help probcalc 
-------------------------------------------------------------------------------

Title:

probcalc: Probability Calculator for Binomial, Poisson, and Normal Distributio > ns

Syntax

probcalc {dist param1 param2 param3}, param4 param5

Description:

probcalc calculates the probability mass function for the discrete binomial and Poisson distributions and the probability density function for the continuous normal distribution. Output is written to the display in a format useful for learning probability calculations.

The algorithm can handle probability questions pertaining to, for example, "exactly 5 events," "at most 120 events," and "at least 7 events."

---------------------------------------------------------------------------

Commands for the Binomial Distribution:

Probability of observing exactly x events, P(X=x)

probcalc b #n #p exactly #x} (Note: bold represents commands and #param represents actual numeric input value)

The probability distribution based on n and p, densities only shown for pmf>0.01

probcalc b #n #p dist

Probability of observing at most x events, P(X<=x)

probcalc b #n #p atmost #x

Probability of observing at least x events, P(X>=x)

probcalc b #n #p atleast #x

Commands for the Poisson Distribution:

Probability of observing exactly x events, P(X=x)

probcalc p #mu exactly #x

The probability distribution based on mu, densities only shown for pmf>0.01

probcalc p #mu dist

Probability of observing at most x events, P(X<=x)

probcalc p #mu atmost #x

Probability of observing at least x events, P(X>=x)

probcalc p #mu atleast #x

Commands for the Normal Distribution:

Probability of observing a value of X between a and b, P(a<=X<b)

probcalc n #mean #sigma between #a #b

The probability density within plus-minus 4 standard deviations of a mean (30 bins)

probcalc n #mean #sigma dist

Probability of observing an X-value that is at most x, P(X<=x)

probcalc n #mean #sigma atmost #x

Probability of observing an X-value that is at least x, P(X>=x)

probcalc n #mean #sigma atleast #x

Examples:

A set of measurements for a particular variable follow the binomial distribution with parameters n=15 and p=0.15. What is the probability of occurrence of exactly 5 events, P(X=5)?

.probcalc b 15 0.15 exactly 5

Generate the distribution of binomial variates based on the parameter values n=30 and p=0.35. What is the probability distribution, showing only variates for which pmf>0.01?

.probcalc b 30 0.35 dist

A variable was observed to follow the binomial distribution with n=100 and p=0.17. What is the probability of observing at most 16 events, P(X<=16)? (16 and less --> left tail)

.probcalc b 100 0.17 atmost 16

Quark-gluon collisions were tabulated for a number of identical collider experiments and were found to follow a binomial distribution with n=1500 and p=0.25. What is the chance that at least 375 collisions would have been observed, P(X>=375)? (375 and greater --> right tail)

.probcalc b 1500 0.25 atleast 375 An event occurs at a rate of mu=15 times per day on average. What is the probability of exactly 5 events occuring on any given day, P(X=5)?

.probcalc p 15 exactly 5 What is the Poisson probability distribution when mu=10? (Note: only variates for which pmf>0.01 are shown)

.probcalc p 10 dist

An event occurs on average mu=100 per millisecond. What is the probability of at most 93 events will be observed in a millisecond, P(X<=93)? (93 and less -> left tail)

.probcalc p 100 atmost 93 The number of ions that interact within a square centimeter of target material is mu=14. What is the probability that at least 12 ions will interact in a square centimeter of area, P(X>=12)? (12 and greater --> right tail)

.probcalc p 14 atleast 12

Daily caloric intake among a set of low-fat diet participants was found to be normally distributed with mean 1987 (calories) and s.d.=52. What proportion of participants would be expected to have daily caloric intake values between 1930 and 2040 calories, P(1930<X<=2040)?

.probcalc n 1987 52 between 1930 2040

Patient weight measurements indicate a mean of 150 and s.d. of 20. What is the normal probability density between plus-minus 4 standard deviations of the mean?

.probcalc n 150 20 dist

Weight of high school students was determined to be normally distributed with mean=128 (lbs) and s.d.=25 (i.e., s.d.). What proportion of students are likely to weigh less than 120 lbs, P(X<=120)?

.probcalc n 128 25 atmost 120

Daily temperature in Houston was determined to be normally distributed with mean=68 and s.d.=16. What is the chance of the temperature being 90F or greater, P(X>=90)?

.probcalc n 68 16 atleast 90

During run-time, output results merely displayed to the screen, for cutting and pasting.

Author:

Leif E. Peterson Associate Professor of Public Health Weill Cornell Medical College, Cornell University Center for Biostatistics, The Methodist Hospital Research Institute (TMHRI) Email: lepeterson@tmhs.org

Also see

Online: binomialp, binomial, poissonp, poisson, normal.