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23 Cards in this Set
- Front
- Back
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simple random sample |
all members of the population have the same chance of being selected for the sample |
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systematic sample |
a random starting point is selected, and then every kth item thereafter is selected for the sample. |
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Stratified sample |
the population is divided into several groups, and then a random sample is selected from each |
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Stratum |
A group/subset of the population |
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Cluster sampling |
the population is divided into primary units, then samples are drawn from the primary units. |
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Unbiased sample |
all members of the population have a chance of being selected for the sample. |
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sampling error |
the difference between a population parameter and a sample statistic. |
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sampling distribution of the sample mean |
a probability distribution of all possible sample means of a given size from a population. |
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standard error of the mean |
measures the variation in the sampling distribution of the sample mean. |
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A proportion |
a ratio, fraction, or percent that indicates the part of the sample or population that has a particular characteristic. |
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random variable |
a numerical value determined by the outcome of a random experiment |
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probability distribution. |
is a listing of all possible outcomes of an experiment and the probability associated with each outcome |
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A discrete probability distribution |
can assume only certain values |
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A continuous distribution |
can assume an infinite number of values within a specific range. |
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Characteristics of a Binomial Distribution |
A. Each outcome is classified into one of two mutually exclusive categories. B. The distribution results from a count of the number of successes in a fixed number of trails. C. The probability of a success remains the same from trial to trial. D. Each trial is independent. |
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Characteristics of a Poisson Distribution |
A. It describes the number of times some event occurs during a specified interval. B. The probability of a “success” is proportional to the length of the interval. C. Non overlapping intervals are independent. D. It is a limiting form of the binomial distribution when n is large and p is small. |
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Characteristics of a Hypergeometric Distribution |
A. There are only two possible outcomes. B. The probability of a success is not the same on each trial. C. The distribution results from a count of the number of successes in a fixed number of trials. |
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Features of Discrete Probability Distribution |
A. The sum of the probabilities is 1.00. B. The probability of a particular outcome is between 0.00 and 1.00. C. The outcomes are mutually exclusive. |
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Characteristics of The Uniform distribution |
A. It is rectangular in shape. B. The mean and the median are equal. C. It is completely described by its minimum value a and its maximum value b. |
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Characteristics of The Normal distribution |
A. It is bell-shaped and has a single peak at the centre of the distribution. B. The distribution is symmetric. C. It is asymptotic, meaning the curve approaches but never touches the X-axis. D. It is completely described by the mean and standard deviation. |
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area under a normal curve |
the probability of an outcome. |
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Cumulative Density Function, F(X) |
integral of a probability density function |
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Probability Density Function, f(x) |
derivative of a cumulative density function |
