![]() The important thing here is to correlate P( S) The term success might actually represent the process of selecting a defectiveĬhip. For example, you may want to find the probability of finding aĭefective chip, given the probability 0.2 that a chip is defective. The term success may not necessarily be what you would call a desirable Whereas, p and q=1- p denote the probabilities (success) and F (failure) denote possible categories for all outcomes ![]() Some notation has become very standard when working with binomial distributions. People either have or haven't eaten at McDonald's. Here it means there are two and only two distinct categories.įor instance, students either pass or they fail a test. This distribution is related to what happens when you study the This context, just like bicycle, bifocal, and bigamist. The prefix bi- has the usual meaning of two in We already referenced uniform distributions and However, other distributions will be important to this courseĭue to their relationship to inferential statistics. We will introduce the binomial today and thenįocus on the normal distribution. Examples ofĭiscrete distributions include the Binomial, the Hypergeometric, and the Probability distributions may be either discrete or continuous.ĭistributions are good examples of continuousĭistributionsthe random variable can take on any value. The Bell-shaped, Normal, Gaussian Distribution.Remember the old saying: ``The coin has no memory.The Normal Distribution Back to the Table of Contents Applied Statistics - Lesson 4 The Binomial and Normal, Bell-shaped, Gaussian Distributions Lesson Overview:.Probability of getting a head on one toss of the coin after 2500 tosses of the coin?.Probability of NOT getting a head or a tail on one toss of the coin?.Probability of getting a head on one toss of the coin?. ![]() Probability of getting a head or a tail on one toss of the coin?.Remember, simple probability is the number of desired outcomes divided by the number of possible outcomes. There is a 16.66% chance I'll roll a 5 on one independent roll of the die.How certain one is that a particular event will happen.Subjective interpretation of probability.This is the interpretation we typically use.166, so if we roll the die 1000 times, we would expect to get a 5 roughly 166.6 times. The probability of rolling a 5 on a six-sided die is: p =.What you would expect to get, in the long run, if you were to repeat the experiment many times.Long-run relative-frequency interpretation.The number of possible successful or desirable outcomes divided by the number of all possible outcomes.p means the probability of the event is less than.If the event is certain to occur, then p = 1.If there is no chance the event will occur, then p = 0.Expressed as an italicized, lower-case p.The range of probabilities: Zero to One.The proportion of scores between any two Z-scores is the same as the probability of selecting a case between those two Z-scores.The numbers on the outside of the standard normal curve from the previous slide can be expressed as percentages or probabilities.Memorize this image.burn it into your brain!! ![]() Z-scores along the bottom, probabilities around the top
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