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Lower quartile - (1.5*IQR)

Upper quartile + (1.5*IQR)

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What is it called when the minimum and maximum values in a data set?

They are called outliers


What are data points that do not fit with the rest of a data set?

Data points that do not fit with the rest of a data set are known as outliers. These values are significantly different from the majority of the data, either much higher or lower, and can skew statistical analyses. Outliers may arise from variability in the data, measurement errors, or they could indicate a novel phenomenon worth investigating. Identifying and understanding outliers is crucial for accurate data interpretation.


What is Data that does not fit with the rest of a data set?

Data that does not fit with the rest of a data set is known as an outlier. Outliers can skew statistical analyses and distort the interpretation of data. They can be caused by errors in data collection, measurement variability, or may represent true but rare occurrences in the data set. Identifying and handling outliers appropriately is crucial in ensuring the accuracy and reliability of data analysis results.


How do you find the minimum value of a box and whisker plot?

It i the smallest value in the data set and corresponds to the value of the left-most end of the whisker. Unless there were outliers, in which case it will be an "X" to the left of the left-whisker.


What are outliers and how do they affect data?

Outliers are observations that are unusually large or unusually small. There is no universally agreed definition but values smaller than Q1 - 1.5*IQR or larger than Q3 + 1.5IQR are normally considered outliers. Q1 and Q3 are the lower and upper quartiles and Q3-Q1 is the inter quartile range, IQR. Outliers distort the mean but cannot affect the median. If it distorts the median, then most of the data are rubbish and the data set should be examined thoroughly. Outliers will distort measures of dispersion, and higher moments, such as the variance, standard deviation, skewness, kurtosis etc but again, will not affect the IQR except in very extreme conditions.

Related Questions

Can there be 2 outliers in a set of data?

There is no limit to the number of outliers there can be in a set of data.


What data that does not fit well with the rest of a data set.?

They are called extreme values or outliers.


What is it called when the minimum and maximum values in a data set?

They are called outliers


Do they have outliers in a data set?

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.


What are data points that do not fit with the rest of a data set?

Data points that do not fit with the rest of a data set are known as outliers. These values are significantly different from the majority of the data, either much higher or lower, and can skew statistical analyses. Outliers may arise from variability in the data, measurement errors, or they could indicate a novel phenomenon worth investigating. Identifying and understanding outliers is crucial for accurate data interpretation.


What Is data that does not fit with the rest of the data set?

Anomalous Data


How would you explain the outliers in chemistry?

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.


What is Data that does not fit with the rest of a data set?

Data that does not fit with the rest of a data set is known as an outlier. Outliers can skew statistical analyses and distort the interpretation of data. They can be caused by errors in data collection, measurement variability, or may represent true but rare occurrences in the data set. Identifying and handling outliers appropriately is crucial in ensuring the accuracy and reliability of data analysis results.


What is grubbs algorithm?

Grubbs test is used to detect outliers in a univariate data set.


In general the median of a data set is more resistant to outliers than the mean.?

Yes, it is.


How can you determine which measure of central tendency is best for the set if 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. :)


Why do they invented the stem and the leaf plot?

to organize your data set and figure out mean, median, mode, range, and outliers.