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Apr
Examples Of Inferential And Descriptive Statistics. The term implies that information has to be inferred from the presented data. It makes our analysis become powerful and meaningful. On the contrary in Inferential statistics researchers test the hypothesis. The following example illustrates how we might use descriptive statistics in the real world.
A data set is a collection of responses or observations from a sample or entire population. A population is a group of data that has all of the information that youre interested in using. For example we could calculate the mean and standard deviation of the exam marks for the 100 students and this could provide valuable information about this group of 100 students. It allows us to compare data make hypothesis and predictions. We are interested in understanding the distribution of test scores so we use the following descriptive statistics. Inferential statistics are produced through complex mathematical calculations that allow scientists to infer trends about a larger population based on a study of a sample taken from it.
It allows us to compare data make hypothesis and predictions.
The difference of descriptive statistics and inferential statistics are. It allows us to compare data make hypothesis and predictions. They are available to facilitate us in estimating populations. We are interested in understanding the distribution of test scores so we use the following descriptive statistics. In quantitative research after collecting data the first step of statistical analysis is to describe characteristics of the responses such as the average of one variable eg age or the relation between two variables eg age and creativity. A data set is a collection of responses or observations from a sample or entire population.