The indicated IQ score, x, is
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.
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**Find the Indicated IQ Score:**
The graph to the right depicts IQ scores of adults, and those scores are normally distributed with a mean of 100 and a standard deviation of 15.
Click to view page 1 of the table. Click to view page 2 of the table.
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**Question:**
The indicated IQ score, \( x \), is \(\_\_\_\_\_\_) (Round to one decimal place as needed)
Enter your answer in the answer box and then click Check Answer.
**All parts showing**
**Diagram Explanation:**
The diagram on the right is a normal distribution curve. A section on the curve is shaded in green, labeled with the value "0.55," indicating the probability or area under the curve associated with finding the indicated IQ score.
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**Buttons and Options:**
- **Check Answer**: Button to verify the entered answer.
- **Clear All**: Option to clear the entered data.
**Additional Tools:**
- Zoom and navigation tools are available (Magnifying glass and arrows).
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It is given that the mean and the standard deviation is 100 and 15, respectively.
That is, .
From the graph, .
It is known that . Then,
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