Advantages of descriptive statistics pdf
Advantages of descriptive statistics pdf

This article "Advantages of descriptive statistics pdf" will lead you to understand about types of descriptive statistics.


The descriptive statistics is one of the most frequently used statistical method by statisticians. As compared to inferential statistics, it uses two statistical measures namely mean, median, minimum, maximum, standard deviation, variance, range and count. Also, it allows for comparisons between different groups of samples which may be collected in either categorical or continuous form. Therefore, it allows us to analyze any sample that contains numerical values. It can also be used to compare samples which have a large number of features and compare them across categories. A good example of its application is given by economists who need to compare a group of persons’ income levels. So, before proceeding further, let us discuss some other advantages. Firstly, a sample provides a snapshot of the population at a particular time. This means that we can use this information to make predictions based on what proportion of our sample will fall within a certain range. Secondly, the dataset provided by descriptive statistics allows us to draw conclusions about a whole population. For instance, if we have two groups, say, male or female, you know which gender group consists of more people and how many members. By using such a dataset, we can easily predict their income levels. Thirdly, some variables are often treated as independent when working with descriptive statistics. They include area, age, profession and income level. These depend on their own characteristics and cannot be isolated from each other. Moreover, they cannot change over time as they do not occur randomly. Such observations allow us to determine the impact of treatment on various factors in the health of people which includes blood pressure, cholesterol levels etc. Fourthly, by estimating the mean, we can better understand the distributions of the samples. Fifthly, by calculating the mean of your population, you can decide where the sample lies. An effective way to discover where a particular sample lies is to look at its medians, minimums and maximums. Lastly, a large number of samples may provide greater validity when making decisions about the population as it has a high chance of containing outliers. Hence it prevents our sample from leading to misclassification of data. In conclusion, it can be safely said that the following paragraphs summarize the main applications of the descriptive statistic as well as the various advantages associated with it.

Types Of Descriptive statistics

1. Mean

2. Median

3. Mode

4. Standard Deviation

5. Variance

6. Range

7. Count

8. Central Tendency

9. Percentiles

10. Skewness

11. Kurtosis

12. Histogram

13. Scatterplots

14. Strict Uniformity

15. Coefficient of Correlation

16. Pearson's Rank

17. Chi-square

18. Nonparametric Spearman's R

19. Numerical Average

20. Poisson's Distribution

21. Regression

22. Bivariate Analysis (Multiple Linear Models)

23. Multivariate Analysis (Multivariate Logistic Regression Models)

24. Student's t-Distribution

25. Two Sample Test

26. ANOVA

27. Generalized Tests

28. T-Test