Descriptive statistics is the term provided to the examination of data that helps to summarize or show data in a meaningful manner. Inferential Statistics called sampling is used to make sure the sample chosen represents the population as closely as possible.
In descriptive statistics, data summarized and represented in an accurate way using charts, tables, and graphs whereas inferential Statistics determines the probability of the characteristics of the sample using probability theory. Descriptive statistics is the term of statistics given to the survey of data that helps describe, show or abstract data in a significant extent.
Descriptive statistics are very significant because if we present our raw data, it would be hard to imagine what the data was showing, especially if there was a lot of it. Descriptive statistics, therefore, allows us to present the data in a more meaningful way, which allows simpler interpretation of the data. Descriptive statistics describe data through statistics and graphs is an important topic and discussed in other agrarian Statistics guides.
Inferential statistics, unlike descriptive statistics, is the effort to apply the conclusions obtained from one experimental study to more general populations. Median is the measure that lies exactly in the center when the data is arranged in either ascending or descending order. Mode is the value that occurs most frequently in the data. The harmonic mean is the best measure of central tendency when the data are in rates and ratios.
The geometric mean is used when we must average the percentages and rates of change. Dispersion measures how scattered the data is around the mean. It is also called the distance measure as it measures the distance between the average and all the other values in the data. The simple measure of dispersion is the range, which is the difference between the maximum and minimum values in the data.
The most frequently used measure of dispersion is standard deviation which measures the root mean of squared distance between the mean and the other observations. The quartile deviation is used to understand the distribution of the data and to identify the outliers.
Box plot is a visual representation of a five-point summary of the data such as minimum value, maximum value, median Q2 , first quartile Q1 , and second quartile Q2. Also Read: Understanding Distributions in Statistics. When the population is very large, then collecting the data, compiling them, and calculating descriptive statistics, sometimes accuracy, will be a cumbersome process. For example, an HR manager may be interested in understanding the effectiveness of training in the performance of the employees.
He has to make the decision based on the available data, and most of the time, it is done through sampling. All the summary measures, such as mean, median, mode, standard deviation, quartiles, etc.
This part of inferential statistics is known as Parameter estimation. Making inferences about the population from the sample data involve uncertainties, i. This uncertainty is to be reduced. The sample statistic should be very close to the parameter. Here one seeks the help of probability distribution. Every data is expected to follow a certain probability distribution.
The probabilities that we get from this distribution will help us to ensure whether the statistics are closer to the parameter or not. How to show cause and effect relationship? How to get the underlying structure? What is exploratory statistics? I read somewhere that analysis could be descriptive, inferential or exploratory in nature. Good question. For example, one might ask questions about how people like to get around a city and explore that problem exploratory , before jumping into questions about what color scooters people like best.
Statistical data can be classified in several ways. Here we provide an overview of the major types of data in… Read more. In statistics, there are four data measurement scales: nominal, ordinal, interval and ratio. These are simply ways to sub-categorize different… Read more.
Descriptive Statistics. Image Source: Wikipedia. Tags: data analysis , statistics. Next post Awesome Data Visualizations. I like the way you wrote this like you would have said it. Are tables and graphs examples of descriptive statistics or inferential statistics?
Thanks so much, it was wonderful, now I get the clear concept on data analysis. Simple and concise article. Really helped with getting overview. Excellent explanation. Thanks a lot! Leave a reply Cancel reply Your email address will not be published.
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