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inlier, outlier The terms 'inlier' and 'outlier' each describe a situation where a outcrop of one type of rock appears at the surface completely surrounded by another. This is usually a result of erosion having removed part of an overlying rock unit from an underlying unit. An inlier is then an isolated region of underlying rock exposed by erosion of the overlying units, whereas an outlier is an isolated remnant of overlying rock that has survived the erosion that has stripped it away everywhere else to reveal the underlying rocks. In regions of flat-lying or gently dipping strata, inliers tend to occur in valley bottoms whereas the hilltops may be occupied by outliers. Where the strata have been strongly folded prior to erosion these simple topographic relationships do not necessarily apply, and it is possible to have an inlier preserved in the core of an anticline occupying high ground or an outlier preserved in the core of a syncline occupying low ground. Inliers and outliers can also be generated by fault move-ments followed by erosion. For example, if an older unit is thrust over a younger unit erosion can isolate part of the thrust sheet, leaving an outlier of older rock surrounded by younger rock (a reversal of the usual age relation-ship). Similarly erosion can expose a window through the thrust sheet to reveal an inlier of younger rock surrounded by older rock. Fault movements by which blocks of terrain move up or down relative to each other, as when horsts or grabens are formed, can also produce inliers and outliers.
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The biggest time difference in the world between two locations is 26 hours. This difference occurs between Baker Island and the Line Islands in the Pacific Ocean.
The name for the elevation difference between adjacent contour lines is the contour interval.
The largest time difference between any two countries in the world is 26 hours. This difference occurs between Baker Island and the Line Islands, which are located in the Pacific Ocean.
The difference between 14 degrees and -5 degrees is 19 degrees. If you are calculating the absolute value of the temperature difference, it would be the same as 19 degrees.
The longest time zone difference between two locations on Earth is 26 hours.
Range is the largest minus the smallest value in the data set. An outlier is a value that is far away from the majority of the data.
Calculate the mean, median, and range with the outlier, and then again without the outlier. Then find the difference. Mode will be unaffected by an outlier.
The mean is affected the most by an outlier.
Yes, the range is affected by outliers because it is calculated as the difference between the maximum and minimum values in a dataset. An outlier can significantly increase the maximum value or decrease the minimum value, thereby expanding the range. Consequently, even a single outlier can distort the perception of variability within the data.
No, median is not an outlier.
OK to find out what is an outlier: OK lets say u have a 5 no. and they are 1,2,3,4,and 55 <---- 55 would have been your outlier because it is a huge difference from the other no. well i hope that help you out :D
Removing an outlier has a more significant impact on the range than on the median. The range, defined as the difference between the maximum and minimum values, can be dramatically altered if the outlier is either the highest or lowest value. In contrast, the median, which represents the middle value of a dataset, is less affected by extreme values, especially in larger datasets. Thus, the range is more sensitive to the removal of outliers compared to the median.
0s are not the outlier values
Depends on whether the outlier was too small or too large. If the outlier was too small, the mean without the outlier would be larger. Conversely, if the outlier was too large, the mean without the outlier would be smaller.
There would be a difference to the median. The old number wouldn't be the median but the mode wouldn't change. If the outlier is a high value, it will cause the mean value to shift to the higher side, while a low valued outlier will drop the mean value to a lower number.
To determine how much an outlier decreases the answer, you need to compare the statistical measure before and after including the outlier. For example, if the mean of a dataset is 50 without the outlier and drops to 40 with the outlier included, the outlier decreases the answer by 10. The specific impact of an outlier can vary significantly depending on its value relative to the rest of the data.
No. A single observation can never be an outlier.