# Is Chi square a t test?

**Chi**-

**Square**Statistic in Research. The

**Chi Square**statistic is commonly used for

**testing**relationships between categorical variables. The null hypothesis of the

**Chi**-

**Square test**is that no relationship exists on the categorical variables in the population; they are independent.

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People also ask, what does the chi square test tell you?

The **Chi**-**square test** is intended to **test** how likely it is that an observed distribution is due to chance. It is also called a "goodness of fit" statistic, because it measures how well the observed distribution of data fits with the distribution that is expected if the variables are independent.

Also Know, what is considered a high chi square value? A very small **chi square** test statistic means that your observed data fits your expected data extremely well. In other words, there is a relationship. A very **large chi square** test statistic means that the data does not fit very well. In other words, there isn't a relationship.

Furthermore, what is the difference between chi square and t test?

A **t**-**test tests** a null hypothesis about two means; most often, it **tests** the hypothesis that two means are equal, or that the **difference between** them is zero. A **chi**-**square test tests** a null hypothesis about the relationship **between** two variables.

How do we find the p value?

If your test statistic is positive, first **find** the probability that Z is greater than your test statistic (look up your test statistic on the Z-table, **find** its corresponding probability, and subtract it from one). Then double this result to get the **p**-**value**.