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Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data. Various techniques that are commonly used are classified as: - Graphical description in which we use graphs to summarize data.
- Tabular description in which we use tables to summarize data.
- Summary statistics in which we calculate certain values to summarize data.
In general, statistical data can be described as a list of subjects or units and the data associated with each of them. Although most research uses many data types for each unit, we will limit ourselves to just one data item each for this simple introduction.
We have two objectives for our summary:
- We want to choose a statistic that shows how different units seem similar. Statistical textbooks call the solution to this objective, a measure of central tendency.
- We want to choose another statistic that shows how they differ. This kind of statistic is often called a measure of statistical variability.
When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the arithmetic mean, the median, or the mode. Sometimes, we choose specific values from the cumulative distribution function called quantiles. A statistic (singular) is the result of applying a statistical algorithm to a set of data. ...
In statistics, central tendency is an average of a set of measurements, the word average being variously construed as mean, median, or other measure of location, depending on the context. ...
A statistic (singular) is the result of applying a statistical algorithm to a set of data. ...
In descriptive statistics, statistical dispersion (also called statistical variability) is quantifiable variation of measurements of differing members of a population within the scale on which they are measured. ...
In mathematics and statistics, the arithmetic mean (or simply the mean) of a list of numbers is the sum of all the members of the list divided by the number of items in the list. ...
In probability theory and statistics, a median is a number dividing the higher half of a sample, a population, or a probability distribution from the lower half. ...
In, mode means the most frequent value assumed by a random variable, or occurring in a sampling of a random variable. ...
In probability theory, the cumulative distribution function (abbreviated cdf) completely describes the probability distribution of a real-valued random variable, X. For every real number x, the cdf is given by where the right-hand side represents the probability that the random variable X takes on a value less than...
This article or section does not cite any references or sources. ...
The most common measures of variability for quantitative data are the variance; its square root, the standard deviation; the range; interquartile range; and the average absolute deviation (average deviation). Quantitative data is data measured or identified on a numerical scale. ...
In probability theory and statistics, the variance of a random variable (or somewhat more precisely, of a probability distribution) is a measure of its statistical dispersion, indicating how its possible values are spread around the expected value. ...
In probability and statistics, the standard deviation of a probability distribution, random variable, or population or multiset of values is a measure of the spread of its values. ...
In descriptive statistics, the range is the length of the smallest interval which contains all the data. ...
In descriptive statistics, the interquartile range (IQR) is the difference between the third and first quartiles and is a measure of statistical dispersion. ...
The absolute deviation of an element of a data set is the absolute difference between that element and a given point. ...
[edit] Steps in descriptive statistics - Collect data
- Classify data
- Summarize data
- Present data
- Proceed to inferential statistics if there are enough data to draw a conclusion.
==statistics]] In Christian liturgy, a collect is both a liturgical action and a short, general prayer. ...
For Wikipedias categorization projects, see Wikipedia:Categorization. ...
Statistical classification is a type of supervised learning problem in which labeled training data is used to create a function that will correctly predict the label of future data. ...
Street preacher in Covent Garden using a presentation style Presentation is the process of presenting the content of a topic to an audience. ...
It has been suggested that this article or section be merged with statistical inference. ...
For other uses, see Data (disambiguation). ...
A conclusion can have various specific meanings depending on the context. ...
Data mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns using tools such as classification, association rule mining, clustering, etc. ...
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