Go into your data to determine which values are outliers and if they're significant and random (not an apparent group), eliminate them. This will take them out of your boxplot.
an outliers can affect the symmetry of the data because u can still move around it
Outliers
Outlier: an observation that is very different from the rest of the data.How does this affect the data: outliers affect data because it means that your calculations might be off which makes it a possibility that more than the outlier is off.
I think it means that our data includes outliers.
Go into your data to determine which values are outliers and if they're significant and random (not an apparent group), eliminate them. This will take them out of your boxplot.
There is no limit to the number of outliers there can be in a set of data.
Mean- If there are no outliers. A really low number or really high number will mess up the mean. Median- If there are outliers. The outliers will not mess up the median. Mode- If the most of one number is centrally located in the data. :)
No. Outliers are part of the data and do not affect them. They will, however, affect statistics based on the data and inferences based on the data.
an outliers can affect the symmetry of the data because u can still move around it
In statistics, outliers are values outside the norm relative to the rest of collected data. Many times they can skew the results and distort the interpretation of data. They may or may not indicate anything significant; they might just be an anomalous data point that is not significant. It is difficult to tell.
It is not.
In chemistry, outliers are data points that deviate significantly from the rest of the data set. Outliers can result from measurement errors, experimental uncertainties, or unexpected reactions. It is important to identify and address outliers in data analysis to ensure accurate and reliable results.
Outliers
If the data numbers are all really close together than no. But if the data has numbers; for example: 12,43,45,51,57,62,90 (12 and 90 are the outliers) which are really far aprt, than yes.
They are called extreme values or outliers.
Mode: Data are qualitative or categoric. Median: Quantitative data with outliers - particularly if the distribution is skew. Mean: Quantitative data without outliers, or else approx symmetrical.