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Author Question: The Stanford Binet Intelligence Quotient is a normed intelligence test, and its IQ measures are ... (Read 170 times)

V@ndy87

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The Stanford Binet Intelligence Quotient is a normed intelligence test, and its IQ measures are quite normally distributed. Its standard deviation is 16. If the test were perfectly normal in its distribution, this would mean which of the following?
 
  (Select all that apply.)
  a. There are more people with IQs of 100 than any other number.
  b. For every person with an IQ of 120, there is one with an IQ of 80.
  c. More than 95 of people have IQs between 68 and 132.
  d. If someone's IQ is measured as 109, and years later it is measured as 112, someone else's IQ has dropped three points.
  e. About 14 of people have IQs between 117 and 132.
  f. Excluding people with IQs of exactly 100, half of the remainder have IQs lower than 100, and the other half have IQs higher than 100.

Question 2

The data set is: 2, 3, 6, 7, 12. A measure of dispersion is calculated, and it is about 3.5. What is this measure of dispersion?
 
  a. The difference score
  b. The variance
  c. The range
  d. The standard deviation



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alexisweber49

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Answer to Question 1

ANS: A, B, C, E, F
The normal curve is a perfectly symmetrical frequency distribution. The value at the exact center of a normal curve is the mean of the values. When a frequency distribution is shaped like the normal curve, we know that 34.13 of the subjects scored between the mean and 1 standard deviation above the mean and 34.13 of the subjects scored between the mean and 1 standard deviation below the mean. This means that 68.26 of the subjects scored between 1 and +1 standard deviations. Because the normal curve is perfectly symmetrical, it is known that 50 of the subjects scored above the mean, and 50 of the subjects scored below the mean. Furthermore, 95.44 of the subjects scored between 2 and +2 standard deviations.

Answer to Question 2

ANS: D
The definition of standard deviation (SD) is the average difference between the mean and each of the scores in the set. Standard deviation (SD) is a measure of dispersion that is the square root of the variance. SD is the most precise analysis technique for examining the distribution of scores. SD includes difference scores in its calculation but does not involve the use of standardized scores.




V@ndy87

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Reply 2 on: Jul 8, 2018
Thanks for the timely response, appreciate it


ricroger

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Reply 3 on: Yesterday
Wow, this really help

 

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