These refers to the techniques that attempt to summarize our data with a single value that identifies the center of the data.

Question: These refers to the techniques that attempt to summarize our data with a single value that identifies the center of the data.

The techniques that attempt to summarize our data with a single value that identifies the center of the data are called measures of central tendency. The three most common measures of central tendency are the mean, median, and mode.

• Mean: The mean, also known as the arithmetic average, is calculated by adding up all of the values in the data set and dividing by the number of values.
• Median: The median is the middle value in the data set when the values are arranged in order from smallest to largest.
• Mode: The mode is the most frequent value in the data set.

Each measure of central tendency has its own strengths and weaknesses. The mean is a good measure of central tendency for most data sets, but it can be skewed by outliers. The median is a good measure of central tendency for data sets that contain outliers. The mode is a good measure of central tendency for data sets that are categorical or ordinal.

It is important to choose the right measure of central tendency for your data set. The best measure of central tendency will depend on the type of data you have and the question you are trying to answer.

Here is an example of how to choose the right measure of central tendency:

Suppose you have a data set of the heights of 100 students. You are interested in knowing what the average height of the students is. The mean height would be a good measure of central tendency to use in this case.

However, if one of the students in the data set is 7 feet tall, the mean height will be skewed by this outlier. In this case, the median height would be a better measure of central tendency to use.

It is also important to consider the type of data you have when choosing a measure of central tendency. For example, if you have a data set of the colors of students' eyes, the mode would be a good measure of central tendency to use, since the data is categorical.

By choosing the right measure of central tendency, you can get a better understanding of the center of your data set.

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