The mean is most sensitive to outliers because it is affected by the value of each data point. Outliers, which are extreme values, can significantly affect the mean.

The mean is calculated by adding up all the data points and dividing the sum by the number of data points.

The median is the middle value of a data set when arranged in ascending order. If there is an even number of data points, the median is the average of the two middle values.

The mode is the most frequently occurring value in a data set. A data set can have more than one mode.

Mean is the sum of all values divided by the number of values in a dataset. In this case, (1+2+3+4+5) / 5 = 3.

Median is the middle value of a dataset when assorted in numerical order. In this case, the values can be assorted as {1, 2, 3, 4, 5} and the middle value is 3.

Mode is the value that appears most frequently in a dataset. In this case, there is no value that appears more than once, so there is no mode.

The median is most appropriate for skewed data because it is not affected by outliers. The mean can be significantly affected by outliers, which can make it a less accurate measure of the center of skewed data.

The median is most appropriate for comparing two or more data sets because it is not affected by outliers. The mean can be significantly affected by outliers, which can make it a less accurate measure of the center of a data set.

Mean is the sum of all values divided by the number of values in a dataset. In this case, (1+2+3+4+5+6+7+8+9+10) / 10 = 55 / 10 = 5.5.

Median is the middle value of a dataset when assorted in numerical order. In this case, the values can be assorted as {1, 2, 3, 4, 5, 6, 7, 8, 9, 10} and the middle value is 5.5.

Mode is the value that appears most frequently in a dataset. In this case, there is no value that appears more than once, so there is no mode.

The mean is most appropriate for data that is normally distributed because it is the most efficient measure of the center of a normally distributed data set.

The median is most appropriate for data that is not normally distributed because it is not affected by outliers. The mean can be significantly affected by outliers, which can make it a less accurate measure of the center of a non-normally distributed data set.