Make it easier to use on calc

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Isaac Shoebottom 2024-02-17 21:51:18 -04:00
parent b0e72be1d0
commit 96b29f0bac

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@ -349,45 +349,50 @@ def pd_gt(x, l):
def man():
seperator = "-" * 30
seperator = "-" * 20
"""
Prints the manual for the module.
Formatted this way to fit in memory on the calculator.
"""
print("This module contains functions for computing the total probability of events.")
print("The functions are:")
print("bnd(x, n, p) - The binomial distribution")
print("bnd_mean(n, p) - The mean of the binomial distribution")
print("bnd_var(n, p) - The variance of the binomial distribution")
print("bnd_std(n, p) - The standard deviation of the binomial distribution")
print("bnd_leq(x, n, p) - The cumulative probability less than or equal to x successes in n trials")
print("bnd_lt(x, n, p) - The cumulative probability less than x successes in n trials")
print("bnd_geq(x, n, p) - The cumulative probability greater than or equal to x successes in n trials")
print("bnd_gt(x, n, p) - The cumulative probability greater than x successes in n trials")
print(seperator)
print("gd(x, p, q) - The geometric distribution")
print("gd_mean(p) - The mean of the geometric distribution")
print("gd_var(p) - The variance of the geometric distribution")
print("gd_std(p) - The standard deviation of the geometric distribution")
print("gd_leq(x, p, q) - The cumulative probability of getting upto x trials until the first success")
print("gd_lt(x, p, q) - The cumulative probability of getting less than x trials until the first success")
print("gd_geq(x, p, q) - The cumulative probability of getting from x trials until the first success")
print("gd_gt(x, p, q) - The cumulative probability of getting from x trials until the first success")
print("Binomial Distribution")
print("bnd(x, n, p)")
print("bnd_mean(n, p)")
print("bnd_var(n, p)")
print("bnd_std(n, p)")
print("bnd_leq(x, n, p)")
print("bnd_lt(x, n, p)")
print("bnd_geq(x, n, p)")
print("bnd_gt(x, n, p)")
print(seperator)
print("hgd(x, N, n, k) - The hyper geometric distribution")
print("hgd_mean(N, n, k) - The mean of the hyper geometric distribution")
print("hgd_var(N, n, k) - The variance of the hyper geometric distribution")
print("hgd_std(N, n, k) - The standard deviation of the hyper geometric distribution")
print("hgd_leq(x, N, n, k) - The cumulative probability of getting upto x successes in n draws from a population of size N with k successes")
print("hgd_lt(x, N, n, k) - The cumulative probability of getting less than x successes in n draws from a population of size N with k successes")
print("hgd_geq(x, N, n, k) - The cumulative probability of getting from x successes in n draws from a population of size N with k successes")
print("hgd_gt(x, N, n, k) - The cumulative probability of getting from x successes in n draws from a population of size N with k successes")
print("Geometric Distribution")
print("gd(x, p, q)")
print("gd_mean(p)")
print("gd_var(p)")
print("gd_std(p)")
print("gd_leq(x, p, q)")
print("gd_lt(x, p, q)")
print("gd_geq(x, p, q)")
print("gd_gt(x, p, q)")
print(seperator)
print("pd(x, l) - The poisson distribution")
print("pd_mean(l) - The mean of the poisson distribution")
print("pd_var(l) - The variance of the poisson distribution")
print("pd_std(l) - The standard deviation of the poisson distribution")
print("pd_leq(x, l) - The cumulative probability of getting upto x occurrences")
print("pd_lt(x, l) - The cumulative probability of getting less than x occurrences")
print("pd_geq(x, l) - The cumulative probability of getting from x occurrences")
print("pd_gt(x, l) - The cumulative probability of getting from x occurrences")
print("Hyper Geometric Distribution")
print("hgd(x, N, n, k)")
print("hgd_mean(N, n, k)")
print("hgd_var(N, n, k)")
print("hgd_std(N, n, k)")
print("hgd_leq(x, N, n, k)")
print("hgd_lt(x, N, n, k)")
print("hgd_geq(x, N, n, k)")
print("hgd_gt(x, N, n, k)")
print(seperator)
print("Poisson Distribution")
print("pd(x, l)")
print("pd_mean(l)")
print("pd_var(l)")
print("pd_std(l)")
print("pd_leq(x, l)")
print("pd_lt(x, l)")
print("pd_geq(x, l)")
print("pd_gt(x, l)")