99.6% for
mean= 100 standard deviation= 15 value or x or n = 110 the formula to find the z-value = (value - mean)/standard deviation so, z = 110-100/15 = .6666666 = .6667
The "bell curve" of anything, with the peak of the curve supposedly at a score of 100.
The classic example is a Bell curve. IQ testing (using the WAIS, or Wechsler Adult Intelligence Scale) yields a peak at the 100-105 IQ mark, with a downward curve on either side of the peak - representing the higher and lower IQ scores, respectively.
The variability of IQ within a population, as with many other measurable characteristics subject to manifold influences (e.g. the height and weight of individuals), appears to follow what is referred to as the normal (gaussian) distribution, otherwise known colloquially as the the bell curve. The area under this curve from one standard deviation below the mean to one standard deviation above the mean is very close to two thirds. More accurately it is about 0.6827. So the answer to your question is 7000 x 0.6827 = 4779. John Smith ---- Hi John Smith, Your answer works for the range of 85 to 115, but the question asked about the range of 85 to 120. I would tackle it this way: First, I would assess the Z-scores for both 85 and 120 with a mean of 100 and standard deviation of 15. The Z-score is the area under the normal curve including and to the left of the statistic in question. Or perhaps more clearly defined, it is the percent chance that your test statistic, or any statistic less than it, has of occurring in the given distribution. The Z-score for 85 in this distribution is 0.158655, and the Z-score for 120 is 0.908788. However, since the score for 120 accounts for everything less than and including 120, it already accounts for the chance of 85 occurring. So, since we know the chance of anything less than or including 85 occurring, we can subtract this from the Z-score for 120 to get the chance of finding a statistic within the range of 85-120. This percentage is 0.750133. Now, our sample size is 7000, and we know that 75.0133% of that sample falls within the range in question, so simply multiply the two to get the answer: 7000 x 0.750133 = approximately 5251 people.
US IQ standard Deviation is 16.
it is shaped roughly like a bell... a bell curve.
100 is the average with a standard deviation of 15.
The average IQ for a student in the UK is around 100, which is considered to be in the normal range. IQ scores are standardized to have a mean of 100 and a standard deviation of 15.
an IQ of 132 in SD (standard deviation) of 16 and 130 in a SD of 15 , this mean top 2% of world's population according to the bell curve..for more info , search in google.
The average IQ of a normal human being is considered to be around 100, with a standard deviation of 15. This means that most people fall within the range of 85 to 115 on the IQ scale, which is considered to be within the normal or average range of intelligence.
It depends to some extent on how you define "average". Most modern IQ tests are designed to give a normal distribution curve, meaning that 2/3 of the people will score within one standard deviation of the mean. (On the Stanford-Binet test, this means between 85 and 115).
IQ is distributed normally, with a mean of 100 and a standard deviation of 15. The z-score of 100 is therefore:(value-mean)*standard deviation= (100-100)*15= 0More generally, a raw score that is equivalent to the mean of a normal distribution will always have a z-score of 0.
What an IQ of 145 means really depends on the test. On some tests it might means that you are smarter than 99.85% of the population, on others it might mean that you are brighter than about 80% of the population. Modern IQ tests tend to be designed to give a normal distribution of scores with 100 as the mean. A normal distribution is a bell shape, so that the closer the IQ is to 100, the more people there are with that IQ. Exactly how many for a given IQ depends on something called the standard deviation. About two thirds of people have an IQ within 1 standard deviation of 100 (the mean). For example, IQ tests commonly have a standard deviation of about +/-15. This means about two thirds of people have an IQ between 85 and 115. You might call this the average range. About 95% of people will be within two standard deviations, so using the same example, about 95% of people will have an IQ between 70 and 130. And 99.7% within 3 standard deviations. So, on an IQ test with a standard deviation of +/-15, you might say that people with an IQ of 130 or more are above average (in the top 15% or so), and if your IQ is 145 then you are in the top 0.15% of the population. However, the standard deviation depends on the test. Standard deviations on common tests range from 10 to 24. Because of this, these days psychologists tend to talk of percentile ranges when talking about IQ with a certain confidence interval. So, you would be far more likely to be told that your IQ is in the 94% percentile range with a confidence interval of 90%
IQ Test
The average IQ score for the general population is around 100, with most people falling within the range of 85 to 115. This range is considered to be within the normal or average intelligence level. IQ tests are designed to have a mean score of 100 and a standard deviation of 15.
It doesn't really work that way, but: a 447 on the MAT is actually pretty good. The average score is 400 with a standard deviation of 25, so 447 is not quite two standard deviations above average.Modern IQ scores have an average of 100 with a standard deviation of about 15, so a person who got a 447 on the MAT placed in roughly the same part of the bell curve as a person scoring in the mid-to-upper 120s on an IQ test.