Statistics Excel Worksheet
University of the Philippines
Diliman Extension Program in Pampanga
Claro M. Recto Highway, CSEZ, Pampanga
A.Y 2013-2014
LABORATORY WORK # 2
THE BINOMIAL DISTRIBUTION
Submitted by:
Briones, Kristelle R.
Mangrobang, Jonathane
Submitted to:
Prof. Ernesto Adorio
January 2014
Description:
Our instructor instructed to put tabulate the Binomial Distribution for various n given the values of p which are (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 and 0.9).
The binomial distribution is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p. This success/failure experiment is also called a Bernoulli experiment or Bernoulli trial. The binomial distribution is a Bernoulli distribution when n = 1.
In many cases, it is appropriate to summarize a group of independent observations by the number of observations in the group that represent one of two outcomes. For example, the proportion of individuals in a random sample who support one of two political candidates fits this description. In this case, the statistic is thecount X of voters who support the candidate divided by the total number of individuals in the group n. This provides an estimate of the parameter p, the proportion of individuals who support the candidate in the entire population.
The binomial distribution describes the behavior of a count variable X if the following conditions apply:
1: The number of observations n is fixed.
2: Each observation is independent.
3: Each observation represents one of two outcomes ("success" or "failure").
4: The probability of "success" p is the same for each outcome.
The binomial distribution is the basis for the popular binomial test of statistical significance. Probability mass function (pmf) is a function that gives the probability that a discrete random variable is exactly equal to some value. Also, it is a
Diliman Extension Program in Pampanga
Claro M. Recto Highway, CSEZ, Pampanga
A.Y 2013-2014
LABORATORY WORK # 2
THE BINOMIAL DISTRIBUTION
Submitted by:
Briones, Kristelle R.
Mangrobang, Jonathane
Submitted to:
Prof. Ernesto Adorio
January 2014
Description:
Our instructor instructed to put tabulate the Binomial Distribution for various n given the values of p which are (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 and 0.9).
The binomial distribution is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p. This success/failure experiment is also called a Bernoulli experiment or Bernoulli trial. The binomial distribution is a Bernoulli distribution when n = 1.
In many cases, it is appropriate to summarize a group of independent observations by the number of observations in the group that represent one of two outcomes. For example, the proportion of individuals in a random sample who support one of two political candidates fits this description. In this case, the statistic is thecount X of voters who support the candidate divided by the total number of individuals in the group n. This provides an estimate of the parameter p, the proportion of individuals who support the candidate in the entire population.
The binomial distribution describes the behavior of a count variable X if the following conditions apply:
1: The number of observations n is fixed.
2: Each observation is independent.
3: Each observation represents one of two outcomes ("success" or "failure").
4: The probability of "success" p is the same for each outcome.
The binomial distribution is the basis for the popular binomial test of statistical significance. Probability mass function (pmf) is a function that gives the probability that a discrete random variable is exactly equal to some value. Also, it is a