What is statistical data and statistical methods?

Statistical Data:

Statistical data science involves the collection, interpretation, and validation of data. It involves a variety of statistical operations performed with some statistical tools without having prior statistical knowledge. There are several software packages for performing statistical data analysis, including SAS (Statistical Analysis System), SPSS (Statistical Package for Social Sciences), etc.

There are Different Types of Statistical data :

1. Numerical Data: The data can serve as a measure, such as a person's height, weight, IQ, or blood pressure, or they can serve as a count, such as the number of shares a person owns, a dog's number of teeth, or the number of pages in a book you finish before falling asleep.

2.Categorical data : Categorical data are attributes that can take on numerical values (such as the numbers "1" and "2" indicating male and female, respectively).

3. Ordinary Data : In ordinal data, categorical data are mixed with numerical data. The data fall into categories, but the numbers placed on the categories have meaning. For example, rating a restaurant on a scale from 0 (lowest) to 4 (highest) stars provides ordinal data.

Statistical Methods:

It is a statistical method that extracts information from research data and provides ways to assess the robustness of research outputs with mathematical formulas, models, and techniques.

There are different types of Statistical Methods:

1. Descriptive Methods : A descriptive method involves every step in the analysis and interpretation process, such as the collection of data, the tabulation of data, the measurement of central tendency, the measurement of dispersion, as well as the analysis of time series. This method is also otherwise called descriptive statistics .

2 Analytical methods : This method comprises all those methods which help analyze and compare any two or more variables. These include correlation analysis, regression analysis, attribute association analysis, and the like. This method is also referred to as analytic analysis.

3. Inductive Methods :A generalization procedure consists of all procedures that lead to an estimation of a phenomenon using random observations or partial data, such as interpolation and extrapolation. This methods is also otherwise called inductive statistics.

4. Inferential Methods :In other Words, it is a method of drawing conclusions about the characteristics of a population based on samples of data. This method includes theories such as sampling theory, different tests of significance, statistical control, etc. This method is also otherwise called inferential statistics.

5. Applied Methods :These methods are used to solve real-life problems, such as statistical quality control, sampling surveys, linear programming, inventory control, and other procedures.

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