Cambridge book 7, test 3, task 1.
The following paragraphs will be comparing and contrasting the main features of the bar chart discussing the percentage change in real estate prices in 5 different cities over the 12- year period between 1990 and 2002 using the year 1989 as the benchmark.
Overall, the first six years between 1990 and 1996 showed a significant decrease in prices in all cities except for Madrid and Frankfurt, while in the second six years there was a marked growth in prices in all cities except for Frankfurt which showed a decrease in price and we’ll be discussing this in detail.
First of all, over the first period between 1990-1995 it can be seen that 3 out of 5 cities dropped in prices compared to the year 1989 and this can be seen more remarkably in both Tokyo and London that showed around -7% decrease in prices followed by NewYork with a -5% drop. On the other hand, there was an increase in prices in Madrid by around 1.5% and Frankfurt which showed the highest increase in prices by nearly +2%.
Moving on to the next 6 years between 1996-2002 we can clearly observe the significant increase in house prices in all the countries except for Frankfurt. Firstly, we can see that NY prices increased by +5% during this period with a total difference of around +10% from pre 1996. Secondly, Madrid which has risen to around 4.5% with a total difference of 3%. Moreover, Tokyo’s prices increased only by 2% compared to the prices of the pre 1996 period and yet its prices remained lower than the benchmark year. Furthermore, London showed a significant increase in prices and reached an increase of 11% during the post 1996 period with a total change of around 19% from the pre 1996 period making it ranking first in prices of real estate, while Frankfurt was the only city to show a decrease in prices of 1% in the post 1996 period. In conclusion, the preceding has been a discussion of the main feature of the bar chart discussing real estate prices in 5 cities where in the first 6 years we saw a net decrease in prices in 3 out of 5 cities, while in the second 6 years we saw a net growth in prices in 4 out of 5 cities.
Grammar and spelling errors:
Line 7, column 838, Rule ID: WHITESPACE_RULE
Message: Possible typo: you repeated a whitespace
Suggestion:
...n prices of 1% in the post 1996 period. In conclusion, the preceding has been a ...
^^
Transition Words or Phrases used:
first, firstly, furthermore, if, moreover, second, secondly, while, except for, in conclusion, first of all, on the other hand
Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments
Performance on Part of Speech:
To be verbs : 8.0 7.0 114% => OK
Auxiliary verbs: 5.0 1.00243902439 499% => Less auxiliary verb wanted.
Conjunction : 11.0 6.8 162% => OK
Relative clauses : 7.0 3.15609756098 222% => Less relative clauses wanted (maybe 'which' is over used).
Pronoun: 14.0 5.60731707317 250% => Less pronouns wanted
Preposition: 77.0 33.7804878049 228% => Less preposition wanted.
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: 1760.0 965.302439024 182% => OK
No of words: 387.0 196.424390244 197% => Less content wanted.
Chars per words: 4.54780361757 4.92477711251 92% => OK
Fourth root words length: 4.43534841618 3.73543355544 119% => OK
Word Length SD: 2.48961547336 2.65546596893 94% => OK
Unique words: 155.0 106.607317073 145% => OK
Unique words percentage: 0.400516795866 0.547539520022 73% => More unique words wanted or less content wanted.
syllable_count: 495.9 283.868780488 175% => OK
avg_syllables_per_word: 1.3 1.45097560976 90% => OK
A sentence (or a clause, phrase) starts by:
Pronoun: 1.0 1.53170731707 65% => OK
Article: 3.0 4.33902439024 69% => OK
Subordination: 3.0 1.07073170732 280% => Less adverbial clause wanted.
Conjunction: 0.0 0.482926829268 0% => OK
Preposition: 2.0 3.36585365854 59% => More preposition wanted as sentence beginning.
Performance on sentences:
How many sentences: 10.0 8.94146341463 112% => OK
Sentence length: 38.0 22.4926829268 169% => The Avg. Sentence Length is relatively long.
Sentence length SD: 84.9153107514 43.030603864 197% => OK
Chars per sentence: 176.0 112.824112599 156% => OK
Words per sentence: 38.7 22.9334400587 169% => OK
Discourse Markers: 12.6 5.23603664747 241% => Less transition words/phrases wanted.
Paragraphs: 4.0 3.83414634146 104% => OK
Language errors: 1.0 1.69756097561 59% => OK
Sentences with positive sentiment : 6.0 3.70975609756 162% => OK
Sentences with negative sentiment : 2.0 1.13902439024 176% => OK
Sentences with neutral sentiment: 2.0 4.09268292683 49% => OK
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.0 0.215688989381 0% => OK
Sentence topic coherence: 0.0 0.103423049105 0% => OK
Sentence topic coherence SD: 0.0 0.0843802449381 0% => Sentences are similar to each other.
Paragraph topic coherence: 0.0 0.15604864568 0% => OK
Paragraph topic coherence SD: 0.0 0.0819641961636 0% => 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: 19.4 13.2329268293 147% => OK
flesch_reading_ease: 58.29 61.2550243902 95% => OK
smog_index: 3.1 6.51609756098 48% => Smog_index is low.
flesch_kincaid_grade: 14.6 10.3012195122 142% => OK
coleman_liau_index: 9.7 11.4140731707 85% => OK
dale_chall_readability_score: 7.85 8.06136585366 97% => OK
difficult_words: 57.0 40.7170731707 140% => OK
linsear_write_formula: 26.0 11.4329268293 227% => Linsear_write_formula is high.
gunning_fog: 17.2 10.9970731707 156% => OK
text_standard: 10.0 11.0658536585 90% => OK
What are above readability scores?
---------------------
It is not exactly right on the topic in the view of e-grader. Maybe there is a wrong essay topic.
Rates: 11.2359550562 out of 100
Scores by essay e-grader: 1.0 Out of 9
---------------------
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.