The purpose of descriptive statistics is to describe and summarize data such that patterns are easier to identify. They ma, however, not be used to make about the data itself or about a hypothesis that may have been developed. Descriptive statistics are very important especially for a large amount of data as they make it easier for us to define the entire population. They provide information about like the overall population in the form of the central tendency and the spread of the data (Weiss, & Weiss, 2012). Descriptive statistics help to ease understanding of statistics. It is necessary to combine descriptive statistics with graphical displays. This is because graphical displays make it easier to understand data. It displays the way data is distributed in the sample.
When a set of data contains outliers or values that lie far away from the rest of the population, the median is more reliable. This is because it always lies within the rest of the population and is least affected by outliers (Weiss, & Weiss, 2012). Very large or small values are likely to affect the mean in a big way. This then necessitates the use of the median as the measure of central tendency.
The confidence interval gives us an idea of where the mean of the entire data set lies (Weiss, & Weiss, 2012). The confidence interval implies that there is a 95 % probability that the mean of the data set lies within the given interval of 4,250 gm/day – 4,750 gm/day. This implies that assuming that the mean lies within this interval has only a 5 % likelihood of being a wrong assumption.
Weiss, N. A., & Weiss, C. A. (2012). Introductory statistics. Pearson Education.
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