The table and charts below give information on the police budget for 2017 and 2018 in one area of Britain. The table shows where the money came from and the charts show how it was distributed.
The given graphs provide information on the police’s financial plan for 2017 and 2018 in one specific area of Britain. The table illustrates sources of the money, while the chart presents how much was spent on salaries, technology, buildings and transport.
In general, the chart shows the majority of the police budget was from National Government and Local Taxes in 2017 and 2018. According to the two pie charts, spending money on salaries took the most percentage of the police expenses in both of the two years.
In 2017 and 2018, the total police budget witnessed a moderate increase in collecting money from the three mentioned sources from 304,7 million to 318,6 million. To be more specific, the National Government greatly contributed 175.5 and 177.8 million pounds in two respective years, a gentle rise. Considered as the second contribution, the amount of police budget raised by Local Taxes saw a considerable increase by 11.1 million pounds, from 91.2 to 102.3 million pounds. The figures for other sources (such as grants) that shared the same trend and accounted for the smallest part, around 38 million pounds in both of two years.
Regarding the two pie charts, the figure for spending money on salaries (officers and staff) saw a trivial fall from 75% to 69%, despite being the largest part. A reverse trend was recorded in spending on technology, from 8% to 14%, and was the lowest. Spending on buildings and transport remained unchanged at 17% in each year.
| Post date | Users | Rates | Link to Content |
|---|---|---|---|
| 2024-03-29 | minhnhat2002 | 84 | view |
| 2024-03-29 | minhnhat2002 | 78 | view |
| 2024-03-09 | minhnhat2002 | 73 | view |
| 2023-12-12 | Ahmad_off | 78 | view |
| 2023-12-12 | Ahmad_off | 78 | view |
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- The table and charts below give information on the police budget for 2017 and 2018 in one area of Britain The table shows where the money came from and the charts show how it was distributed 73
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Transition Words or Phrases used:
but, if, regarding, second, so, while, in general, such as
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 : 10.0 6.8 147% => OK
Relative clauses : 1.0 3.15609756098 32% => OK
Pronoun: 1.0 5.60731707317 18% => OK
Preposition: 41.0 33.7804878049 121% => OK
Nominalization: 4.0 3.97073170732 101% => OK
Performance on vocabulary words:
No of characters: 1242.0 965.302439024 129% => OK
No of words: 247.0 196.424390244 126% => OK
Chars per words: 5.02834008097 4.92477711251 102% => OK
Fourth root words length: 3.96437052324 3.73543355544 106% => OK
Word Length SD: 2.58052627736 2.65546596893 97% => OK
Unique words: 135.0 106.607317073 127% => OK
Unique words percentage: 0.546558704453 0.547539520022 100% => OK
syllable_count: 345.6 283.868780488 122% => OK
avg_syllables_per_word: 1.4 1.45097560976 96% => OK
A sentence (or a clause, phrase) starts by:
Pronoun: 0.0 1.53170731707 0% => OK
Article: 10.0 4.33902439024 230% => Less articles wanted as sentence beginning.
Subordination: 1.0 1.07073170732 93% => OK
Conjunction: 1.0 0.482926829268 207% => Less conjunction wanted as sentence beginning.
Preposition: 9.0 3.36585365854 267% => Less preposition wanted as sentence beginnings.
Performance on sentences:
How many sentences: 11.0 8.94146341463 123% => OK
Sentence length: 22.0 22.4926829268 98% => OK
Sentence length SD: 28.6910012673 43.030603864 67% => OK
Chars per sentence: 112.909090909 112.824112599 100% => OK
Words per sentence: 22.4545454545 22.9334400587 98% => OK
Discourse Markers: 5.27272727273 5.23603664747 101% => OK
Paragraphs: 4.0 3.83414634146 104% => OK
Language errors: 0.0 1.69756097561 0% => OK
Sentences with positive sentiment : 4.0 3.70975609756 108% => OK
Sentences with negative sentiment : 2.0 1.13902439024 176% => OK
Sentences with neutral sentiment: 5.0 4.09268292683 122% => OK
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.303826943233 0.215688989381 141% => OK
Sentence topic coherence: 0.113370747939 0.103423049105 110% => OK
Sentence topic coherence SD: 0.103379048294 0.0843802449381 123% => OK
Paragraph topic coherence: 0.19798935548 0.15604864568 127% => OK
Paragraph topic coherence SD: 0.107881724886 0.0819641961636 132% => OK
Essay readability:
automated_readability_index: 13.5 13.2329268293 102% => OK
flesch_reading_ease: 66.07 61.2550243902 108% => OK
smog_index: 3.1 6.51609756098 48% => Smog_index is low.
flesch_kincaid_grade: 9.5 10.3012195122 92% => OK
coleman_liau_index: 12.19 11.4140731707 107% => OK
dale_chall_readability_score: 8.44 8.06136585366 105% => OK
difficult_words: 58.0 40.7170731707 142% => OK
linsear_write_formula: 11.0 11.4329268293 96% => OK
gunning_fog: 10.8 10.9970731707 98% => OK
text_standard: 11.0 11.0658536585 99% => OK
What are above readability scores?
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Rates: 73.0337078652 out of 100
Scores by essay e-grader: 6.5 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.