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Q: How do you calculate a percent delayed from a percentile or standard score for example what is the percent delayed for a child scoring in the 5th percentile?

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You make a list of the grades, in descending order. Then you pick the top 10%; for example, if there are 50 students, you pick the top 5. To get the percentile, you look at the corresponding grade, in the position that corresponds to #5 in this example.

You can't convert that directly. To convert percentages - or any kind of numbers, for that matter - to percentile, you need to use the definition of percentile. For example, if you have a grade of 90%, you check how many other grades have less than 90%, and divide that by the total number of grades. Note that for example with a grade of 90%, your percentile can be anywhere between 0 and 100 - depending what grades OTHERS had.

centile [ˈsɛntaɪl]In mathematics, measurements, or statistics, it is another word for percentile, the ranking a value has within a statistical group. For example, the 99th percentile would be the highest, and 50th percentile most nearly the average.

example. a baby is in the 30th percentile for weight. that baby is bigger than 29 babies out of 100, and smaller than 69.

An example of delayed feedback is when a student hands in an assignment to their teacher, but the teacher waits a few days before providing feedback on it. This delay can make it challenging for the student to connect the feedback with the work they completed.

Developmentally delayed is not a disability, but is a result of a disability. For example an autistic child can be intelectually developmentally disabled or a child with spina bifida can be physically developmentally delayed

Each standard deviation represents a certain percentile. So if we use two decimal places, −3 is the 0.13th percentile, −2 the 2.28th percentile, −1 the 15.87th percentile, 0 the 50th percentile , +1 the 84.13th percentile, +2 the 97.72th percentile, and +3 the 99.87th percentile.The mean, median and mode are all the same it the distribution is normal.BUT WHY DOES THIS WORK? HOW DO YOU DO IT?The main idea to make all this work and understandable is that the area under the normal curve is one. So if you have a SD and a mean, you can find the z score.Then, using a calculator, or a table, or even sometimes just some rules you may have learned like the empirical rule, you can find the area to the left or right of any given z score. This area is actually a percentile!So for example, if convert a data point to a z - score using the mean and standard deviation ( The formula is z=(x-mean)/standard deviation, by the way), and I look up the probability of that z-score, and say it is .25. Then it is the 25th percentile.The table below gives you all the percentiles and their corresponding z scores.z-score percentile for normal distributionPercentilez-ScorePercentilez-ScorePercentilez-Score1-2.32634-0.412670.442-2.05435-0.385680.4683-1.88136-0.358690.4964-1.75137-0.332700.5245-1.64538-0.305710.5536-1.55539-0.279720.5837-1.47640-0.253730.6138-1.40541-0.228740.6439-1.34142-0.202750.67410-1.28243-0.176760.70611-1.22744-0.151770.73912-1.17545-0.126780.77213-1.12646-0.1790.80614-1.0847-0.075800.84215-1.03648-0.05810.87816-0.99449-0.025820.91517-0.954500830.95418-0.915510.025840.99419-0.878520.05851.03620-0.842530.075861.0821-0.806540.1871.12622-0.772550.126881.17523-0.739560.151891.22724-0.706570.176901.28225-0.674580.202911.34126-0.643590.228921.40527-0.613600.253931.47628-0.583610.279941.55529-0.553620.305951.64530-0.524630.332961.75131-0.496640.358971.88132-0.468650.385982.05433-0.44660.412992.326

You can calculate standard deviation by addin the numbers of data that are together and dividing that number by the amount pieces of data.THAT IS TOTALLY INCORRECT.What was answered above was the calculation for getting an (mean) average.If you take five numbers for example 1, 2, 3, 4, 5 then the (mean) average is 3.But the standard deviation between them is 1.58814 and the variance is 2.5Also the population std. deviation will be 1.41421 and the population variance will be 2.see standard-deviation.appspot.com/

The formula for calculating median on grouped data is L + I *(50% * N-F)/f L - lower limit of the median group I - group interval N - Number of frequency (total sum of frequencies in each group) F - cumulative freqency for the group before the median group f - frequency of the median group Since median is just the same as the 2nd quartile, we use 0.5 in place of 50% in the formula. We can tweak the formula a little bit to calculate any percentile. For example, if you want to calculate 35th percentile, change the formula to L + I *(35% * N-F)/f which is L + I *(0.35 * N-F)/f. Please note that L,I,F & f should reflect that of the group where the percentile falls. You can find this by these steps: 1) Calculate N * 0.35. Lets say N=50 then 50* 0.35 = 17.5. 2) Using cumulative frequency, identify the group where 17.5 falls. 3) Use L,I,F & f for that particular group in the formula L + I *(0.35 * N-F)/f

The percentile rank of a score is the percentage of scores in its frequency distribution that are lower than it. For example, a test score that is greater than 75% of the scores of people taking the test is said to be at the 75th percentile.Percentile ranks are commonly used to clarify the interpretation of scores on standardized tests. For the test theory, the percentile rank of a raw score is interpreted as the percentages of examinees in the norm group who scored below the score of interest.[1]Percentile ranks (PRs or "percentiles") are often normally distributed ("bell-shaped") while normal curve equivalents (NCEs) are uniform and rectangular in shape. Percentile ranks are not on an equal-interval scale; that is, the difference between any two scores is not the same between any other two scores whose difference in percentile ranks is the same. For example, 50 − 25 = 25 is not the same distance as 60 − 35 = 25 because of the bell-curve shape of the distribution. Some percentile ranks are closer to some than others. Percentile rank 30 is closer on the bell curve to 40 than it is to 20.The mathematical formula iswhere cfℓ is the cumulative frequency for all scores lower than the score of interest, ƒi is the frequency of the score of interest, and N is the number of examinees in the sample. If the distribution is normallydistributed, the percentile rank can be inferred from the standard score.

An IQ test is simply a (somewhat flawed) means of assessing a person's "relative intelligence". It is important that IQ is not extremely important when working with such a measure in psychology. Now, the IQ test is designed such that scores follow a pattern known as a "normal distribution". This is not simply an expected distribution! This distribution is very important in the study of statistics, and has many applications to scientific disciplines (such as psychology). A standard deviation is essentially a measure of distance from the mean. For example, say that the average person lives to be 75, with a standard deviation of 4. This means that a person who lives to be 79 would be one standard deviation above the mean, and a person who lives to be 67 would be two standard deviations below the mean. As a table depicting the normal distribution can show, one standard deviation above the mean is at the 84th percentile, while one standard deviation below the mean is at the 16th percentile (two stds above: 97.5th, two stds below: 2.5th) This means that an IQ score of 115 is at the 84th percentile, while an IQ score of 85 is at the 16th percentile. 68% of all people are within this range, and that is "most" people.