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How to Read a Z Table for Standard Normal Probabilities

In statistics, how is a ztable​ used to find probabilities for the standard normal distribution, including right-tail and between-two-z computations?

Subject: Statistics Chapter: Continuous Random Variables and the Normal Distribution Topic: The Standard Normal Distribution Answer included
ztable​ z table standard normal table standard normal distribution z score cumulative probability normal CDF left-tail area
Accepted answer Answer included

A ztable​ is a standard normal table: it lists numerical values of the cumulative distribution function (CDF) for a standard normal random variable \(Z\sim N(0,1)\).

\[ \Phi(z)=P(Z\le z) \]

Two common ztable formats

  • Left-tail table: entries are \(\Phi(z)=P(Z\le z)\).
  • Mean-to-z table: entries are \(A(z)=P(0\le Z\le z)\) for \(z\ge 0\).

Conversions for \(z\ge 0\):

\[ \Phi(z)=0.5 + A(z), \qquad P(Z\ge z)=1-\Phi(z)=0.5-A(z) \]

Symmetry for any \(z\):

\[ \Phi(-z)=1-\Phi(z) \]

How to read a ztable (row and column)

  1. Write the z-score to two decimal places (or the precision used by the table).
  2. Use the row for the ones and tenths digits (for example, \(1.2\)).
  3. Use the column for the hundredths digit (for example, \(0.03\)).
  4. The table entry is the probability associated with that \(z\) (usually \(\Phi(z)\)).

Mini ztable excerpt (left-tail CDF)

The excerpt below illustrates how the row \(1.2\) and column \(0.03\) locate \(\Phi(1.23)\).

z 0.00 0.01 0.02 0.03 0.04
1.2 0.8849 0.8869 0.8888 0.8907 0.8925

Core probability computations using ztable values

1) Left-tail probability

If the table is a left-tail table, the entry is already the desired probability:

\[ P(Z\le 1.23)=\Phi(1.23)\approx 0.8907 \]

2) Right-tail probability

Right-tail areas use the complement rule:

\[ P(Z>1.23)=1-\Phi(1.23)\approx 1-0.8907=0.1093 \]

3) Between two z-scores

Areas between two values use subtraction:

\[ P(a\le Z\le b)=\Phi(b)-\Phi(a) \]

Example with \(a=-0.85\) and \(b=1.23\). Using symmetry, \(\Phi(-0.85)=1-\Phi(0.85)\approx 1-0.8023=0.1977\).

\[ P(-0.85\le Z\le 1.23)\approx 0.8907-0.1977=0.6930 \]

4) Two-tailed probability

Two-tailed areas are often written as:

\[ P(|Z|>z)=2\cdot P(Z>z)=2\cdot (1-\Phi(z)) \]

Example with \(z=1.96\), where a typical ztable gives \(\Phi(1.96)\approx 0.9750\):

\[ P(|Z|>1.96)\approx 2\cdot(1-0.9750)=2\cdot 0.0250=0.0500 \]

Visualization: ztable area as shaded standard normal probability

-3 0 1.23 3 shaded area = \( \Phi(1.23) \approx 0.8907 \)
The shaded region represents the left-tail probability \(P(Z\le 1.23)\). A ztable entry for \(z=1.23\) reports this cumulative area (or can be converted to it, depending on table format).

Practical checklist for ztable use

  • Confirm the table type: left-tail \(\Phi(z)\) versus mean-to-z \(A(z)\).
  • Handle negatives consistently: use symmetry \(\Phi(-z)=1-\Phi(z)\) when only nonnegative \(z\) values appear.
  • Use complements and differences: right tail \(1-\Phi(z)\); between two values \(\Phi(b)-\Phi(a)\).
  • Round z-scores appropriately: many tables are built for two decimals; interpolation is an optional refinement.
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