How to Use the Statistical Tools for Data Analysis?

 Statistical Tools 

As the fields of statistics and data analysis are becoming more demanding all over the world, people are increasingly realizing the importance of excellent analysis and correct results. Statistical tools are the tools used by researchers to obtain correct results. 

In order to achieve correct data results, researchers must be able to obtain accurate data from survey results or other data collection methods. The researchers must understand the data they need to collect in order to enable researchers to determine which statistical tool should be used according to the outputs they want to obtain.

 Statistical tools for data analysis 

Statistics tools helps in getting the data before the process of data analysis from different sources, including:

1. Sources from the field: Researchers obtain it directly, and researchers collect information and investigate facts about a particular study itself, such as a questionnaire.
2. Official Sources: The competent institutions are responsible for collecting statistical data on the various types of phenomena, such as health, scientific, economic, etc.

Statistical tools for data analysis 

1. Observation: It is the direct or scientific observation of a phenomenon in the writing of research or study, in order to record all information about it, and interpretation, and knowledge of the laws that control it, and is considered one of the best methods of data collection and study.
   Observation has many advantages, including: it does not require much effort, depends on the conclusion, and make researchers to obtain behavior data at the time of the desired behavior. In addition, the observation allows researchers to collect the desired data from the behavior of individuals familiar with them.
   The other side is the disadvantages of observation, which is: the difficulty of predicting the spontaneous behavior of individuals at the same time, and the intention of individuals to highlight a behavior to put a good impression of the study of researchers, which lose credibility. In addition to obstructing the observation process, due to factors such as weather fluctuations, environmental control and nature in the work of researchers and hindered access to information quickly.
    
2. Interview: The interview is between two people, a sender and a receiver, who discuss and discuss, and there is a question and answer, in order to obtain the information and data to be obtained. The interview is one of the best ways of collecting personal data.
   The interview is characterized by a number of qualities and features, namely: it is of great use in the counseling, and high level of performance, and is useful in the treatment and diagnosis of problems, and give researchers sufficient and excessive information.
   The interview is highly effective in an illiterate society that does not read or write, and is an effective way to ascertain the validity of existing data sent in other ways. The drawbacks of the interview are that they are affected by the respondent's psychology and the interviewer, and that their success is estimated in the cooperation of the respondent, and may give the respondent inaccurate and false information.
    
3. Questionnaire: A set of questions that are formulated accurately and placed in a paper called a form or questionnaire. They are given to the respondent and should answer the questions. It is a tool to get the desired data about a phenomenon. Types of questionnaire are: open-ended questionnaire, closed-question questionnaire, and mixed questionnaire, the questionnaire is one of the most prevalent methods of data collection.

 What is analysis of data? 

Analysis of data is defined as the process of evaluating data using analytical and logical thinking to study each component of research data. Analysis of data is just one of several steps that must be completed when performing a search experiment. Data are collected from different sources, reviewed, and then analyzed to form some kind of research or conclusion.

 Analyzing data steps 

There are several steps for analyzing data:

• The first step for analyzing data is defining research objectives because failure to set goals leads to loss of individual time.
• The second step for analyzing data is entering data into your computer; this involves setting up statistical analysis files.
• The third step for analyzing data is the descriptive analysis is an exploratory analysis to identify any unexpected patterns or results, including the calculation of summary tables and graphs as defined when setting goals.
• The fourth step for analyzing data is the accurate measurements such as standard errors are added to the descriptive analysis.
• The fifth step for analyzing data is the results of the current study that are compared with previous studies, and new hypotheses can then be formulated.
• The sixth step for analyzing data is providing the final tables, charts, and analysis methods used. In addition, the methods of analysis should be documented in the research. This is because the reader knows the method that has been followed. This step for analyzing data also provides an opportunity for another researcher in the future to use the same method in a similar research.

 Watch: Use of Statistical Tools 

With greetings: Al - Manara Consulting to help researchers and graduate students