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Descriptive Statistics

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Probability Distributions

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Inferential Statistics

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Simple and Multiple Linear Regression

Correlation, Scattergram

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Statistics in simple is defined as

  • The collection of data,
  • organizing interpreting,
  • analyzing
  • presenting the data

 

Statistics in layman terms

  • it is used for comparison, calculating averages etc.
  • for the businessman; it is the tool to know the position of his business with reference to industry and competitors.
  • The wagon wheel of cricketer score,
  • A Weather report as examples of uses of statistics in everyday life.
  • sus or survey (which is termed as a primary source of data). The successful government projects depend on these data collected.

 

The statistical data can be collected through Two ways namely PRIMARY and SECONDARY.

 

Primary Data

Primary Source of data is collected directly or personally for a specific purpose. This is the most reliable data.

 

Secondary Data

Secondary data is a data which is used data or second-hand information. Once this data is collected it is to be organized in such a way that which can be easily interpreted.

Not all the data can be used instead sampling technique is used. Sampling is a process in which a set is taken from the population which acts as a representative of the data. This data is used for statistical purposes. The error which is because of the difference between central value and sample value can be classified as Type 1 error and Type 2 error. This classification depends on the acceptance or rejection of the null hypothesis. Some of the statistical tools are mean, correlation and regression, time series methods etc.

 If you want to become a good statistician, make sure that you have understood the basic terms and concepts thoroughly, basic formulas and its applications. Misuse of the statistical: some of them argue that it statistical data gives only mathematical figures but not the complete data regarding the problem and causes for it. Statistical data can be misrepresented, as the mathematical data can be taken differently by different people as there is no uniformity in it. It can be easily manipulated which bring a huge change in the conclusions, especially in the government bodies.

 

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Write-ups

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Mathematical statistics data analysis

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  • Confidence intervals and regression analysis
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