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37 Cards in this Set
- Front
- Back
Genetic analysis of complex characteristics |
Quantitative genetics |
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Characteristics that vary continuously along a scale of measurements with many overlapping phenotypes |
Continuous characteristics |
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Are traits that are influenced by genes at many loci |
Polygenic |
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Characteristics thatare both polygenic and influenced by environmental factors |
Multifactorial |
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The relationship of phenotype and genotype is straightforward, each genotype produces a single phenotypeand most phenotyprs encoded by a single genotype |
Discontinuous characteristics |
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The same genotype may produce a range of potential phenotypes which may overlap |
Continuous characteristics |
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Types of quantitative characteristics |
Meristic and threshold |
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Not continous but are determined by multiple genetic and environmental factors and has a limited number of phenotypes |
Meristic characteristics |
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Measured by presence or absenxe, exhibit only two phenotypes but are determined by multiple genetic environmental factors |
Threshold characterisric |
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Underlying susceptibility |
Liability or risk |
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A graph of the frequencies of the different phenotyped |
Frequency distribution |
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X axis expresses? |
Phenotypic classes |
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Y axis expresses? |
Numbers of individuals in each class |
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Group of interest |
Population |
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Smaller collection of individuals |
Sample |
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Characteristics of a good sample |
Must be representative, must be large enough |
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Determining sample size |
Determine the margin error, determine the confidence level |
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This is the positive and negative deviation you allow in your results for the sample, the deviation of each individual and the population |
Margin error |
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The probability that the result lies within the boundaries of the margin error |
Confidence level |
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Indicates the variability of a group of measuremebts or how spread bout the disteibution |
Variance |
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Also called the average and provides information about the center of the distribution |
The Mean |
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Often preferred for describing the variability of a measurement |
Standard deviation |
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Used to describe the shape of the norma distribution |
Mean and standard deviation |
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Is a probability function that describes how the values of a variable is distributed |
Normal distribution |
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Provides a quick estimate of the spread of data in a normal distribution given the mean snd standard deviation. |
Emprical rule, three sigma rule, 68-95-99.7 rule |
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When a number of data points fall outside the three standard eviation range. |
Rough gauge of normality |
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A measure used to represent how strongly two random variables are related |
Correlation |
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A measure used to indicate the extent to which two random varaibles chsnge in tandem |
Covariance |
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Referred to the scale form of variance |
Correlation |
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Is a measurement correlation |
Covariance |
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Is a statistical measure that calculates the strength of the relationshio between the relative movements of two variables |
Correlation coefficient |
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There js a direct association between variables |
Positive value |
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There js an inverse association between variables |
Negative value |
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No association between values |
Zero value |
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Allows to predict the characteristics of offsleing from a giiven mating, even wjthout the knowledge of the genotypes |
Regression |
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Indicates how much y increases on average per increase in x |
Regression coefficient |
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Defines the relation between the x and y variables |
Regression line |