Sampling distribution is the probability distribution of a given sample statistic. For example, the sample mean. We could take many samples of size k and look at the mean of each of those. The means would form a distribution and that distribution has a mean, a variance and standard deviation. Now the population only has one mean, so we can't do this. Population distribution can refer to how some quality of the population is distributed among the population.
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A time series is a sequence of data points, measured typically at successive points in time spaced at uniformed time intervals. Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics. Regression analysis is a statistical process for estimating the relationship among variables.
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A "Good" estimator is the one which provides an estimate with the following qualities:Unbiasedness: An estimate is said to be an unbiased estimate of a given parameter when the expected value of that estimator can be shown to be equal to the parameter being estimated. For example, the mean of a sample is an unbiased estimate of the mean of the population from which the sample was drawn. Unbiasedness is a good quality for an estimate, since, in such a case, using weighted average of several estimates provides a better estimate than each one of those estimates. Therefore, unbiasedness allows us to upgrade our estimates. For example, if your estimates of the population mean µ are say, 10, and 11.2 from two independent samples of sizes 20, and 30 respectively, then a better estimate of the population mean µ based on both samples is [20 (10) + 30 (11.2)] (20 + 30) = 10.75.Consistency: The standard deviation of an estimate is called the standard error of that estimate. The larger the standard error the more error in your estimate. The standard deviation of an estimate is a commonly used index of the error entailed in estimating a population parameter based on the information in a random sample of size n from the entire population.An estimator is said to be "consistent" if increasing the sample size produces an estimate with smaller standard error. Therefore, your estimate is "consistent" with the sample size. That is, spending more money to obtain a larger sample produces a better estimate.Efficiency: An efficient estimate is one which has the smallest standard error among all unbiased estimators.The "best" estimator is the one which is the closest to the population parameter being estimated.
The small difference in individuals is called genetic variation. This variation is caused by differences in individuals' DNA sequences, resulting in diversity among traits such as eye color, height, and susceptibility to diseases.
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The entire collection of genes among a population is called the "gene pool".
The pattern of spacing between individuals across the range of a population is known as the distribution pattern. It can be uniform, random, or clumped, depending on factors like resource availability and social interactions among individuals.
Population spacing refers to the arrangement of individuals within a population, determining how individuals are distributed in a given area. It can help to delineate territories, resources, and interactions among individuals. Population spacing patterns can vary from clumped (individuals found in groups) to random (individuals spread evenly) to uniform (individuals evenly spaced).
Spacing in populations refers to the pattern of individuals within a population in relation to one another. It can be clumped, uniform, or random. This spacing pattern can be influenced by resources, competition, and social behavior among individuals in the population.
A population pattern is shown on a map where people live, such as dense areas within the population. Other patterns could be specific themes, such as average income of the population.
antagonistic interactions among individuals in the population
Variation refers to the degree of difference or diversity among individuals within a population or species. It can involve differences in traits, characteristics, or behaviors, which can be shaped by genetic, environmental, and other factors. Studying variation is important in understanding evolution, adaptation, and biodiversity.
If the largest segment of a population is in its post-reproductive years, this can lead to a decrease in population growth as there are fewer individuals contributing to reproduction. This can result in a decline in the overall population size over time unless offset by immigration or increase in birth rates among younger individuals.
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Individuals within a population have variation in traits. Some of the variation in traits is heritable. Individuals with certain traits are more likely to survive and reproduce. Over time, the frequency of traits that are advantageous for survival and reproduction will increase in a population.