For statistical tests based on (Student's) t-distribution you use the t-table. This is appropriate for small sample sizes - up to around 30. For larger samples (or degrees of freedom), the t-distribution becomes very close to the Standard Normal distribution so you use the z-tables.
If the sample size is less then 30 use the T table, if greater then 30 use the Z table.
You use a z test when you are testing a hypothesis that is using proportions You use a t test when you are testing a hypothesis that is using means
You decide this because a t chart is when you give details about something so if your doing t chart that's when you decide to do a t chart
T score is usually used when the sample size is below 30 and/or when the population standard deviation is unknown.
t is the significance of Z-transform
If the sample size is less then 30 use the T table, if greater then 30 use the Z table.
When we use a z-test, we know the population mean and standard deviation. When we use a t-test, we do not know the population standard deviation and thus must estimate this using the sample data that we have collected. If you look at your z-table and t-table, tcrit for df(infinity) = zcrit because at df(infinity) we would have an entire population and no longer need an estimate.
If the distribution is Gaussian (or Normal) use z-scores. If it is Student's t, then use t-scores.
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zygote
You either look it up in a table of z scores or you can use a calculator such as the TI8 and use normalcdf.
If the sample size is large (>30) or the population standard deviation is known, we use the z-distribution.If the sample sie is small and the population standard deviation is unknown, we use the t-distribution
You use a z test when you are testing a hypothesis that is using proportions You use a t test when you are testing a hypothesis that is using means
A z table is used to calculate the probability of choosing something that is normally distributed. In order to use it, first a z score is needed. A z score is the number of standard distributions a value is away from the mean of the data. In order to find the z score, take the value of the datum, subtract the mean, then divide by the standard deviation. The result is a z score. Look up the z score on the table to find the probability of getting anything equal to or lesser than the value you chose.
Not all z-score tables are the same. You must know how to use the specific table that you have.
T-Rex or T-rex
Because t-score isn't as accurate as z-score, you should use 40 as a safety sample size, rather than 30 as you would for a z-score.