# Mean, Median and Mode

The mean, median and mode are also known as the measures of central tendency. Each of the measures provide researchers with specific types of information pertaining to the distribution of values in order to gain a better understanding of the values and what the collection of data means (Salkind, 2017).

# Definitions

Mean:

The “mean,” also known as the “average,” is used to compute the average value of a set of data points. As an example, if you wanted to compute the mean of a set of scores in a given class, you would add all of the scores and divide that sum by the total number scores. The formula for computing the mean would be the following:

is the mean value from the calculation.

is the sum of all of the values.

n is the size of the sample or the number of values.

Median:

The “median” is the middle value when the values in the data set are listed from smallest to largest. In the event that an even number of values are in a data set, the two middle values must be added together and divided by 2.

Mode:

The “mode” is the value that appears in the dataset the most frequently. It is possible that more than one value appears the most times.

# Sample Data

The following data set will be used in order to practice computing a mean, median and mode. The values below are student grades for a “Practice Test” in an Introductory Computer Science course which was given to students at the beginning of a semester. The instructor will use these results and compare these results with their final exam, which includes the same questions as the “Practices Test.”

# Instructional Video

# Conclusion

As seen in the table above, and from the sample data provided, the mean is equal to 65.44, the media is 62 and the mode is 58. This data shows that the data is normally distributed.

In the instance of this introductory Computer Science course, the instructor now has valuable information on which students fall below the average (or mean) score in the class. The instructor can adequately personalize the learning experience for those who have lower achievement scores or low levels of prior knolwedge of the course content. Additionally, the measures of central tendency can be compared with the scores of the final exam, which is identitical to this pre-test, in order to alter future offerings of the course and provide additional instructional time for areas of low scores.

Salkind, N. (2017). Statisitics for people who (think they) hate statistics. Thousand Oaks, CA: SAGE Publications.