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Only 7.2 percent of the population has O-negative blood A mobile blood center is visited by 20 donors in afternoon Let X denote number of universal donors among them probability that X is at least 2?
Wiki User
∙ 10y ago
- The probability that any given donor is a universal donor is 0.072.
- We need the probability that the number of universal donors in this group of 20 is not zero or one.
Probability of getting zero universal donors: ( 1 - 0.072 )^20 = 0.224367
Probability of getting one such donor: 0.348156 (given by the binomial probability density function: probability of one success in 20 trials with p=0.072)
Total: 0.224367 + 0.348156 = 0.572523, the probability of zero or one donors
But we want 1 - 0.572523 = 0.427477, the probability of getting two or more such donors.
^ stands for 'to the power of'
Wiki User
∙ 10y ago
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How do you get sample using universal sampling technique?
try researching about total enumeration technique... it's the other name for universal sampling technique ^_^ Good luck..
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Frequently it's impossible or impractical to test the entire universe of data to determine probabilities. So we test a small sub-set of the universal database and we call that the sample. Then using that sub-set of data we calculate its distribution, which is called the sample distribution. Normally we find the sample distribution has a bell shape, which we actually call the "normal distribution." When the data reflect the normal distribution of a sample, we call it the Student's t distribution to distinguish it from the normal distribution of a universe of data. The Student's t distribution is useful because with it and the small number of data we test, we can infer the probability distribution of the entire universal data set with some degree of confidence.
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shaking the sample before transferring it into a sterile universal bottle is an important step in many microbiological experiments as it helps to ensure that the sample is well-mixed and that any microorganisms present are evenly distributed throughout the sample.
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1. Abstraction : model is described using universal principles and properties- reusable across situations, hides complexity. 2. Transparency : close representation to real world-intuitively clear and understandable from any point of view. 3. Effectiveness : readily translated into actual information systems that are durable, reliable, and extensible.
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The direction of a linear relationship is positive when the two variables increase together and decrease together. The direction is negative if an increase in one variable is accompanied by a decrease in the other. The strength of the relationship tells you, in the context of a scatter plot of the two variables, how close the observations are to the line representing the linear relationship. There are various very closely related measures: regression coefficient or product moment correlation coefficient (PMCC) are commonly used. These can take any value between -1 and +1. A value of -1 represents a perfect negative relationship, +1 represents a perfect positive relationship. A value of 0 represents no linear relationship (there may be a non-linear one, though). Values near -1 or +1 are said show a strong linear relationship, values near 0 a weak one. There is no universal rule about when a relation goes from being strong to moderate to none.
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