In the passage, the business manager of a television station argues for two causal relationships. First, he argues that less time to weather and local news increases viewer complaints on coverage. Second, he argues that less time to weather and local news decreases local business advertising, and subsequently less advertising revenue. Finally, he proposes that to correct these relationships, the time devoted to weather and local news should be restored. In order to evaluate the validity of this argument, specific evidence is required. I will address this issue in order of the two causal relationships.
To evaluate the first argument, evidence for the independent variable (time dedicated to weather and local news) is required. This would come in the form of time dedicated to national news, weather and local news before last year and throughout this year, to show the decrease in time dedicated to weather and local news. There would need to be a clear decrease in weather and local news coverage and an increase in national news coverage to sustain his argument. Second, there needs to be evidence for the dependent variable, to show viewer displeasure over the change in coverage. This could come in the form of number of complaints concerning coverage, or the change in the number of viewers. If the number of complaints increased after the change in coverage or the number of viewers decreased, then his argument would be supported.
To evaluate the second argument, there needs to be evidence for the second dependent variable, local business advertising. This requires evidence in the form of advertising revenue coming from local businesses from before and after the coverage change. If advertising revenue decreases with the coverage change, then his argument is strengthened.
To prove both causal relationships, we would also need to prove that there are no other independent variables that might cause the change in the number of viewers or the amount of advertising revenue. To do this, we would need evidence to control for factors such as economic growth, viewership of other television channels and coverage of local news and weather on other channels. For example, if I find that the local economy is down, it might explain why local businesses are cancelling advertising contracts. This would put the validity of the second causal relationship in dispute.
In conclusion, to evaluate the arguments put forth by the business manager, we need evidence relating to the independent variable, the dependent variable and other possible sources of change.
Transition Words or Phrases used:
also, finally, first, if, second, so, then, for example, in conclusion, such as
Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments
Performance on Part of Speech:
To be verbs : 11.0 19.6327345309 56% => More to be verbs wanted.
Auxiliary verbs: 15.0 12.9520958084 116% => OK
Conjunction : 17.0 11.1786427146 152% => OK
Relative clauses : 6.0 13.6137724551 44% => More relative clauses wanted.
Pronoun: 27.0 28.8173652695 94% => OK
Preposition: 67.0 55.5748502994 121% => OK
Nominalization: 14.0 16.3942115768 85% => OK
Performance on vocabulary words:
No of characters: 2173.0 2260.96107784 96% => OK
No of words: 413.0 441.139720559 94% => More content wanted.
Chars per words: 5.26150121065 5.12650576532 103% => OK
Fourth root words length: 4.50803742585 4.56307096286 99% => OK
Word Length SD: 2.85208646843 2.78398813304 102% => OK
Unique words: 156.0 204.123752495 76% => More unique words wanted.
Unique words percentage: 0.377723970944 0.468620217663 81% => More unique words wanted or less content wanted.
syllable_count: 690.3 705.55239521 98% => OK
avg_syllables_per_word: 1.7 1.59920159681 106% => OK
A sentence (or a clause, phrase) starts by:
Pronoun: 12.0 4.96107784431 242% => Less pronouns wanted as sentence beginning.
Interrogative: 0.0 0.471057884232 0% => OK
Article: 3.0 8.76447105788 34% => OK
Subordination: 3.0 2.70958083832 111% => OK
Conjunction: 2.0 1.67365269461 119% => OK
Preposition: 10.0 4.22255489022 237% => Less preposition wanted as sentence beginnings.
Performance on sentences:
How many sentences: 20.0 19.7664670659 101% => OK
Sentence length: 20.0 22.8473053892 88% => OK
Sentence length SD: 38.2158344145 57.8364921388 66% => OK
Chars per sentence: 108.65 119.503703932 91% => OK
Words per sentence: 20.65 23.324526521 89% => OK
Discourse Markers: 3.95 5.70786347227 69% => OK
Paragraphs: 5.0 5.15768463074 97% => OK
Language errors: 0.0 5.25449101796 0% => OK
Sentences with positive sentiment : 6.0 8.20758483034 73% => OK
Sentences with negative sentiment : 11.0 6.88822355289 160% => OK
Sentences with neutral sentiment: 3.0 4.67664670659 64% => OK
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.306115164295 0.218282227539 140% => OK
Sentence topic coherence: 0.110471656482 0.0743258471296 149% => OK
Sentence topic coherence SD: 0.116656982561 0.0701772020484 166% => OK
Paragraph topic coherence: 0.163748655911 0.128457276422 127% => OK
Paragraph topic coherence SD: 0.126770900067 0.0628817314937 202% => More connections among paragraphs wanted.
Essay readability:
automated_readability_index: 13.7 14.3799401198 95% => OK
flesch_reading_ease: 42.72 48.3550499002 88% => OK
smog_index: 8.8 7.1628742515 123% => OK
flesch_kincaid_grade: 12.3 12.197005988 101% => OK
coleman_liau_index: 13.23 12.5979740519 105% => OK
dale_chall_readability_score: 7.34 8.32208582834 88% => OK
difficult_words: 71.0 98.500998004 72% => More difficult words wanted.
linsear_write_formula: 7.0 12.3882235529 57% => Linsear_write_formula is low.
gunning_fog: 10.0 11.1389221557 90% => OK
text_standard: 14.0 11.9071856287 118% => OK
What are above readability scores?
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Rates: 58.33 out of 100
Scores by essay e-grader: 3.5 Out of 6 -- The score is based on the average performance of 20,000 argument essays. This e-grader is not smart enough to check on arguments.
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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.