succession

Examples of succession in the following topics:

• Brazil's Economic Success and Corruption Woes

• Introduction to negative binomial distribution

  • We are waiting for the fourth success (k = 4).
  • Each trial outcome can be classified as a success or failure.
  • The probability of a success (p) is the same for each trial.
  • Because it took Brian six tries to get the fourth success, we know the last kick must have been a success.
  • Each sequence in Table 3.20 has exactly two failures and four successes with the last attempt always being a success.

• Poisson Distribution

  • The Poisson distribution can be used to calculate the probabilities of various numbers of "successes" based on the mean number of successes.
  • Keep in mind that the term "success" does not really mean success in the traditional positive sense.

• Ecological Succession

  • When disturbances occur, succession allows for communities to become re-established over periods of time.
  • Succession describes the sequential appearance and disappearance of species in a community over time.
  • In primary succession, newly-exposed or newly-formed land is colonized by living things.
  • During primary succession in lava on Maui, Hawaii, succulent plants are the pioneer species.
  • Secondary succession is shown in an oak and hickory forest after a forest fire.

• Bernoulli distribution

  • We label a person a success if she refuses to administer the worst shock.
  • Thus, success or failure is recorded for each person in the study.
  • We typically label one of these outcomes a "success" and the other outcome a "failure".
  • We may also denote a success by 1 and a failure by 0.
  • Bernoulli random variables are often denoted as 1 for a success and 0 for a failure.

• Financial Rewards for Managers

  • Career success and fulfillment hinge on effective human-resource management and empowering employees with the necessary tools and skills.
  • When assigning tasks, managers must keep career success and development in mind.
  • Promoting career success for employees and managers involves the creation of developmental goals that build stronger skills and aim toward fulfillment.
  • By employing these steps, a manager can help their employees be successful.
  • Describe how managers and human resource professionals can effectively empower employees to achieve success and fulfillment

• The Impact of Business Owners on Success and Failure Rates

  • As the creator, organizer, and manager of a business, a business owner is critical to the success or failure of a given venture.
  • There are countless factors that determine success or failure when starting and running your own business.
  • The ability to sell the idea itself is therefore another critical success factor for any business owner.
  • Combining the core importance of the business owner in the creation of the business and the variety of skills business owners can leverage to achieve success, business owners are often enough the primary influence on a small business' potential success (and potential failure).
  • Recognize the significant impact a business owner has on the success of a small business

• The Hypergeometric Random Variable

  • A hypergeometric random variable is a discrete random variable characterized by a fixed number of trials with differing probabilities of success.
  • The hypergeometric distribution is a discrete probability distribution that describes the probability of $k$ successes in $n$ draws without replacement from a finite population of size $N$ containing a maximum of $K$ successes.
  • This is in contrast to the binomial distribution, which describes the probability of $k$ successes in $n$ draws with replacement.
  • As random selections are made from the population, each subsequent draw decreases the population causing the probability of success to change with each draw.

• Binomial Probability Distributions

  • A "success" could be defined as an individual who withdrew.
  • Many random experiments include counting the number of successes in a series of a fixed number of independently repeated trials, which may result in either success or failure.
  • The distribution of the number of successes is a binomial distribution.
  • If $x$ success occur, where $x=0, 1, 2, \dots, n$, then $n-x$ failures occur.
  • The number of ways of selecting $x$ positions for the $x$ successes in the $x$ trials is:

• Geometric distribution

  • What about if it takes her n−1 individuals who will administer the worst shock before finding her first success, i.e. the first success is on the nth person?
  • (If the first success is the fifth person, then we say n = 5. )
  • If the first success is on the nth person, then there are n−1 failures and finally 1 success, which corresponds to the probability (0.65)n−1(0.35).
  • If the probability of a success is high (e.g. 0.8), then we don't usually wait very long for a success: 1/0.8 = 1.25 trials on average.
  • If the probability of a success is low (e.g. 0.1), then we would expect to view many trials before we see a success: 1/0.1 = 10 trials.