Best Statistical Method To Consider For Conducting Research

Conducting Research
What is the best statistical method for research? The question is whose answer every student is looking for. Well, it depends on what you are doing. Running an experiment may be your best bet if you want the most accurate data about your target audience and their behavior. If you want to make predictions about future data, then the cross-sectional analysis may be best to determine the variables most suitable for your target outcomes. Once you have the data, you can apply linear or logistic regression to determine which variables are the most reliable predictors of your outcomes and interests. This article aims to discuss the best statistical method for research work.

Why The Use of Statistical Method Is Necessary for Research Work?

As a researcher, you must know that proper statistical method is important for interpreting data and presenting research results. Suppose, you plan to do statistical research in your study area. In that case, you must understand the importance of statistical methods that can be used in your research to get the best out of data. 

Researchers use statistical method to generate unique data for their research. It is very helpful in interpreting and analyzing accurate and fair deductions from research data. It can help you form an appropriate hypothesis that can be verified by conducting further experiments. 

It indicates whether one variable is related to another variable, whether observations follow a certain pattern, if there is any relationship between two variables or not, and many more such things. The statistical methods provide a tool to obtain valid results that can also be applied to further research.

Which Statistical Method Can Help You Well in Research Work?

So much research gets done every day, but it's easy to take the stress. Before making decisions based on this research, you must understand what it means and how it needs to be conducted. That's where statistical methods come in. Statistical method provides the framework you need for research and reach meaningful conclusions. Following are some effective statistical methods, which play vital role in research and make it reliable:

Mean of Data

The key to statistical analysis is understanding what a mean is and how we can calculate it. The mean, also known as an average, is one of the measures for describing a data set. To determine the mean, add up all your data values and divide by the total number of values.

For example, if you had four numbers—1, 2, 3, and 4—you would add those numbers together (1 + 2 + 3 + 4) and then divide that sum by four (4). The resulting number would be 2.5; that's your mean.

Median of Collected Data

Sometimes called the 50th percentile, a median is the midpoint of a set of data. Add up all your numbers and cut them in half to find them. If you have an odd number of items (like 9), one extra piece of data will be left over (4). In most cases, medians are used when dealing with skewed or otherwise lopsided datasets. It turns out that medians give more accurate depictions than averages do, and considered as one of the best statistical method for research.


Sometimes it can be difficult for researchers to determine which statistical method should be used to get best results from research. Using too many or inappropriate statistical methods can result in inaccurate results and further harm your credibility. The best statistical method will be one that does not require hundreds of tests and display low values. This limits of outer values and controls for multiple testing results in more valid conclusions about results.


The term range refers to two measures of variability in a data set: high-low and quartiles. The range, or distance between low and high, is found by adding up all your scores and subtracting them from one another. The range measures how to spread or disperse a set of data values. In this statistical method, you can use both numeric and categorical ranges. 

Standard Deviation

The standard deviation can be used as a descriptive statistical method that gives us an idea of how dispersed data is from its mean. If data is not scattered, then it has a low standard deviation. If data is very scattered, then it has a high standard deviation. Standard deviation does not tell us how spread out our data is; it only tells us if we have clustered or spread-out data.


The most straightforward statistical method is regression analysis, which helps establish a relationship between an independent and dependent variable. Regression is usually the best statistical method if looking for relationships between X and Y. This method can reveal which factors are most related to your outcome and where there may be non-linear relationships in your data.

Statistical Analysis Software SAS

SAS is a famous statistical analysis software that provides enhanced statistical analysis functions. It is not a free tool and is primarily used in research like human behavior, psychology, and business. You can create a graphical data representation using its easy-to-use GUI or create data scripts. In the premier SAS, you can also execute the enhanced features of SAS to produce graphs and pie charts.

Concluding Lines

Without appropriate statistical method, research is not worth anything. It is imperative to know how to conduct statistical analysis in research work because it not only aids you in collecting and analyzing data but also gives a clearer understanding of how variables relate to each other. The best methods are used to interpret research results. If you can select appropriate statistical methods, it will make a big difference in presenting research results in a way that makes them useful and accessible to other researchers.

Post a Comment

Previous Post Next Post

Contact Form