What is Statistics?

Statistics is a science that studies statistical methods. Statistical methods are scientific techniques that are used to plan and execute data collection, analysis, presentation and interpretation. Croxton and Cowden in their view, Statistics is a science of collection, presentation, analysis and interpretation of numerical data. Statistics should not be confused with a statistic. A statistic is a characteristic of a sample. It is used to estimate a value of population parameter.
Statistics as a subject is divided into:
1. Statistical methods
2. Applied statistics
Statistical methods are techniques and procedures by which numerical data are treated in order to gain insight from them. These methods as suggested by the definition of statistics are:
1. Data collection
2. Data organization
3. Data presentation
4. Data analysis
5. Data interpretation

Data Collection
Data collection is the process of obtaining data for the purposes of statistical investigation. It involves careful planning so as not to collect faulty data which may give unreliable results when analyzed. Faulty data may give misleading conclusions which sometimes may cause harm. Data may be obtained from primary or secondary sources. Primary sources of data are those that the researcher himself/herself goes to the field and collects the data which is otherwise known as primary data. Secondary sources involve data from published sources such as journals, periodicals, books, newspapers, government publications and research papers. We shall talk more about primary and secondary sources of data in the future discussions.

Data Organization
Data organization involves editing, classification, and tabulation. Once you have collected your data, you will realize that it contains inconsistencies, missing values, irrelevant responses and other little errors that were not intended. To ensure that your data gives you the information you need, you must clean the data. Data cleaning can easily be achieved by entering the data into a software like MS Excel, R, Stata, SAS, SPSS and many others. If you are not conversant with statistical softwares, you can at least use MS Excel. Then you can classify your data by grouping it into common characteristics. You may want to tabulate your data. This step is optional depending on what you want out of your data. Tabulation basically lets you arrange your data into rows and columns for clarity.

Data Presentation
Data, as raw as it is, makes little or no meaning to most people. So we need a way to make our data easily understandable. This can be achieved through use of graphs and diagrams. We shall talk more about graphs and diagrams in our later discussions.

Data Analysis
Data analysis is a way of trying to ask your data questions and expect answers. It is done with the help of statistical softwares. The choice of a statistical software depends on the organization you are working for and personal prevalence. 

Data interpretation
Gaining insights from the data is the sole purpose for all the statistical methods that we have considered from above. Data interpretation depends on the knowledge you have for the data and the statistical experience. Wrong interpretation of data may lead to wrong conclusions hence poor decision making. Valid conclusions may only be drawn b correctly interpreting the analysis results.

Applied Statistics
It is the application of statistical methods in specific areas. These areas include but not limited to Business, Economics, Accounting, Demography, Agriculture, Technology, Research, Medicine, Engineering, and so on.


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