The table and charts detailed below give information about the police budget in 2017 and 2018 in on area of Britain The table illustrates where the money came from and the charts show how it was distributed

The two illustrations demonstrate the sources of money that are allocated to local security in a specific area of Britain in the years 2017 and 2018. The table gives information about the sources of the police budget while the pie charts depict the percentage of invested money into 3 different categories. Overall, the national government was the most significant allocator while other sources such as grants accounted for the least. Additionally, the majority of the money was spent on staff salaries and the least budget was spent on technology.

Having looked at the table for more details, it is clear that the largest amount of money for the police budget was from the national government, taking up around 175.5 million in 2017, followed by a slight increase of 2.3 million a year later. The local taxes category was in the second rank, accounting for nearly half of the national government’s figure in 2017. Notably, its figure increased to over 100 million in 2018. The money from other sources, specifically, grants didn’t show any drastic changes, stagnating at roughly 38 million.

Focusing on the rest data given, in 2017, precisely three-fourths of the police budget was for paying wages. However, its figure experienced a persistent decrease of 6 percent in 2018. The money allocated to buildings and transport showed no dramatic alterations, maintaining around 17 percent in 2 years. Significantly, the proportion of money invested in technology in 2017 was under a tenth and reached nearly double the initial data in 2018, holding 14 percent.

Votes
Average: 8.4 (1 vote)
Essays by the user:

Grammar and spelling errors:
Line 3, column 256, Rule ID: POSSESIVE_APOSTROPHE[1]
Message: Possible typo: apostrophe is missing. Did you mean 'taxes'' or 'tax's', 'taxis's'?
Suggestion: taxes'; tax's; taxis's
... of 2.3 million a year later. The local taxes category was in the second rank, accoun...
^^^^^

Transition Words or Phrases used:
however, if, look, second, so, while, as for, such as

Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments

Performance on Part of Speech:
To be verbs : 9.0 7.0 129% => OK
Auxiliary verbs: 0.0 1.00243902439 0% => OK
Conjunction : 4.0 6.8 59% => More conjunction wanted.
Relative clauses : 2.0 3.15609756098 63% => OK
Pronoun: 5.0 5.60731707317 89% => OK
Preposition: 41.0 33.7804878049 121% => OK
Nominalization: 4.0 3.97073170732 101% => OK

Performance on vocabulary words:
No of characters: 1316.0 965.302439024 136% => OK
No of words: 254.0 196.424390244 129% => OK
Chars per words: 5.1811023622 4.92477711251 105% => OK
Fourth root words length: 3.99216450694 3.73543355544 107% => OK
Word Length SD: 2.86597948836 2.65546596893 108% => OK
Unique words: 147.0 106.607317073 138% => OK
Unique words percentage: 0.57874015748 0.547539520022 106% => OK
syllable_count: 389.7 283.868780488 137% => OK
avg_syllables_per_word: 1.5 1.45097560976 103% => OK

A sentence (or a clause, phrase) starts by:
Pronoun: 3.0 1.53170731707 196% => OK
Article: 8.0 4.33902439024 184% => OK
Subordination: 0.0 1.07073170732 0% => More adverbial clause wanted.
Conjunction: 0.0 0.482926829268 0% => OK
Preposition: 1.0 3.36585365854 30% => More preposition wanted as sentence beginning.

Performance on sentences:
How many sentences: 12.0 8.94146341463 134% => OK
Sentence length: 21.0 22.4926829268 93% => OK
Sentence length SD: 44.8531554693 43.030603864 104% => OK
Chars per sentence: 109.666666667 112.824112599 97% => OK
Words per sentence: 21.1666666667 22.9334400587 92% => OK
Discourse Markers: 4.41666666667 5.23603664747 84% => OK
Paragraphs: 3.0 3.83414634146 78% => More paragraphs wanted.
Language errors: 1.0 1.69756097561 59% => OK
Sentences with positive sentiment : 6.0 3.70975609756 162% => OK
Sentences with negative sentiment : 1.0 1.13902439024 88% => 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: 0.313173319977 0.215688989381 145% => OK
Sentence topic coherence: 0.103869238416 0.103423049105 100% => OK
Sentence topic coherence SD: 0.0765511611749 0.0843802449381 91% => OK
Paragraph topic coherence: 0.200751770352 0.15604864568 129% => OK
Paragraph topic coherence SD: 0.0697104184309 0.0819641961636 85% => OK

Essay readability:
automated_readability_index: 13.6 13.2329268293 103% => OK
flesch_reading_ease: 58.62 61.2550243902 96% => OK
smog_index: 8.8 6.51609756098 135% => OK
flesch_kincaid_grade: 10.3 10.3012195122 100% => OK
coleman_liau_index: 12.76 11.4140731707 112% => OK
dale_chall_readability_score: 9.03 8.06136585366 112% => OK
difficult_words: 70.0 40.7170731707 172% => OK
linsear_write_formula: 12.0 11.4329268293 105% => OK
gunning_fog: 10.4 10.9970731707 95% => OK
text_standard: 10.0 11.0658536585 90% => OK
What are above readability scores?

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Rates: 84.2696629213 out of 100
Scores by essay e-grader: 7.5 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.