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Since
z-scores are for the Standard Normal Distribution, |
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Example (TI-83): Find the probability that a z-score is between
-1.5 and 2. That is, find P(-1.5 ≤ z ≤ 2). |
Find probability or area |
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Press 2nd VARS [DISTR]. Scroll down to 2:normalcdf( Press ENTER. |
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Enter -1.5,2) and press ENTER to get the answer .91044. The syntax is normalcdf(smaller z, larger z). |
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Since
z-scores are for the Standard Normal Distribution, |
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Example (TI-83): Find the z-score for an area of 0.25 to the left
of the z-score. |
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Press 2nd VARS [DISTR]. Scroll down to 3:invNorm Press ENTER. |
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Enter .25) and press ENTER to get the answer -.67. The syntax is invNorm(area to left of desired z). |
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Since
the IQs are NOT Standard Normal Distribution, |
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Example (TI-83): Adult IQs are normally distributed with µ = 100
and σ = 15. Find the probability that a randomly selected IQ is less
than 112. That is, find P(x < 112).
Since this is a continuous function, we have P(x < 112) = P(x ≤ 112). |
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Press 2nd VARS [DISTR]. Scroll down to 2:normalcdf( Press ENTER. |
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Enter -9999,112,100,15) The syntax is normalcdf(smaller, larger, µ, σ). Note:
The -9999 is used as the smaller
value to be at least 5 standard deviations from the mean. |
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Find the probability that a randomly
selected IQ is at least 122. That is, find
P(x ≥ 122). |
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Press 2nd VARS [DISTR]. Scroll down to 2:normalcdf( Press ENTER. |
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Enter 122,9999,100,15) The syntax is normalcdf(smaller, larger, µ, σ). Note:
The 9999 is used as the larger
value to be at least 5 standard deviations from the mean. |
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Find the probability that a randomly
selected IQ is between 112 and 122. |
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Press 2nd VARS [DISTR]. Scroll down to 2:normalcdf( Press ENTER. |
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Enter 112,122,100,15) and press ENTER The syntax is normalcdf(smaller, larger, µ, σ). |
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