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What do Mean by Statistics?

Statistics may be defined as one type of term which is commonly used by the analyst to analyse the given set of data. Suppose the data which is present is related to the samples of internet users, then what analyst do is that they interpret about the internet user based on the statistical data.
 

Types of Statistics

Descriptive Statistics
 

Descriptive statistics are generally used to define the general features of the data. They give common summary about the given sample & measures. Examples of descriptive statistics is patterns may came from data. There are four main type of descriptive statistics
 

Measure of central tendency: – In this we measure through median, mean and mode.
Measure of frequency: – In this we measure through percent, count, frequency etc
Measure of variation or dispersion: – In this we measure through variance, range, standard deviation e.t.c.
Measure of Position: – In this we measure through quartiles rank, percentile ranks etc
 

Estimators
 

In the field of statistics estimators is a defined parameter which provide a rule for calculation of an estimate of the given area based on data. They provide the estimate about a given data. Example of estimator is sample mean is an estimator for the internet users. In the given data when a quantity is being estimated is called an estimators. There are different methods for estimations out of that the commonly used estimation is are follow:- Bayes estimator, maximum likelihood, moments estimator, least square, maximum a posteriori (MAP), cramer-rao bound. Generally this are the properties of a good estimator: – sufficiency, efficiency, consistency, unbiased etc.
 

Test Statistics
 

Test statistics is used to know whether to reject or not the null hypothesis. Standardized test is being used to calculate the hypothesis testing. The commonly used of test statistics is to analyze the sample data. Example of test statistics for an X-test is the X-statistics. There are different types of test statistics and some of them are: – Anova test which is being used for group mean, Independent test which is being used in case of independent variables, Paired test which is being used in case of related variables.
 

Advantages and Disadvantages of statistical data

Advantages of Statistical Data
 

• As the data is taken from a large section so it cover all the general thing i.e high in generalizability.
• For checking of different variables it can be reused multiple times.
• Correlations and patterns are visible and clear.
• It is less expensive as it is not the prime data and also it take less time in compilation.
• High in reliability.
 

Dis-advantages of Statistical Data
 

• As the data is not the prime one, chances of misinterpretation is very high. And also it is not easy to access it and to check it.
• Validity of data is hard to check.
Statistical data can be easily manipulated which sometimes it effects its main objective.
 
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