Final answer:
Methods that summarize or describe characteristics of data are called descriptive statistics. They organize and present data, using measures like the average. Descriptive statistics differ from inferential statistics, which are used for making predictions.
Step-by-step explanation:
Understanding Descriptive Statistics
Methods used that summarize or describe characteristics of data are called descriptive statistics. These methods are vital in organizing and summarizing data in both numerical and graphical ways. Examples of descriptive statistics include finding the average, or mean, which is a measure of central tendency, and the standard deviation, which indicates the spread of data around the mean. Whereas descriptive statistics aim to summarize the data, inferential statistics use probability to make predictions and draw conclusions from data.
In scientific investigations and analysis, understanding the use of statistics is essential. When a scientist calculates the average decrease in tumor size, for instance, they are employing descriptive statistics to summarize the data collected.
A statistic is a numerical representation of a characteristic from a sample, and it is used to estimate a population parameter, which is a characteristic of the entire population. When dealing with all available data, the values calculated are parameters, such as the average score for all math classes, compared to a sample statistic, like the average score for a single math class.