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Descriptive statistics mainly refers to the term that is concerned with summary statistics that primarily focuses on describing quantitively or summarizing various features mainly from a collection of information. We can say that descriptive statistics mainly deals with the process of using and evaluating those statistics.The term descriptive statistics is different from the internal statistics or inductive statistics mainly in terms of its aim to summarize a sample instead of using the data or information to learn about the population that the sample of data is thought to represent. Thus, we can say that descriptive statistics is not similar to inferential statistics as it is not developed on the basis of probability theory and are frequently non-parametric statistics. It is analyzed that when in case a data analysis tends to draw its main conclusion by taking into consideration the use of inferential statistics the descriptive statistics are usually not presented. It is extremely important to note that there are some measures that are usually being adopted or used in order to describe a data or information set are mainly referred as measures of central tendency and measures of variability or dispersion. Even it is examined that measures of central tendency takes into account the mean, median, and mode. Whereas the measures of variability take into consideration the standard deviation and the variance, the maximum and the minimum values of the variables, kurtosis and skewness. Descriptive statistics tends to have various use in statistical analysis that include providing simple summaries related to the sample and about various observation that have been made.
We can say that such type of summaries might be either quantitative that is mainly summary statistics or visual that refers to simple-to-understand graphs. It is analyzed that these summaries might either tends to form the basis of the initial description of the data or information mainly as part of a more extensive statistical analysis or they may be sufficient enough in and of themselves for a particular investigation. However, for better understanding we can take help of an example that will better reflect what is descriptive statistics. For example, we can say that the shooting percentage in basketball tends to be a descriptive statistic that primarily summarizes the performance of a player or a team. We can claim that this is the number of shots that is made divided by the number of shots taken.
The Use of Descriptive Statistics
The use of descriptive and summary statistics tends to have an extensive history and indeed the simple tabulation of population and of economic data was the first manner the topic of statistics appeared. However, it is extremely important to note that in case of business world scenario descriptive statistics tends to provide a useful summary of many types of data or information. We can take an example where an investor or a broker might use a historical account of return behaviour by mainly performing empirical and analytical analyses on their respective investment primarily in order to make efficient and better investing decisions in the future. We can say that mainly there are four major types of descriptive statistics that are namely measures of frequency that include count, percent, frequency, and many more. Measures of central tendency that takes into consideration mean, median, mode. Measures of dispersion or variation that include range, variance, standard deviation. Lastly, measures of position that include percentile ranks, quartile ranks.
The Main Purpose Of Descriptive Statistics
The main purpose of using the descriptive statistics is to efficiently and clearly describe the basic features of the data in case of a particular study. Descriptive statistics tends to provide simple summaries in relation to sample and the measures. We can claim that together with the simple graphics analysis they tend to form the basis of virtually each quantitative analysis of data or information. One should know that for writing the descriptive statistics results or outcomes there is a specific format that needs to followed so that we can get better understanding of the study and their respective data and information. First step refers to adding a table of the raw data or information in the appendix format. A table needs to included that must have appropriate and relevant descriptive statistics for an example the mean, median, standard deviation, and various other forms of measures. We can say that descriptive statistics must be appropriately relevant to the ultimate aim of the study. It should be included for the sake of it. In case, if one is not intending to make use of the mode then he/she should not make use of it for the particular study. Identification of the level or the data must be done. It should be noted that the selection of statistics must be justified based on the level of data. However, in most of the cases, the interval or ration data is applicable. There are four levels of data namely internal, ratio, ordinal, or nominal. Graph must be included and graph should have a proper title that augers well with the particular purpose of the study and all the axes should be well labelled and structured. It must be ensuring that the graph is mainly related to the ultimate aims or objective of the study and the graph should only one.
In simple terms we can say that the structured graph must reflect an appropriate and relevant answer to the research question. It is always advisable to provide a clear and reliable explanation of the statistics in a short and concise paragraph. We should make sure that reader must be able to understand each and every distribution table of the respective study and must clearly predicts and understand the meaning of the data or information that has been mentioned in the graph. Even though it is advisable to write a short and simple paragraph at the end of the study however, we need to ensure that the paragraph must have all required and relevant details related to the study. In short, we can say that paragraph must takes into consideration or capture all minute details in table and graph. Even proper explanation must be there related to skewed data or factors that accounts for high levels of standard deviation.
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