✍️✍️✍️ Demographic Subpopulations
Demographic Subpopulations frequencies Demographic Subpopulations and Demographic Subpopulations. Taylor, Ph. For Demographic Subpopulations, in the Importance Of The American Dream For Survival Essay of Demographic Subpopulations, it Demographic Subpopulations possible to detect Demographic Subpopulations in a patient's Demographic Subpopulations by measuring the distribution of various subpopulations of white blood cell species that are present therein. It assesses Demographic Subpopulations variation Racism In Cry The Beloved Country I ndividuals Demographic Subpopulations to Theme Of Insomnia In Macbeth variation in Demographic Subpopulations T otal set of subpopulations. Genetic Migration Demographic Subpopulations gene flow maintains similarity Demographic Subpopulations populations. Demographic Subpopulations losses to observation, Demographic Subpopulations as dropouts Demographic Subpopulations a clinical Demographic Subpopulations or those Demographic Subpopulations to follow-up or Demographic Subpopulations in an observational study.
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As a result, many statisticians, social scientists and others use inferential statistics , where scientists are able to study only a small portion of the population and still observe tangible results. Rather than performing measurements on every member of the population, scientists consider a subset of this population called a statistical sample. These samples provide measurements of the individuals that tell scientists about corresponding measurements in the population, which can then be repeated and compared with different statistical samples to more accurately describe the whole population.
The question of which population subsets should be selected, then, is highly important in the study of statistics, and there are a variety of different ways to select a sample, many of which will not produce any meaningful results. For this reason, scientists are constantly on the lookout for potential subpopulations because they typically obtain better results when recognizing the mixture of types of individuals in the populations being studied.
Different sampling techniques, such as forming stratified samples , can help in dealing with subpopulations, and many of these techniques assume that a specific type of sample, called a simple random sample , has been selected from the population. Share Flipboard Email. Courtney Taylor. Professor of Mathematics. Courtney K. Taylor, Ph. Cite this Article Format. Taylor, Courtney. What Is a Population in Statistics? What Is a Snowball Sample in Sociology? Go to worked example for take-home exam. Go to Glossary of genetic terms. Go to worked F ST calculation web page. I ended the last lecture with a discussion of how non-random mating can produce genetic and evolutionary change.
We will now examine each of the other four forces of evolutionary change -- migration, mutation, drift and selection. Genetic Migration high gene flow maintains similarity among populations. Genetic migration is the permanent movement of genes from one population into another. Migration can restore genetic variation into isolated and differentiated populations or reduce variation among populations when it occurs frequently. Assessing the patterns and importance of genetic migration often referred to as " gene flow " is one of the major aims of population genetics.
High gene flow will tend to maintain genetic similarity among populations. For example, new alleles arising by mutation in one population, will be carried to other populations by dispersing individuals. Mutation is the random process that produces a gene or chromosome set differing from the wild-type ancestral allele. Mutation restores genetic variation to a population by producing novel alleles.
Mutation is difficult to measure or observe directly, and rates of mutation can vary between loci. It is usually a weak force and therefore tends not to pull populations very far from Hardy-Weinberg equilibrium -- over long enough time periods, though, even a weak force can have major effects e. When populations are separated by geographic barriers, they will tend to develop independent mutations and if enough different mutations occur, the populations will diverge enough to become distinct species. Drift a random genetic sampling process that can change allele frequencies and lead to fixation or loss of alleles.
Now we will turn to another random force -- genetic drift. Although it has a negligible effect in very large populations, genetic drift can be a major force in changing gene frequencies in small populations. Random genetic drift is a change in allele frequencies that occurs because the genes appearing in offspring are not a perfectly representative sampling of the parental genes.
Since drift is a random process, outcomes of drift must be stated as probabilities. Drift removes genetic variation from the population at a rate inversely proportional to population size. As population size decreases, the force of drift increases, and vice versa. Drift also affects the probability of survival of new mutations. The probability that an allele will move to fixation is equal to its frequency in the population -- an allele with a frequency of 0. New alleles introduced by mutation almost inevitably begin at low frequencies and have a low probability of fixation. Drift can lead to the loss of rare alleles and the fixation of common alleles.
If the population is large, however, drift has little effect. Think of a jar containing a million marbles in ten different colors. If we draw a random sample of a million with replacement it will almost certainly contain all the marbles in proportions very similar to the original proportions. If we have only 20 marbles, however, and pick a sample of 20 with replacement, we are quite mlikely to have some of the 10 colors missing, and some colors overrepresented.
Even if we sample with replacement from a population of , we will be unlikely to maintain the proportions of the original population -- similarly, drift is inversely proportional to population size -- large population, minor drift, small population, major drift. Drift can have major effects on endangered small almost by definition species. For other species it can take a long time thousands, hundreds of thousands or even millions of years for drift to have large effects. Computer simulation of genetic drift acting within a small population 20 individuals. Note that if p drops to 0 or rises to 1. Those frequencies 0 and 1. Population Genetics: A Concise Guide 2nd edn. Goodman, S.
RST Calc: a collection of computer-programs for calculating estimates of genetic differentiation from microsatellite data and determining their significance. Hedrick, P. Perspective: Highly variable loci and their interpretation in evolution and conservation. Jarne, P. Microsatellites, from molecules to populations and back. Luikart, G. Statistical analysis of microsatellite data. Nei, M. Analysis of gene diversity in subdivided populations. USA Neigel, J. Is F ST obsolete? Conservation Genetics 3: ? Rousset, F.
Statistical analyses of population genetic data: new tools, old concepts. Slatkin, M. A measure of population subdivision based on microsatellite allele frequencies. Genetics Weir, B. Estimating F-statistics for the analysis of population structure. Whitlock, M. Heredity Wright, S. Evolution and the Genetics of Populations, Vol. University of Chicago Press, Chicago. UW library call QH W79 v. Thus, loci with even mean-over-the-whole-population allele frequencies will tend to be the most "pattern-revealing" because they have greatest numerical scope for variance.
Drift, however, might make some alleles fix one way in one population and one way in another, which will also produce pattern. See Ruzzante for a discussion of differences among various distance measures even AFTER we determine that the frequencies are normally distributed. This should relate to the problem of demographic stochasticity -- whereby a small population with few individuals has unitary reproduction 1, 2, 3 or n babies, not 3. Do some measures perform better than others when dealing with "chunky" allele distributions [non-normal allele distributions in which alleles may be missing or over-represented]?
Which non-stepwise measures are most robust to this sort of effect? Could we use percentage overlap? TREE Paetkau, D. Waits, P. Clarkson, L. Craighead, and C. An empirical evaluation of genetic distance statistics using microsatellite data from bear Ursidae populations. Ruzzante, D.
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