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Above Below Or Between

This page follows the JoeCMath video % Above, Below, or Between? (Normal Distribution). The video is a short overview of how to choose a method when a normal curve question asks for an area above a value, below a value, or between two values.

Main Idea

The video starts with the kind of decision students make before doing any arithmetic: what information did the problem give, and what region of the normal curve is being shaded?

The three region types are:

\[\text{below a value},\qquad \text{above a value},\qquad \text{between two values}.\]

Once the region is clear, the method depends on the labels in the problem. A z-score problem usually sends you to a z-table. A standard-deviation problem can often use the empirical rule. A quartile problem can use the $25\%$ chunks of the normal curve.

Watch this section: set up to normal distribution problem at 0:00.

Z-Score Approach

The first method in the video is the z-score approach. This is the flexible method for normal curve area questions because it turns the original value into a standard normal value:

\[z=\frac{x-\mu}{\sigma}.\]

After that, the z-table gives the left-tail area below the z-score. From there, the region controls the last step:

\[P(X<a)=\text{left-tail area at }a,\] \[P(X>a)=1-P(X<a),\]

and

\[P(a<X<b)=P(X<b)-P(X<a).\]

That is the heart of the above, below, or between decision. Below uses the table value directly. Above uses the complement. Between subtracts two left-tail areas.

Watch this section: z-score approach to solving problem at 0:15.

Standard-Deviation Template

The second method in the video is the standard-deviation normal distribution template. This is useful when the marked values are exactly one, two, or three standard deviations from the mean.

For a normal distribution, the empirical-rule areas are:

\[P(\mu-\sigma<X<\mu+\sigma)\approx 68\%,\] \[P(\mu-2\sigma<X<\mu+2\sigma)\approx 95\%,\]

and

\[P(\mu-3\sigma<X<\mu+3\sigma)\approx 99.7\%.\]

The template also gives the smaller slices. For example, the area from the mean to one standard deviation above the mean is about $34\%$, and the area from one to two standard deviations above the mean is about $13.5\%$.

So if a shaded region is built from standard-deviation marks, the video points you toward the template instead of forcing a z-table calculation.

Watch this section: using standard deviation normal distribution template at 0:41.

Quartile Template

The third method in the video is the quartile normal distribution template. Quartiles split the distribution into four equal area pieces:

\[25\%,\qquad 25\%,\qquad 25\%,\qquad 25\%.\]

That means

\[P(X<Q_1)=25\%,\] \[P(Q_1<X<Q_3)=50\%,\]

and

\[P(X>Q_3)=25\%.\]

The video also connects the quartile marks to the standard normal scale. For a normal distribution, the first quartile is close to

\[z=-0.67,\]

and the third quartile is close to

\[z=0.67.\]

So when the problem names $Q_1$, $Q_3$, or quartiles directly, the area may be available from the quartile structure before opening a z-table.

Watch this section: using quartile normal distribution template at 1:14.

Choosing The Method

The video is really about choosing the shortest honest path. Start by naming the region, then use the information the problem gives.

Problem clue Method to try What to do
A raw value $x$, mean $\mu$, and standard deviation $\sigma$ Z-score approach Convert with $z=\dfrac{x-\mu}{\sigma}$, then use the z-table.
A mark like $\mu+\sigma$ or $\mu-2\sigma$ Standard-deviation template Use the empirical-rule areas and slices.
A mark like $Q_1$, $Q_2$, or $Q_3$ Quartile template Use the $25\%$ sections of the distribution.
A region above a value Complement Find the area below first, then subtract from $1$.
A region between two values Difference of left tails Find both left-tail areas, then subtract.

Watch this section: normal curve area overview at 0:00.

Timestamp Guide

Section Main idea Video
Set up Decide whether the region is above, below, or between. 0:00
Z-score approach Convert to $z$, then use table areas below, above, or between. 0:15
Standard-deviation template Use the empirical-rule template when the marks are built from $\sigma$. 0:41
Quartile template Use $Q_1$ and $Q_3$ as $25\%$ and $75\%$ cut points. 1:14

If the problem gives raw data values, start with why we convert to z-scores.

If you need table values for above, below, or between regions, use the z-table notes.

If the marks are one, two, or three standard deviations from the mean, review the empirical rule notes.

For the smaller $34\%$, $13.5\%$, $2.35\%$, and $0.15\%$ regions inside the empirical-rule template, use the normal curve percentages notes.

You can also browse the Normal Distribution notes or watch the full JoeCMath normal distribution playlist on YouTube.


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