Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Descriptive statistics are used to describe the main features of a collection of data in quantitative terms. Descriptive statistics are distinguished from inferential statistics (or inductive statistics), in that descriptive statistics aim to quantitatively summarize a data set, rather than being used to support inferential statements about the population that the data are thought to represent. Even when a data analysis draws its main conclusions using inductive statistical analysis, descriptive statistics are generally presented along with more formal analyses, to give the audience an overall sense of the data being analyzed. Descriptive statistics are useful for describing the basic features of data, for example, the summary statistics for the scale variables and measures of the data. In a research study with large data, descriptive statistics may help us to manage the data and present it in a summary table. One important use of Descriptive Statistics is to summarize a collection of data in a clear and understandable way. There are two basic methods: numerical and graphical. Using the numerical approach one might compute statistics such as the mean and standard deviation. Using the graphical approach one might create a stem and leaf display and a box plot. Graphical methods are better suited than numerical methods for identifying patterns in the data. Numerical approaches are more precise and objective. Types of descriptive statistics 1. Measure of central tendency: In descriptive statistics, the measure of central tendency measures the average value of the sample. In descriptive statistics, there are two types of averages: the first are the mathematical averages and the second are the positional averages. The mathematical averages are of three types: arithmetic mean, geometric mean, and harmonic mean. In descriptive statistics, the arithmetic mean is the most widely used measure for central tendency; it can be obtained by adding all the items of the series and dividing this total by the number of items. In descriptive statistics, the geometric mean is defined as the nth root of the products of all the n values of the variable. In descriptive statistics, the geometric mean is used when the items in the series are very large. The harmonic mean is defined as the reciprocal of the item. In descriptive statistics, the harmonic mean is useful in finding the averages that involve speed, time, price and ratio. There are two types of positional average: the median and the mode. In descriptive statistics, the median is the average value of the series in which half the values are less than the median and half the values are greater than the median. The mode, the second positional average, shows a higher frequency in the series. 2. Measure of dispersion: In descriptive statistics, we can elaborate upon the data further by measuring the dispersion. In descriptive statistics, usually the range of the standard deviation and variance is used to measure the dispersion. In descriptive statistics, range is defined as the difference between the highest and the lowest value. In descriptive statistics, the standard deviation and variance are usually used to measure the dispersion. Standard deviation is also called the root mean square deviation. Variance is also used to measure the dispersion, which can be simply derived from the square of the standard deviation