## What if the Z value is negative?

A negative z-score reveals the raw score is below the mean average. For example, if a z-score is equal to -2, it is 2 standard deviations below the mean. Another way to interpret z-scores is by creating a standard normal distribution (also known as the z-score distribution or probability distribution).

**What does negative standardized value mean?**

A negative standardized value means: it is below the mean; as the score was in the original variable. It does not mean that the score is negative as in ‘negative feelings’.

### How do you find the p value when Z is negative?

If your test statistic is negative, first find the probability that Z is less than your test statistic (look up your test statistic on the Z-table and find its corresponding probability). Then double this probability to get the p-value.

**How do you use a negative z-table?**

If you have a negative z-score simply use the same table but disregard the negative sign, then subtract the area from the table from 1.

#### What does a negative test statistic mean?

Explanation: A negative t-statistic simply means that it lies to the left of the mean . The t-distribution, just like the standard normal, has a mean of 0 . All values to the left of the mean are negative and positive to the right of the mean.

**Can you have a negative standardized value?**

## How do you standardize data with negative values?

The solution is simple: Shift your data by adding all numbers with the absolute of the most negative (minimum value of your data) such that the most negative one will become zero and all other number become positive.

**Can a p-value be negative?**

Terms in this set (26) Can A p-value be negative? P-values correspond to the probability of observing an extreme (or more extreme) event based on the significance level and the assumption that the null hypothesis is true. Since probabilities are NEVER negative, the p-value is NEVER negative.

### Can a standard deviation be negative?

The standard deviation from the minimum feasible value should be zero. If you are not approximately equal to at least two figures in your data set, the standard deviation must be higher than 0 – positive. Standard deviation cannot be negative in any conditions.