Q:

What does "J-curve" mean in a population?

A:

The term "J-curve" is a type of population growth wherein a population grows exponentially without restrictions. It is also known as the exponential curve.

A population is a class of similar and interbreeding organisms that inhabit a particular region. The life cycle of a population comprises three different stages namely growth, stability and decline. If the population lives in a favorable environment with ample nutritional sources and scarce competition, the population will tend to rapidly increase without constraints. It only stabilizes when the resources begin to dwindle or the population encounters other environmental factors that limit its growth. The population gradually declines and eventually dies out.

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Related Questions

  • Q:

    What is judgment sampling?

    A:

    Judgment sampling is a method in statistics and quantitative research for non-randomly selecting subjects for study from a population by selecting according to the opinion of an expert. It is a biased method that is useful when some members of a population make better subjects than others. The nature of judgment sampling makes data derived by this method harder to generalize and prone to an increased chance of misrepresentation.

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  • Q:

    Why is sampling important?

    A:

    Sampling, in statistics, is a method of answering questions that deal with large numbers of individuals by selecting a smaller subset of the population for study. One of the most prevalent types of sampling is random sampling.

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  • Q:

    What is the definition of sampling distribution?

    A:

    Sampling distribution is defined as the probabilities ascribed to statistics when pulled at random from a population. Sampling distribution of statistics can take the form of either probability distribution or probability density function. Sampling distribution is used primarily in statistics, and may be paired with other mathematical operations to solve problems.

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  • Q:

    What does "r squared" mean?

    A:

    The term "R-squared," or the coefficient of determination, explains the percent of variance away from a dependent variable and is expressed as a percentage between 0 and 100. An R-squared value explains how data fits a statistical set of numbers, sometimes expressed on a graph as a line or curve surrounded by points. The closer the R-squared value is to 100, the more dependent that value is on another variable.

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