Please enable JavaScript.
Coggle requires JavaScript to display documents.
Chapter 6: Probability - Coggle Diagram
Chapter 6: Probability
Although the exact outcome of a sample, cannot be guaranteed it is possible to talk about the potential outcomes in terms of probabilities.
When you know the makeup of a population, you can determine the probability of obtaining specific samples.
Probability is used to predict the type of samples that are likely to be obtained from a population.
-
-
Each individual in the population having an equal chance of being selected is required for a random sample.
-
A second requirement, necessary for many statistical formulas, states that if more than one individual is being selected, the probabilities must stay constant from one selection to the next.
-
Independent refers to the fact that the probability of selecting any particular individual is independent of the individuals already selected for the sample
Since independent random sample is usually a required component for most statistical applications, it is assumed that it is the sampling method being used.
Random Sampling:
A sampling technique that returns the current selection to the population before the next selection is made is called sampling with replacement.
Unit normal table:This is a table that lists the proportions corresponding to each z-score location in a normal distribution.
-
The unit normal table can be used only with normal-shaped distributions. If a distribution is not normal, transforming to z-scores will not make it normal.
-
The binomial distribution is used whenever the measurement procedure simply classifies individuals into exactly two categories.
The binomial distribution gives the probability for each value of X, where X equals the number of occurrences of category A in a series of n events.
When pn and qn are both at least 10, the binomial distribution is closely approximated by a normal distribution
