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How do you calculate the trimmed mean?
2 Answers
- Trimmed mean involves trimming P percent observations from both ends.
- E.g.: If you are asked to compute a 10% trimmed mean, P=10.
- Given a bunch of observations, Xi:
- If np is an integer use k=np and trim k observations at both ends.
- R = remaining observations = n−2k.
- Trimmed mean = (1/R)(Xk+1+Xk+2+…
How do you calculate a 15% trimmed mean?
In the above example, if we wanted 15% trimmed mean, ��=0.15, n=10, k=n��=1.5. Calculations yield k has an integer part 1, and a fractional part 0.5. R=n-2k=10-2*1.5=10-3=7.
How do you calculate 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.)
What is 50% trimmed mean?
Description: The mean is the sum of the observations divided by the number of observations. The trimmed mean compensates for this by dropping a certain percentage of values on the tails. For example, the 50% trimmed mean is the mean of the values between the upper and lower quartiles.
What is a 5% trimmed mean?
A trimmed mean is an option in descriptive statistics in many computer programs. For example, with a 5% trimmed mean, the lowest 5% and highest 5% of the data are excluded. The mean is calculated from the remaining 90% of data points.
When should you use a trimmed mean?
A mean is a mathematical average of two or more numbers while the trimmed mean helps to reduce the effects of outliers on the calculated average. The trimmed mean is best suited for data with large, erratic deviations or extremely skewed distributions.
What advantages does a trimmed mean have over the regular arithmetic mean?
A trimmed mean removes a small designated percentage of the largest and smallest values before calculating the average. Using a trimmed mean helps eliminate the influence of outliers or data points on the tails that may unfairly affect the traditional mean.
What is 5 trimmed mean in SPSS?
5% Trimmed Mean – This is the mean that would be obtained if the lower and upper 5% of values of the variable were deleted. If the value of the 5% trimmed mean is very different from the mean, this indicates that there are some outliers.
When to use a trimmed mean?
Trimmed Means and Inflation Rates. A trimmed mean may be used in place of a traditional mean when determining inflation rates from the Consumer Price Index (CPI) or personal consumption expenditures (PCE).
How the trimmed mean is used?
Trimmed means are used in reporting economic data in order to smooth the results and paint a more realistic picture. A trimmed mean removes a small designated percentage of the largest and smallest values before calculating the average.
What is the trimmed mean?
A trimmed mean (similar to an adjusted mean) is a method of averaging that removes a small designated percentage of the largest and smallest values before calculating the mean. After removing the specified outlier observations, the trimmed mean is found using a standard arithmetic averaging formula.