Which measures of spread are resistant to outliers?
Which measures of spread are resistant to outliers?
Use median if the distribution has outliers because the median is resistant to outliers. measures of spread are range, IQR, and standard deviation. Use standard deviation anytime mean is used for the center (symmetric distribution). Use IQR anytime median is used for the center (skewed distribution).
What is a resistant measure of center?
The median is not affected by outliers, therefore the MEDIAN IS A RESISTANT MEASURE OF CENTER. For a symmetric distribution, the MEAN and MEDIAN are close together. In a skewed distribution, the mean is farther out in the long tail than the median.
What are the three measures of spread?
Measures of spread include the range, quartiles and the interquartile range, variance and standard deviation.
What measure of center best represents the data set?
median
Will a data set always have one mode?
Explanation: Mode is an item that occurs more number of times in a distribution. In an Individual Observation, if each item occurs only once, you will not get mode. In a Discrete Distribution and Continuous Distribution, there is mode always.
Can a data set have more than one median?
Q. A data set can have more than one median? It is possible to have three numbers in the middle of a data set.
What if there is no mode in a data set?
It is possible for a set of data values to have more than one mode. If there is no data value or data values that occur most frequently, we say that the set of data values has no mode.
What is the significance of mean median and mode?
The mean (average) of a data set is found by adding all numbers in the data set and then dividing by the number of values in the set. The median is the middle value when a data set is ordered from least to greatest. The mode is the number that occurs most often in a data set.
Is the median affected by extreme values?
The median does not have to be one of the data values. The median does not use all of the data values, only the one(s) in the middle. The median is resistant to change, it is not affected by extreme values.
Which measure is most affected by extreme values?
Range is the most simple and commonly understandable measures of dispersion. Range is defined as the difference between the highest(or largest ) and lowest(or smallest) observed value in a series. Therefore, it is the most affected measures of dispersion by the extreme values of the series.
Which average is most affected by extreme values?
Arithmetic mean
Which measure of central tendency is not resistant to extreme values?
medians
Which measure of central tendency better describes hours worked?
Mean is the most frequently used measure of central tendency and generally considered the best measure of it. However, there are some situations where either median or mode are preferred. Median is the preferred measure of central tendency when: There are a few extreme scores in the distribution of the data.
Which of the following measures is not easily affected by extreme values?
Is the mode affected by extreme values?
The mode is not affected by extreme values. The mode is easy to identify in a data set and in a discrete frequency distribution.
Which of the following is least affected by extreme values?
Median is the value that divides the data set in exactly two parts. One of the advantages of median is that it is not effected by the outliers.
Is the interquartile range affected by extreme values?
The interquartile range (IQR) is the distance between the 75th percentile and the 25th percentile. Because it uses the middle 50%, the IQR is not affected by outliers or extreme values.
What does the interquartile range tell us?
The “interquartile range”, abbreviated “IQR”, is just the width of the box in the box-and-whisker plot. The IQR tells how spread out the “middle” values are; it can also be used to tell when some of the other values are “too far” from the central value.
Why is interquartile range important?
Besides being a less sensitive measure of the spread of a data set, the interquartile range has another important use. Due to its resistance to outliers, the interquartile range is useful in identifying when a value is an outlier. The interquartile range rule is what informs us whether we have a mild or strong outlier.
How do you find the interquartile range of an odd set of numbers?
We can find the interquartile range or IQR in four simple steps:
- Order the data from least to greatest.
- Find the median.
- Calculate the median of both the lower and upper half of the data.
- The IQR is the difference between the upper and lower medians.