Data Analysis: Planning and Preparing

Introduction

If a solid research topic is comparable to a story, then a roadmap is essential for excellent storytelling. Before requesting advice, we recommend that every student or researcher establishes his data analysis strategy. However, in this article, we will look at the structure of a data analysis plan. Alternatively, you can enroll in the Data Analysis Online Course

for a more advanced approach to planning and preparing data analysis content. This course will also walk you through the fundamentals and help you to become competent as a professional.

Data Analysis Plan: Meaning

The data analysis strategy or plan serves as a road map for organizing and analyzing the data obtained. It consists of the following elements:

1. Clearly states the study objectives and hypotheses.
2. Specifies the utilized dataset
3. The inclusion and exclusion criteria
4. Clearly states the research variables
5. States the Statistical test hypotheses and statistical analysis software.
6. Develop shell tables

Crucial Elements of Data Analysis Plan

The following are the crucial elements of the data analysis plan:

●  Specifies the study's Objectives and Hypotheses

You must explicitly state all study objectives. They must be specific, quantifiable, attainable, realistic, and time-bound. Moreover, hypotheses are the beliefs that derive from personal experience or prior literature and serve as the foundation for the statistical methodologies used to extend results to the population.

●  Use the Dataset

You must explain the usage of a dataset for statistical analysis and highlight its key features. These include the dataset's owner, how to gain access, how to examine it for quality control, and where the dataset is housed (Excel, Epi Info, SQL, Microsoft access, etc.).

●  Inclusion and exclusion criteria

These determine which dataset feature you may use for data analysis. These criteria will also guide the selection of variables for the initial analysis.

●  Research Variables

Every variable gathered in the study should be explained in a proper manner. However, they should present according to the measurement level, i.e., ordinal/nominal or ratio/interval levels or the role the variable performs in the research (independent/predictors or dependent/outcome variables). Moreover, there should be a proper specification of variable types. The variable type, in conjunction with the study hypothesis, serves as the foundation for selecting relevant statistical tests for inferential statistics. As a result, a solid data analysis strategy should include a summary of the variables.

●  Statistical Analysis Software

Several data analysis software packages are available, including SPSS, Epi Info, SAS, STATA, and Microsoft Excel. These packages include the release year, version number, and author/manufacturer. Beginners have a tendency to experiment with various applications and eventually fail to understand any of them. However, it is preferable to choose and master one because practically all statistical software performs similarly for fundamentals, and much-advanced analysis is a must-have for a student thesis.

●  Choosing a statistical method to attest hypotheses

Several statistical approaches can be employed to answer the research question correctly. However, this depends on the research topic, hypothesis, and kind of variable. This section of the data analysis strategy explains why you should use each statistical approach to test hypotheses. In addition, the statistical significance threshold (p-value), which is frequently but not always 0.05, should also be mentioned.

●  Developing shell tables

You can segregate data analysis into three levels of complexity; univariable, bivariable, and multivariable analysis. As a result, you should create shell tables in anticipation of the data acquired from these many levels of analysis.

Conclusion

Hopefully, you may find this article informative. We have compiled the elements that you can follow to prepare and plan for data analysis. This data analysis plan may help you with an excellent decision-making process. By looking at this structure, if you desire to have a career in this domain, we suggest you enroll for the extensive Data Analysis Training in Noida.