Statistics is everything about the data presentation, compilation and interpretation. If the conducted survey supplies a lot of data interpretation and the presentation is very impressive with clear details that makes you stand out of the crowd. The data presentation and interpretation goes in a careful way. The employees in an organisation will be with analytical and logical skills.

## Analytical skills:

Analytical skills are the most important skill which it covers the central theme of any statistical related matters. An employee in an organisation with the skill of analysis of numbers, he can work in a corporate. Statistics is mathematics related subject, and it is the part of mathematics, but depends on a specific factor to approach a compiled data. The quality of learning the data from a different angle can be helpful to upgrade your own skills that can be benefited with the years of experience. The statistical methods research the huge amount of data and their properties. Statistics used in various streams such as business, physical, psychology, humanities, government, industries and social sciences. The statistical data and methods can be collected using sampling methods and other procedures. There are two types of statistical factors used in analysing data,

1. Descriptive Statistics
2. Inferential Statistics

Descriptive method is used to collect data from sampling mean or SD (Standard Deviation), whereas inferential statistics are used when the methods are views as a subclass for a particular region.

### Mean:

A mathematical average of the group of one, two or more numbers are called as mean. The mean for a particular set of numbers can be calculated in the number of ways having an inclusion of geometric mean and arithmetic mean. Arithmetic mean explains how the good the commodity acted over the time whereas the geometric mean explains the results of investors who invested in the same commodity at the same time. In calculating the sampling size of the mean, the procedures / algorithms works by adding all the data values collected from the sampling and dividing the sum by the set of data items.

### Regression Analysis:

Regression analysis is used in the statistics to understand the independent variable related to the dependent variable if any exists between sets of data to explore the methods of the relationship. The regression analysis is used to determine the linear relationship between the dependent variable with over one independent variables, is used to forecast the number of dependent variables.

### Variance:

It is a measurement of the numerical values in a data set. The distance of each number in the set is from the mean deviation which can be measured by variance. Variance can help the risks to be determined where the investor may accept while buying an investment. The analysis of variance is to compare the performance of various stocks.

Logical Conclusion is tough to present the logical conclusion. To conclude the logical part, one needs to be experienced in data storage, data collections, data interpretation and data analysis. Having said, statistics writing is the part of mathematics which deal with data collection, interpretation, data analysis and the organisations of data. While applying statistics to the organisational related matters, scientific or social problem, the statistics can be conventional to start with a population or model statistics which the process to be studied.

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