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When to Do Descriptive Analysisĭescriptive analysis is often used when reviewing any past or present data. If in doubt, review the four types of descriptive analysis methods explained above.
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What methods you choose will depend on the data you are dealing with and what you are looking to determine. Cleaning data may involve changing its textual format, categorizing it, and/or removing outliers.įinally, descriptive analysis involves applying the chosen statistical methods so as to draw the desired conclusions. This is because data may be formatted in inaccessible ways, which will make it difficult to manipulate with statistics. This can be done in a variety of ways, but surveys and good old fashioned measurements are often used.Īnother important step in descriptive and other types of data analysis is to clean the data. The first step in any type of data analysis is to collect the data. With that said, the process of descriptive analysis usually consists of the same few steps.
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In other words, it’s up to you what you want to look for in your analysis. Like many types of data analysis, descriptive analysis can be quite open-ended.
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Image by Goumbik How to Do Descriptive Analysis This is where measures like percentiles and quartiles can be used. Last of all, descriptive analysis can involve identifying the position of one event or response in relation to others. In order to measure this kind of distribution, measures of dispersion like range or standard deviation can be employed. However, if one individual is five feet tall and the other is seven feet tall, the average height is still six feet. If both individuals are six feet tall, the average height is six feet. To illustrate this, consider the average height in a sample of two people. Sometimes, it may be worth knowing how data is distributed across a range. In this case, the mean average would be a very helpful descriptive metric. As an example, consider a survey in which the height of 1,000 people is measured. Common measures of central tendency include the three averages - mean, median, and mode. In descriptive analysis, it’s also worth knowing the central (or average) event or response. A list of 1,000 responses would be difficult to consume, but the data can be made much more accessible by measuring how many times a certain flavor was selected. For example, consider a survey where 1,000 participants are asked about their favourite ice cream flavor. This is the purpose of measures of frequency, like a count or percent. In descriptive analysis, it’s essential to know how frequently a certain event or response occurs.