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For this assignment, you will write a program that calculates some various text-leveling metrics of a document based on some of its characteristics. Read input from the user Do quite a bit of arithmetic calculation
There are many ways to generate a readability metric for a document. Some of these metrics include the Gunning Fog Score, the Flesch-Kincaid Reading Ease metric, the Flesch-Kincaid Grade Level, the SMOG Index, and the Automated Readability Index. Readability metrics do not indicate how well a reading will be understood by the target audience nor take into account the content of the material itself. Rather, the leveling method can only estimate which audience could be a target for the document. One application of generating readability metrics for documents or books is to enable teachers to determine what books would be appropriately challenging for a student in their class without taking into account the content of the material itself. By determining a student's individual reading level, teachers can also try to challenge students by suggesting books or documents that are above their current level. Given just a few pieces of information, we can determine the grade-level appropriateness of a given document. Your program will calculate various readability metrics for a document. NOTE: You will not actually be processing any text ( String ) data for this assignment. Rather, you will simply be reading numeric input from the user about statistics regarding a textual passage and then calculating the results.
Program 3 Overview
Goals
Overview
The Gunning Fog Index attempts to determine the upper elementary reading The Gunning Fog Index attempts to determine the upper elementary reading level of a document by calculating a weighted average of the number of words per sentence and the percentage of long words in the document. To calculate the Gunning Fog Index, use this formula:
For example, let's examine a 500-word sample with five 12-word sentences, ten 10-word sentences, ten 9word sentences, fifteen 8-word sentences, fifteen 6-word sentences and ten 4-word sentences. The document contains 60 "big words", which are words that have three or more syllables.
1. The number of words in the sample is 500.
2. The number of sentences in the sample is 65.
3. The average sentence length is 500.00 / 65.00 , or 7.6923076923.
4. The percentage of "big words" in the document is (60.0 / 500.0) * 100.0 , or 12.00.
5. The final calculation is (7.6923076923 + 12.00) * 0.40 , which is 7.87692307692. This means that this fictitious sample document has a reading level of approximately late 7th grade.

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