Here, we are going to look at the concept of univariate analysis. Let’s now get an in-depth look at descriptive statistics However, regardless of these shortcomings, descriptive statistics are still the best way of summarizing a wide range of data and aid in making comparisons between the same.
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This is because the number just gives an overall impression of the aspects but does not provide the exact detail of the same.įor example, the GPA of a student does tell whether the student performed well in the easy subjects and failed the hard one or vice versa. It is important to note that, when using a single value to describe a large set of data, there is a possibility that you are going to change the original meaning of the data or lose some important detail. The moment one looks at the GPA of a student, he can tell the potential of that student on the various courses that he/she takes. This is just a single number that gives a general indication of the performance of a single individual. Another instance is determining the how a student performs in school. Here we can get a single number that will help us describe very many discrete events. Clearly, there are quite a number of activities in a single game therefore we can use descriptive statistics to make this simpler. Therefore, descriptive statistics comes in to break this numerous amounts of data into a simple form.įor example, one might be interested to find the average passes a footballer makes in a single match. In a study, there are quite a number of variables that are usually measured. On the other hand, descriptive statistics is used mainly to give a description of the behavior of the sample data.ĭescriptive statistics are usually used in presenting a quantitative analysis of data in a simple way. Thus, inferential statistics are used mainly to infer based on the sample data we have at hand to make conclusions. We can also use inferential statistics to judge on the probability of something occurring based on the behavior of the sample of data taken for a study. For inferential statistics, you are trying to come up with a conclusion drawing from the data you have.įor example, we can use inferential statistics to try and give an indication of what the population thinks from the sample. Basically, descriptive statistics is about describing what the data you have shown. Coupled with a number of graphics analysis, descriptive statistics form a major component of almost all quantitative data analysis.ĭescriptive statistics are quite different from inferential statistics. The main purpose of descriptive statistics is to provide a brief summary of the samples and the measures done on a particular study.
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