The Flesch Reading Ease Test is a test that ranks the reading level of passages.t Let W be the total number of words in the passage, S the number of sentences, and L the number of syllables. Then the Flesch test calculates the score F of the passage using the formula F = 206.835 – 1.015W - 84.6. – 84.6- w (a) Calculate F for the paragraph above (the one that describes the Flesch Reading Ease Test). Omit the formula itself. Round your answer to the nearest whole number. (We count 3 sentences, 51 words, and 71 syllables.) F = 71.80 (b) For the rest of this exercise we consider passages that have 10 sentences and 375 syllables. Find a formula expressing F as a function of W for such passages. 29610 F = 206.835 – 0.105W- W (c) A passage is thought to be easily understandable by 13- to 15-year-old students if the Flesch score, rounded to one decimal place, is 60 or higher. For the passages considered in part (b), how many words should be in the passage to make it easily understood by 13- to 15-year-old students? Suggestion: First use a table increment of 20 to get an estimate of the answer. Then change to a table increment of 1. 243 X words (d) What is the maximum number of words in the passages considered in part (b)? (Can there be more words than syllables?) 350 X words

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Inverse Normal Distribution

The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.

Mean, Median, Mode

It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.

Z-Scores

A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.