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IQ scores are normally distributed with a mean of 100 and a standard deviation of 15 If a certain statistician has an IQ of 140 what percent of the population has an IQ less than she does?
99.6% for
IQ test scores are normally distributed with a mean of 100 and a standard deviation of 15 An individual's IQ score is found to be 110 Find the z-score corresponding to this value?
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
What does a bell curve of IQ look like?
The "bell curve" of anything, with the peak of the curve supposedly at a score of 100.
What is a single peaked distribution in statistics?
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.
Iq scores normally distributed with mean of 100 and standard deviation of 15 how many between 85 and 120 in sample 0f 7000?
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.
