A standard normal table, also called the unit normal table or Z table, is a mathematical table for the values of, which are the values of the cumulative distribution function of the normal distribution. Since probability tables cannot be printed for every normal distribution, as there are an infinite variety of normal distributions, it is common practice to convert a normal to a standard normal and then use the standard normal table to find probabilities. Because we have defined probability as equivalent to proportion, you can also use the unit normal table to look up probabilities for normal distributions. You can use this z-table to find probabilities associated with the standard normal curve.

There is a table which must be used to look up standard normal probabilities. The z-score is broken into two parts, the whole number and tenth are looked up along the left side and the hundredth is looked up across the top. What is important is to understand that the normal distribution is used very frequently because: It can be shown that many characteristics of interest, such as IQ, height and weight of people, etc. Answering Probability Questions with the Unit Normal Table: The unit normal table provides a listing of proportions (probabilities) corresponding to many z-scores in the standard normal distribution. Though the cumulative standard normal table is most commonly used, your lecturer might instead use the cumulative from zero standard normaltable, which gives the probability that Z is between 0 and a positive number. The values in the main table are probabilities that Z is between 0 and +a.

Can determine a probability from a frequency distribution table by computing the proportion for the X value in question. Look up the appropriate value of z in the unit normal table. You can see that our proportion column corresponds to probability. It in turn corresponsd to the area under the curve (or in this case under the bars) for those intervals. So make sure that you understand the Unit Normal Table that you are using.

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