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Descriptive And Inferential Statistics Summary. In order to understand the key differences between descriptive and inferential statistics as well as know when to use them you must first understand what each type of statistics does and what it is used to analyze. - to catch mistakes - to see patterns in the data - to find violations of statistical assumptions. Descriptive statistics is the statistical description of the data set. Use descriptive statistics to summarize and graph the data for a group that you choose.
In order to understand the key differences between descriptive and inferential statistics as well as know when to use them you must first understand what each type of statistics does and what it is used to analyze. The statistical results incorporate the uncertainty that is inherent in using a. Descriptive statistics is the statistical description of the data set. These observations had been described by the descriptive statistics. For inferential statistics we need to define the population and then devise a sampling plan that produces a representative sample. To understand the simple difference between descriptive and inferential statistics all you need to remember is that descriptive statistics summarize your current dataset and inferential statistics aim to draw conclusions about an additional population outside of your dataset.
A common first step in data analysis is to summarize information about variables in your dataset such as the averages and variances of variables.
Inferential statistics is the drawing of inferences or conclusion based on a set of observations. Descriptive statistics is the statistical description of the data set. In summary the difference between descriptive and inferential statistics can be described as follows. TYPES OF STATISTICS Descriptive Statistics Inferential Statistics DESCRIPTIVE STATISTICS. Descriptive statistics are just descriptive. Descriptive statistics summarize the characteristics of a data set.