How to Read a Z-Table

Learning how to read a z table is one of the fastest skills in statistics: once you can read one row and one column, you can turn any z-score into a probability in seconds. A z-table — also called a standard normal table, a z-score table, or a normal distribution table — lists the area under the standard normal curve for z-scores from 0.00 to 3.49. This guide shows you the three table layouts, the exact lookup steps for left-tail, right-tail, and between-values problems, negative z-scores, and reverse lookup, with worked examples you can check against the full printable table at the end.

If you do not have a z-score yet, learn how to calculate a z-score in our companion guide first, or use the z-score calculator to get one. Then come back here to look it up.

What Is a Z-Table?

A z-table is a printed table of the standard normal distribution — the bell curve with mean 0 and standard deviation 1. For each z-score, the table gives the area under that curve, which is a probability. Because the total area under the curve is 1, every area the table gives is a number between 0 and 1, and it can always be read as a percentage.

For example, the table says the area to the left of z = 1.25 is 0.8944. That means 89.44% of values in a standard normal distribution fall below a z-score of 1.25. The same idea works for test scores, heights, IQ scores, and any data that is approximately normal: convert a raw score to a z-score, then read the probability from the z-table.

A z-table chart usually prints z-scores in rows and columns. The row gives the z-score to one decimal place (0.0, 0.1, 0.2, and so on), and the column gives the second decimal place (0.00 to 0.09). The cell where a row and a column meet is the probability. That row-and-column structure is the whole trick — and the most common source of mistakes, as the common mistakes section below shows.

The 3 Z-Table Layouts (and How to Convert Between Them)

Not all z-tables print the same area. Before you read a value, check which layout your table uses — a 0.8413 in one layout is a 0.3413 in another. The three layouts are:

  • Cumulative table (most common): gives the area to the left of z, written Φ(z). For z = 1.00, it reads 0.8413.
  • Mean-to-z table: gives the area between the mean (z = 0) and z. For z = 1.00, it reads 0.3413.
  • Right-tail table: gives the area to the right of z. For z = 1.00, it reads 0.1587.

All three describe the same curve, so you can convert between them with simple arithmetic:

If your table givesLeft area Φ(z)Mean-to-z areaRight-tail area
Left area Φ(z) = AAA − 0.50001 − A
Mean-to-z area = B0.5000 + BB0.5000 − B
Right-tail area = C1 − C0.5000 − CC

Check it with z = 1.00: the cumulative table says 0.8413, so the mean-to-z area is 0.8413 − 0.5000 = 0.3413, and the right tail is 1 − 0.8413 = 0.1587. The printable table at the end of this page is a cumulative table, and every worked example below uses that layout unless it says otherwise.

How to Use a Z-Table

Follow these four steps for every lookup:

  1. Get your z-score. If you have a raw score x from a normal distribution with mean μ and standard deviation σ, convert it with z = (x − μ) / σ. Our free z-score tool does this for you.
  2. Split the z-score into a row and a column. The row is the z-score to one decimal place; the column is the second decimal place. For z = 1.25, the row is 1.2 and the column is 0.05.
  3. Find the row and column in the table. Run your finger along the 1.2 row until you reach the 0.05 column. The number in that cell is your answer.
  4. Read the value and name the area. In a cumulative table, the cell is the area to the left of z — the probability that a value is below your z-score. For z = 1.25, the cell reads 0.8944, so 89.44% of the distribution lies below it.

That is all there is to it. The rest of this guide applies those four steps to each kind of question a z-table can answer.

Standard normal curve showing a z-table lookup for z equals 1.25, with 89.44 percent of the area to the left

How to Read a Z-Table for Left Tail

The left tail is the area to the left of a z-score — the most common question, because a cumulative z-table gives it directly. Worked example with z = 1.25:

  1. Split z = 1.25. Row 1.2, column 0.05.
  2. Find the cell. In the 1.2 row, under the 0.05 column, the table reads 0.8944.
  3. Read the answer. The area to the left of z = 1.25 is 0.8944, so P(Z < 1.25) = 0.8944, or 89.44%.

Two more left-tail lookups using the same steps:

  • z = 1.00: row 1.0, column 0.00 → 0.8413. So 84.13% of the distribution lies below z = 1.00.
  • z = 1.09: row 1.0, column 0.09 → 0.8621. So P(Z < 1.09) = 0.8621, or 86.21%.

Check any left-tail answer instantly with our z-score to percentile converter — enter the z-score and it returns the same percentile the table gives.

Z-Table Negative Z-Score

Many printed tables only list positive z-scores. For a negative z-score, use the symmetry of the bell curve: the area to the left of −z equals the area to the right of +z, so Φ(−z) = 1 − Φ(z).

Worked example, z = −1.25: the table gives Φ(1.25) = 0.8944, so Φ(−1.25) = 1 − 0.8944 = 0.1056. Only 10.56% of the distribution lies below z = −1.25.

The same rule works in reverse: the area to the right of a negative z-score equals the area to the left of its positive twin. For example, the area to the right of z = −1.00 is 0.8413, because the area to the left of z = +1.00 is 0.8413.

Never read a negative z-score from the positive side of the table without subtracting from 1 — that is the single most common z-table error.

How to Find Probability from Z-Table

A cumulative z-table gives the left tail directly. Every other probability is one subtraction away:

  • Left tail, P(Z < z): read the cell. P(Z < 1.25) = 0.8944.
  • Right tail, P(Z > z): 1 − the cell. P(Z > 1.25) = 1 − 0.8944 = 0.1056.
  • Between two values, P(a < Z < b): Φ(b) − Φ(a). See the next section.
  • Outside two values: 1 − the between area.

Worked example — a hypothesis test with z = 2.25. The table gives Φ(2.25) = 0.9878, so the right-tail probability is 1 − 0.9878 = 0.0122. That is the one-tailed p-value. For a two-tailed test, double it: p = 2 × 0.0122 = 0.0244. If you want to skip the table, our p-value calculator from z-score gives the same result, and the left/right tail probability calculator checks any left- or right-tail area.

Z-Table Between Two Values

To find the probability between two z-scores, look up both and subtract the smaller area from the larger one: P(a < Z < b) = Φ(b) − Φ(a).

Worked example — between z = −1 and z = +1: Φ(1.00) = 0.8413 and Φ(−1.00) = 1 − 0.8413 = 0.1587, so P(−1 < Z < 1) = 0.8413 − 0.1587 = 0.6827. That is the familiar 68.27% from the empirical rule — about 68% of values fall within one standard deviation of the mean.

Worked example — between z = 1.00 and z = 1.25: Φ(1.25) − Φ(1.00) = 0.8944 − 0.8413 = 0.0531, so 5.31% of values fall between those two z-scores.

Always subtract in the right order: the larger z-score’s area minus the smaller z-score’s area. Subtracting the other way gives a negative probability, which is impossible — a quick sign check that catches the error.

Reverse Z-Table Lookup

Reverse lookup works backwards: you know the probability and need the z-score. Instead of matching a row and column to a cell, scan the body of the table for the probability closest to your target, then read off its row and column.

Target probabilityNearest table valuez-score
0.90 (left tail)0.8997+1.28
0.975 (left tail)0.9750+1.96
0.05 (left tail)0.0500 (as 1 − 0.9500)−1.645

Worked examples: for a 90th percentile, look for 0.9000 in the table; the closest value is 0.8997 at row 1.2, column 0.08, so z ≈ +1.28. For the middle 95% of a normal distribution, the upper cut-off is the 97.5th percentile: the table shows 0.9750 at z = +1.96. For a 5% left tail, find 0.9500 (z = +1.645) and flip the sign: z = −1.645.

These are the critical values used everywhere in statistics: ±1.645 for 90% confidence, ±1.96 for 95% confidence, and ±2.58 for 99% confidence (the table gives Φ(2.58) = 0.9951, the 99.5th percentile). For exact values without scanning the table, use our probability to z-score tool.

Z-Table vs Z-Score Calculator

A z-table and a z-score calculator answer different halves of the same question. A z-score calculator turns a raw score into a z-score; a z-table turns a z-score into a probability. Use the table when you are learning, when you are in an exam without a calculator, or when you want to see how probabilities change as z grows. Use a calculator when you need more than four decimals, when your z-score has more than two decimal places, or when you are checking a table answer. The z-score graph plotter shows the same area on the curve, which makes the table’s numbers visual. Both routes should agree: if the table says 0.8944 for z = 1.25, the calculator should say the same.

Common Mistakes When Reading a Z-Table

  • Reading the wrong layout. Check whether your table gives the left area, the mean-to-z area, or the right tail before you read a single value. A mean-to-z table says 0.3413 where a cumulative table says 0.8413 for the same z = 1.00.
  • Mixing up the row and column. For z = 1.25, the row is 1.2 and the column is 0.05 — not row 1.5, column 0.02. The first decimal is the row; only the second decimal is the column.
  • Forgetting the negative sign. A negative z-score needs Φ(−z) = 1 − Φ(z). Reading Φ(1.25) = 0.8944 for z = −1.25 gives 0.8944 instead of the correct 0.1056.
  • Subtracting the wrong way round. Between two values, always subtract the smaller area from the larger one. A negative probability means the subtraction is backwards.
  • Reading a probability as a z-score. In reverse lookup, scan the body of the table for the probability, then read the row and column. The number in the body is never the z-score.
  • Rounding too early. Keep four decimals through your working and round only the final answer.

Why Do Z-Tables Only Go Up to 3.49?

Because beyond z = 3.49, the cumulative probability is 0.9998 or more — the area is so close to 1 that four-decimal tables cannot show any further change. The chance of a value beyond z = 3.49 is less than 0.02%, so tables stop there and calculators take over for extreme values.

What Is the Difference Between a Z-Table and a Normal Distribution Table?

There is none — a normal distribution table is another name for a z-table. Both list areas under the standard normal curve. The only real difference is the layout: some tables print the cumulative (left-tail) area, others print the mean-to-z area or the right tail. Check the layout first, using the conversion table above, and any of them will give the same answer.

Can a Z-Table Give a P-Value?

Yes. A p-value is a tail probability, and a z-table gives tail probabilities. For a one-tailed test, the p-value is the area beyond your z-score: for z = 2.25, p = 1 − 0.9878 = 0.0122. For a two-tailed test, double it: p = 0.0244. If that p-value is below your significance level (usually 0.05), the result is statistically significant.

Z-Table 0.00 to 3.49 Printable

Below is the full cumulative z-table: the area to the left of each z-score, Φ(z), to four decimals. Find your z-score’s row (first decimal) and column (second decimal). For negative z-scores, use Φ(−z) = 1 − Φ(z). Nine anchor values to check: z = 0.00 → 0.5000, z = 0.50 → 0.6915, z = 1.00 → 0.8413, z = 1.25 → 0.8944, z = 1.96 → 0.9750, z = 2.00 → 0.9772, z = 2.58 → 0.9951, z = 3.00 → 0.9987, and z = 3.49 → 0.9998.

z0.000.010.020.030.040.050.060.070.080.09
0.00.50000.50400.50800.51200.51600.51990.52390.52790.53190.5359
0.10.53980.54380.54780.55170.55570.55960.56360.56750.57140.5753
0.20.57930.58320.58710.59100.59480.59870.60260.60640.61030.6141
0.30.61790.62170.62550.62930.63310.63680.64060.64430.64800.6517
0.40.65540.65910.66280.66640.67000.67360.67720.68080.68440.6879
0.50.69150.69500.69850.70190.70540.70880.71230.71570.71900.7224
0.60.72570.72910.73240.73570.73890.74220.74540.74860.75170.7549
0.70.75800.76110.76420.76730.77040.77340.77640.77940.78230.7852
0.80.78810.79100.79390.79670.79950.80230.80510.80780.81060.8133
0.90.81590.81860.82120.82380.82640.82890.83150.83400.83650.8389
1.00.84130.84380.84610.84850.85080.85310.85540.85770.85990.8621
1.10.86430.86650.86860.87080.87290.87490.87700.87900.88100.8830
1.20.88490.88690.88880.89070.89250.89440.89620.89800.89970.9015
1.30.90320.90490.90660.90820.90990.91150.91310.91470.91620.9177
1.40.91920.92070.92220.92360.92510.92650.92790.92920.93060.9319
1.50.93320.93450.93570.93700.93820.93940.94060.94180.94290.9441
1.60.94520.94630.94740.94840.94950.95050.95150.95250.95350.9545
1.70.95540.95640.95730.95820.95910.95990.96080.96160.96250.9633
1.80.96410.96490.96560.96640.96710.96780.96860.96930.96990.9706
1.90.97130.97190.97260.97320.97380.97440.97500.97560.97610.9767
2.00.97720.97780.97830.97880.97930.97980.98030.98080.98120.9817
2.10.98210.98260.98300.98340.98380.98420.98460.98500.98540.9857
2.20.98610.98640.98680.98710.98750.98780.98810.98840.98870.9890
2.30.98930.98960.98980.99010.99040.99060.99090.99110.99130.9916
2.40.99180.99200.99220.99250.99270.99290.99310.99320.99340.9936
2.50.99380.99400.99410.99430.99450.99460.99480.99490.99510.9952
2.60.99530.99550.99560.99570.99590.99600.99610.99620.99630.9964
2.70.99650.99660.99670.99680.99690.99700.99710.99720.99730.9974
2.80.99740.99750.99760.99770.99770.99780.99790.99790.99800.9981
2.90.99810.99820.99820.99830.99840.99840.99850.99850.99860.9986
3.00.99870.99870.99870.99880.99880.99890.99890.99890.99900.9990
3.10.99900.99910.99910.99910.99920.99920.99920.99920.99930.9993
3.20.99930.99930.99940.99940.99940.99940.99940.99950.99950.9995
3.30.99950.99950.99950.99960.99960.99960.99960.99960.99960.9997
3.40.99970.99970.99970.99970.99970.99970.99970.99970.99970.9998

Tip: to check any value in this table, enter the z-score in our z-score to percentile tool — it should match the table to four decimals.

Frequently Asked Questions

How do you read a z-table step by step?

Split the z-score into a row (first decimal) and a column (second decimal), then read the cell where they meet. For z = 1.25, row 1.2 and column 0.05 give 0.8944 — the area to the left of z = 1.25.

What does 0.8413 mean in a z-table?

It is the area to the left of z = 1.00: 84.13% of values in a standard normal distribution fall below a z-score of 1.00. The same z-score gives a mean-to-z area of 0.3413 and a right-tail area of 0.1587.

How do you read a z-table for a negative z-score?

Use symmetry: Φ(−z) = 1 − Φ(z). Look up the positive z-score and subtract from 1. For z = −1.25, Φ(−1.25) = 1 − 0.8944 = 0.1056.

How do you find the probability between two z-scores?

Look up both values and subtract the smaller area from the larger one: P(a < Z < b) = Φ(b) − Φ(a). Between z = −1 and z = +1, that is 0.8413 − 0.1587 = 0.6827.

How do you do a reverse z-table lookup?

Find the probability inside the body of the table and read its row and column as the z-score. The closest value to 0.9000 is 0.8997, at row 1.2 and column 0.08, so z ≈ +1.28. A probability of 0.9750 gives z = +1.96.

What is the z-score for the 95th percentile?

About +1.645. The table shows 0.9495 at z = 1.64 and 0.9505 at z = 1.65, so the 95th percentile sits between them, at z ≈ 1.645.

Is a z-table the same as a standard normal table?

Yes. “Standard normal table”, “z-score table”, “z-table chart”, and “normal distribution table” are all names for the same table. Only the layout can differ — cumulative, mean-to-z, or right-tail — so check which area your table prints before you read it.

When should I use a z-table instead of a calculator?

Use the table when you are learning, revising, or in an exam where only a printed table is allowed. Use a calculator when your z-score has more than two decimal places, when you need more than four decimals of precision, or when you want to check a table answer.

Conclusion

Reading a z-table comes down to three things: know your table’s layout, split the z-score into a row and a column, and name the area you just read. With those steps, z = 1.25 always gives 0.8944, a negative z-score is one subtraction away, and a probability between two values is a subtraction of two lookups. Keep the printable table above handy, and check every answer with the percentile converter or the probability to z-score converter until the steps feel automatic.

Reference: the standard normal distribution and its tables are documented in the NIST/SEMATECH e-Handbook of Statistical Methods.

Check Tools

Try these free tools to check your z-table answer or skip the table altogether:

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