## When would you use winsorization?

Winsorization is a way to minimize the influence of outliers in your data by either:

- Assigning the outlier a lower weight,
- Changing the value so that it is close to other values in the set.

## What does Winsorized mean in stats?

Winsorized mean is a method of averaging that initially replaces the smallest and largest values with the observations closest to them. This is done to limit the effect of outliers or abnormal extreme values, or outliers, on the calculation.

**What is the difference between trimming and Winsorizing?**

Winsorizing data means to replace the extreme values of a data set with a certain percentile value from each end, while Trimming or Truncating involves removing those extreme values.

### What is a Winsorized z score?

Measure Score Calculation (Winsorized z-scores) Winsorize measure results for each measure. Calculate Winsorized z-scores, also known as measure scores, for each hospital using the hospital’s Winsorized measure results, national mean, and standard deviation of Winsorized measure results for each measure.

### When should you trim data?

Data trimming is applied to data sets when dealing with outliers. Outliers are extreme values that disrupt distributions in a data set. Cutting extreme values can be useful for the mean but not for the median. There is no single accepted standard for dealing with outliers in statistical processes.

**Does Winsorizing affect median?**

Note that the median did not change at all. In all but the most extreme cases, the median is robust to outliers and unaffected by Winsorizing because the extreme values stay on their side of the median .

## How do you Winsorize a variable?

To obtain the Winsorized mean, you sort the data and replace the smallest k values by the (k+1)st smallest value. You do the same for the largest values, replacing the k largest values with the (k+1)st largest value. The mean of this new set of numbers is called the Winsorized mean.

## How do you determine a trimming percentage?

Trimmed Mean Formula Multiply the percentage by the number of observations to arrive at the number of values deducted from each end. Remove the highest and lowest numbers from both ends. Reduce the total number of observations by deducting the number of observations that were cut.

**When we Winsorize data at the 95th percentile it means that we are losing 5% of observations?**

To winsorize data means to set extreme outliers equal to a specified percentile of the data. For example, a 90% winsorization sets all observations greater than the 95th percentile equal to the value at the 95th percentile and all observations less than the 5th percentile equal to the value at the 5th percentile.

### What are trimming percentages?

These means are expressed in percentages. The percentage tells you what percentage of data to remove. For example, with a 5% trimmed mean, the lowest 5% and highest 5% of the data are excluded.

### What is a 10% trimmed mean?

The 10% trimmed mean is the mean computed by excluding the 10% largest and 10% smallest values from the sample and taking the arithmetic mean of the remaining 80% of the sample (other trimmed means are possible: 5%, 20%,, etc.) Example Consider the data (sample) 5, 4, 7, 6, 8, 10, 11, 0, 7, 18.