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The Standard Normal Distribution

Statistics • Continuous Random Variables and the Normal Distribution

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Standard Normal Distribution (Z)

The standard normal distribution is the normal distribution with μ = 0 and σ = 1. A probability such as P(Z < z) is interpreted as an area under the curve. For a continuous random variable, P(Z = z) = 0, so including/excluding endpoints does not change the probability.

In X-mode, the calculator converts using z = (x − μ) / σ and then computes areas with the standard normal curve.

All areas are computed from the cumulative area to the left, then combined by subtraction/complements.

Z-table highlighting uses rounding to 2 decimals and then row/column selection.

Example: z = 1.95

Tip: Click a cell in the Z-table to set z.

Visualization: area under the standard normal curve

The shaded region corresponds to your probability (left tail, right tail, or between two z-values).

The curve is drawn on the z-scale (from about −3.8 to +3.8). Very extreme z-values have areas extremely close to 0 or 1.

Z-table (cumulative area to the left)

This table shows P(Z < z). For a continuous distribution, P(Z < z) and P(Z ≤ z) are the same.

This will highlight the corresponding row/column if it’s within ±3.49.

You can export the generated table as CSV, or upload/paste your own CSV in z,phi format.

If loaded, this custom mapping is used for lookup in “table-style” output (highlighting still uses the generated table grid).

Table layout: choose the row from the z-value rounded/truncated to one decimal, then choose the column from the hundredths place. For negative z, the table uses “more negative” values across columns.

Batch mode (paste/upload z values)

Paste a column of z values (or a CSV with a z column). The output is a CSV you can copy.

Accepted formats: one number per line, or CSV with first column as z, or a header row containing “z”.

Output columns: z, P_left, P_right

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Frequently Asked Questions

What is the standard normal distribution?

It is the normal distribution with mu = 0 and sigma = 1, usually written as Z. Probabilities such as P(Z < z) are areas under the curve to the left of z.

How do I convert X ~ N(mu, sigma) to a Z score?

Use z = (x - mu) / sigma with sigma > 0. After converting, you can compute left-tail, right-tail, or between probabilities using the standard normal curve.

How does the calculator compute right-tail probabilities like P(Z > z)?

It uses the complement of the left-tail cumulative area: P(Z > z) = 1 - Phi(z), where Phi(z) = P(Z < z).

How do I compute P(z1 < Z < z2) using the standard normal distribution?

After ordering so z1 < z2, the probability is Phi(z2) - Phi(z1). The calculator applies this subtraction and shows the steps and shaded area.

Why does the Z-table use rounding to 2 decimals even if I choose more decimals?

Many textbook Z-tables are indexed by z rounded to two decimals using a row and column lookup. The calculator keeps the table highlight and table-style reading consistent with that convention while allowing a more precise displayed result.