Skip to content
SAMATICA
In this chapter: Statistics and probability
  1. Entering data in STAT mode
  2. Mean, standard deviation, variance and quartiles from your data
  3. Regression
  4. Z-scores from your data
  5. Normal distribution
  6. Student-t, chi-square and F distributions
  7. Binomial, Poisson and geometric probabilities

Z-scores from your data: →t and the P, Q and R functions in Scientific calculator plus 991 for Android

The Distribution tab of the STAT menu has four functions. →t converts a value from the data in the editor into its standard score, the z-score: the value minus the mean, divided by the population standard deviation σx. P(t), Q(t) and R(t) then give an area under the standard normal curve: to the left of t, between 0 and t, and to the right of t. P(1.5) is 0.93319279873.

Standard score
value, then →t: (x − x̄) ÷ σx
Left tail
P(t), the area left of t
From the middle
Q(t), the area between 0 and t
Right tail
R(t), the area right of t: 1 − P(t)

A standard score says where a value sits in its data, counted in standard deviations from the mean: 0 at the mean, 1 one standard deviation above it, −1 one below. On the calculator, →t works it out from the data in the editor, and P, Q and R turn it into a probability read off the standard normal curve.

The Distribution tab

In STAT mode, press SHIFT 1 STAT and go to the Distribution tab. It holds four functions: P(t), Q(t) and R(t), which take a value t and return an area, and →t, which makes that t from a data value.

The Distribution tab of the STAT menu: P(t), Q(t), R(t) and →t, each with the part of the curve it measures.
The Distribution tab of the STAT menu: P(t), Q(t), R(t) and →t, each with the part of the curve it measures.

→t: the standard score of a data value

→t is postfix: the value comes first, as in 2→t. It converts a value x into its standard score by subtracting the mean of the entered x values and dividing by their population standard deviation, σx. So a value one standard deviation above the mean becomes 1, one below becomes −1, and the mean itself becomes 0, whatever the original units were.

The manual's example uses the nine values 1, 2, 2, 3, 3, 3, 4, 4 and 5, entered in 1-VAR with a Frequency column as on the statistics editor. The answers here are decimals, with numeric calculation on (DECI on the status line; see decimals for probabilities):

The data
in
xFrequency
1 1
2 2
3 3
4 2
5 1

How to find the standard score of a data value

  1. With the data in the editor, press AC to go to the calculation screen, and type the value: 2.

  2. Press SHIFT 1 STAT, choose →t on the Distribution tab, then press =.

The standard score of 2

in 2→t

out -0.86602540378

The mean of this data is 3 and σx is 1.15470053838, as the 1-VAR screen shows, so 2 sits a little under one standard deviation below the mean.

2, then →t and =, with the manual's data in the editor.
2, then →t and =, with the manual's data in the editor.

Then turn that score into a probability: press SHIFT 1 STAT again, choose P(t) on the Distribution tab, which types P( on the input line, then press Ans ) =:

The area to the left of that score

in P(Ans)

out 0.19323811539

That is the share of a normal curve with this mean and standard deviation that lies below 2: an estimate from the model, not a count of the nine values themselves.

P(t): the area to the left

P(t) is the area to the left of t, everything from −∞ up to it: the probability that a value falls below t.

−4−224 −0.10.10.20.30.40.5
P(1.5): the area under the standard normal curve to the left of 1.5.

At t = 1.5 the shaded part is almost all of the curve:

The area to the left of 1.5

in P(1.5)

out 0.93319279873

P(0) is exactly 0.5, since half the curve lies either side of the mean.

Q(t): the area from the middle

Q(t) is the area between the mean and t, from 0 out to it: the probability that a value falls between the centre of the curve and t.

−4−224 −0.10.10.20.30.40.5
Q(1.5): the area between 0 and 1.5.

The same t = 1.5, measured from the middle instead. It is exactly P(1.5) − 0.5:

The area between 0 and 1.5

in Q(1.5)

out 0.43319279873

Q measures from the middle outward on whichever side t lies, and the curve is symmetric, so a negative t gives the same answer as its positive twin: Q(−1.5) is 0.43319279873 as well. Q(0) is 0, there being no width to measure.

R(t): the area to the right

R(t) is the area to the right of t, from t out to +∞: the probability that a value falls above t. It is what is left of the curve after P, so R(t) = 1 − P(t).

−4−224 −0.10.10.20.30.40.5
R(1.5): the tail to the right of 1.5.
The area to the right of 1.5

in R(1.5)

out 0.06680720127

The curve is symmetric, so R(−t) equals P(t): R(−1.5) is 0.93319279873.

Which to use

You wantUse
The standard score of a data valueThe value, then →t
The chance of falling below tP(t)
The chance of falling above tR(t)
The chance of falling between the mean and tQ(t)
A normal curve with another mean and standard deviationnormalcdf, on SHIFT 3 DISTR

At a glance

KeysWhat they give
SHIFT 1 STAT, Distribution, P(t)The area left of t
SHIFT 1 STAT, Distribution, Q(t)The area between 0 and t
SHIFT 1 STAT, Distribution, R(t)The area right of t
A value, then SHIFT 1 STAT, Distribution, →tIts standard score in the entered data

Questions

How do I find a z-score on the calculator?

Enter the data in STAT mode, press AC to leave the editor, type the value, then choose →t on the Distribution tab of the STAT menu (SHIFT 1) and press =. →t comes after the value, as in 2→t. It subtracts the mean of the data and divides by its population standard deviation σx, so a value one standard deviation above the mean gives 1.

What is the difference between P, Q and R?

All three measure an area under the standard normal curve, each over a different part of it. P(t) is the area to the left of t, from −∞ up to it; Q(t) is the area between the mean (0) and t; R(t) is the area to the right, from t to +∞, so R(t) = 1 − P(t). At t = 1.5, P is 0.93319279873, Q is 0.43319279873 and R is 0.06680720127.

Do P, Q and R use the mean and standard deviation of my data?

No. They use the standard normal curve, mean 0 and standard deviation 1, however the editor is filled; your data comes in only through →t, which turns a data value into a standard score first. For a normal curve with another mean and standard deviation, use normalcdf on SHIFT 3 (DISTR), not the Distribution tab.

How do I find the probability below a z-score?

Use P(t) on the Distribution tab: P(1.5) is 0.93319279873, the probability that a standard normal value falls below 1.5. Straight after →t, P(Ans) gives the probability below the data value you just standardised.

Related pages

Written from the calculator's own manual and from the app itself, version 7.6.0; every figure is one the manual shows or a capture of the app proves. Last revised on 29 September 2026.

Bug reports and feature requests go to kimcuc@samatica.com — a person reads it.