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Descriptive Statistics is the way to summarize and interpret the collected data so that a meaningful pattern is formed.
Hence, applying descriptive statistics requires two types of statistical ideas: Graphical summary uses graphical representation to analyze data. Second is the, measure of central tendency also called numerical summary. In case of numerical summary, mean, median, mode, quartile are used to analyze the given data.
It is the study conducted for inferring or equating our data with the general conditions. So, this shows the difference between inferential statistics and descriptive statistics. Inferential statistics is used in the broader area of statistical study. Hence, the method used in inferential statistics is sample, testing of hypothesis, principle component analysis and regression. Explaining it further with an example: If you need to calculate the marks of students of a class, knowledge of Descriptive statistics can be applied but on the other hand if you want to calculate the marks of entire students of Australia, you need to apply the knowledge of Inferential statistics in which a correct sample from a particular population is drawn to get the result.
These are two major areas in statistics. Hence, studying statistics broadens up knowledge in practical fields and thus serve as a helpful tool in taking decisions wisely. Students generally face problems with their assignment and homework in statistics. But acquainted with the fact that, completing statistical homework and assignment is equally important for a better score, our online service is there to help you to complete your assignment on Statistics.
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Free Statistics Help - Statistics Problems This section will contain our repository of solved statistics problem. We hope such problems will help you to get a better grasping of statistical concept, or maybe they can help you to get inspired to be able to solve those problems from your statistics homework that are nagging you. In our statistics homework help free section, you will find lessons covering topics such as common ways to describe data, summarizing data, different ways to collect and represent data, cumulative frequency, frequency tables, descriptive statistics, correlation, probability, inferential statistics, and more.