llkngocc | 67 | view |
| 2021-07-07 | Vanya Sharma | 61 | view |
| 2020-03-03 | Chang_highlight | 87 | view |
- The table below gives information about the value NZ of exports of kiwi fruit from New Zealand to five countries between 2010 and 2012 72
- The graph below shows Long Term International Migration in UK 1999 2008 100
- The bar chart below shows the amount of money invested in each category from five organizations 87
- The graph and table below give information about water use worldwide and water consumption in two different countries line bar 67
- Today large shopping centers and supermarkets are more common than small local shops Is this a negative or positive development 61
Transition Words or Phrases used:
finally, however, while, in contrast
Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments
Performance on Part of Speech:
To be verbs : 6.0 7.0 86% => OK
Auxiliary verbs: 0.0 1.00243902439 0% => OK
Conjunction : 9.0 6.8 132% => OK
Relative clauses : 0.0 3.15609756098 0% => OK
Pronoun: 0.0 5.60731707317 0% => OK
Preposition: 25.0 33.7804878049 74% => OK
Nominalization: 13.0 3.97073170732 327% => Less nominalizations (nouns with a suffix like: tion ment ence ance) wanted.
Performance on vocabulary words:
No of characters: 947.0 965.302439024 98% => OK
No of words: 177.0 196.424390244 90% => More content wanted.
Chars per words: 5.35028248588 4.92477711251 109% => OK
Fourth root words length: 3.64748333727 3.73543355544 98% => OK
Word Length SD: 3.23459033131 2.65546596893 122% => OK
Unique words: 81.0 106.607317073 76% => More unique words wanted.
Unique words percentage: 0.457627118644 0.547539520022 84% => More unique words wanted or less content wanted.
syllable_count: 277.2 283.868780488 98% => OK
avg_syllables_per_word: 1.6 1.45097560976 110% => OK
A sentence (or a clause, phrase) starts by:
Pronoun: 0.0 1.53170731707 0% => OK
Article: 4.0 4.33902439024 92% => OK
Subordination: 2.0 1.07073170732 187% => OK
Conjunction: 0.0 0.482926829268 0% => OK
Preposition: 4.0 3.36585365854 119% => OK
Performance on sentences:
How many sentences: 11.0 8.94146341463 123% => OK
Sentence length: 16.0 22.4926829268 71% => The Avg. Sentence Length is relatively short.
Sentence length SD: 30.9734623815 43.030603864 72% => OK
Chars per sentence: 86.0909090909 112.824112599 76% => OK
Words per sentence: 16.0909090909 22.9334400587 70% => OK
Discourse Markers: 3.27272727273 5.23603664747 63% => OK
Paragraphs: 4.0 3.83414634146 104% => OK
Language errors: 0.0 1.69756097561 0% => OK
Sentences with positive sentiment : 1.0 3.70975609756 27% => More positive sentences wanted.
Sentences with negative sentiment : 0.0 1.13902439024 0% => More negative sentences wanted.
Sentences with neutral sentiment: 10.0 4.09268292683 244% => Less facts, knowledge or examples wanted.
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.204991172737 0.215688989381 95% => OK
Sentence topic coherence: 0.1074333159 0.103423049105 104% => OK
Sentence topic coherence SD: 0.0727559073837 0.0843802449381 86% => OK
Paragraph topic coherence: 0.164795796684 0.15604864568 106% => OK
Paragraph topic coherence SD: 0.0815610457269 0.0819641961636 100% => OK
Essay readability:
automated_readability_index: 11.8 13.2329268293 89% => Automated_readability_index is low.
flesch_reading_ease: 55.24 61.2550243902 90% => OK
smog_index: 8.8 6.51609756098 135% => OK
flesch_kincaid_grade: 9.5 10.3012195122 92% => OK
coleman_liau_index: 13.45 11.4140731707 118% => OK
dale_chall_readability_score: 7.2 8.06136585366 89% => OK
difficult_words: 31.0 40.7170731707 76% => More difficult words wanted.
linsear_write_formula: 8.0 11.4329268293 70% => OK
gunning_fog: 8.4 10.9970731707 76% => OK
text_standard: 8.0 11.0658536585 72% => 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.