The branch of science known as statistics, examines the collection, organization, and analysis of data in the form of samples and generalizations about the whole population from the data. In research, a study must be designed properly and the study sample should be selected appropriately for positive role in outcomes. In addition, the statistical method should be chosen appropriately. For a clinical trial or an epidemiological study to be effective, adequate knowledge of statistics is required. When statistical methods are improper, erroneous conclusions may be drawn, leading to unethical practices.

Importance Role of Statistics in Scientific Research

A sound understanding of statistics allows you to collect the data properly, perform the appropriate analyses and present the results effectively. Statistics is a crucial process behind how we make discoveries in science, make decisions based on data and make predictions. We can gain an in-depth understanding of a subject through statistics.

Quantitative data can be collected, arranged, analyzed, and presented using appropriate statistical procedures. In statistical analysis, numerical data are analyzed to determine how best to interpret, understand, and use them. Therefore, statistics give us the ability to turn data into information, i.e., data that are interpreted, understood, and can be useful to the individual. Data can only be converted into information and quantitatively analyzed using statistics. In view of the fact that all research studies are characterized by data, a researcher must have an understanding of basic statistical concepts.

STATISTICS: DESCRIPTIVE AND INFERENTIAL STATISTICS

The two aspects of statistical analysis are descriptive statistics and inferential statistics. A sample from a population is not only collected and analyzed in inferential statistics but also conclusions are drawn about that population based on the analyzed data and estimated uncertainties about that population (i.e., using probability theory) are estimated based on inferential analysis. Quantitative data and methods for describing them are the subjects of descriptive statistics. By analyzing data gathered from samples (smaller subsets of the entire group), inferential statistics make inferences about populations (entire groups of people or firms) and use methods to support such conclusions. An inferential statistic is the analysis of whether the data are consistent with a hypothesis. It begins with a hypothesis (a statement or conjecture concerning the relationship between two variables you wish to study) and examines whether the data confirm the hypothesis.

In descriptive statistics, variables are described in relation to one another in a sample or population. In descriptive statistics, data are summarized in terms of mean, median, and mode. Inferential statistics are used to describe and make inferences about a population based on a random sample of data.

Statistics Draw Valid Conclusions Based on Numerical Evidence

Researchers often have a difficult time describing, explaining, or modelling complex data. We can apply statistics to solve this problem. You will be able to interpret and justify your research story coherently and adequately using appropriate statistical methods. The role of statistics is to fill the crucial gap between knowledge and information.

There is more to statistics than just numbers and facts; instead, it is an array of knowledge and procedures, which allow you to learn from data accurately. Statistical analysis helps you differentiate between reasonable and dubious claims based on quantitative evidence.

Statistical analysis involves several steps, including the creation of a study design, the selection and measurement of variables, deciding the sampling technique and sample size, and determining the analysis methodology. In order for results to be of good quality, the entire chain of events must be evaluated. There may be one weak link in the chain that causes unreliable results.

Listed below is a short sample of a few analytical errors and potential problems that can affect the study.

Biassed samples: The results of a study can be biassed from the beginning if the sample was selected incorrectly.

Violating the assumptions for an analysis: Assumptions are inherent to most statistical analyses. A sample, variable, data, and model are often subject to these assumptions. A violation of an important assumption can lead to misleading results.

It is equally essential that statistical practices never be manipulated or misused. To obtain a conclusion more worthy of attention or publication, it is unethical to misrepresent data, selectively report results, or search for patterns that can be presented as statistically significant. Although it may seem harmless, using statistics to “spin” results can prevent publication, undermine a published study, or lead to investigation and retraction.

In conducting a study, statistical methods are used for planning, designing, collecting, analyzing, drawing meaningful interpretations, and reporting the research paper writing findings. The results and inferences can only be made with precision if the appropriate statistical methods are applied.

Figure 1- Scientific Research and Development: The importance of statistics

  • Provides methods for collecting data
  • An analysis that supports or disproves a hypothesis
  • Analyzes data for uncertainties, errors, and outliers
  • Assist in interpreting and summarizing datasets

Statistics for Applied Purposes – Contains descriptive statistics and methods of inferential analysis.

Theoretical Statistics – Consists of logical arguments used to defend the rationale for statistical inference.

Mathematical Statistics – Include the methods of estimation, various aspects of computing statistics, and the design of experiments and the probability distributions.

Role of Statistics in Scientific Research

Statistical knowledge equips you with the tools and conceptual foundations for quantitative reasoning and derivation of information from data. Research findings and research methodology are frequently supported by statistical methods and analyses, which lend credibility to conclusions and methodology. For researchers and educators, statistics are crucial for accurately assessing the validity and usefulness of information, evaluating the credibility of sources, and making appropriate decisions.

In research, statistics play a crucial role. Statistics can be used in various ways, including data collection, analysis, interpretation, explanation, and presentation. Statistical analysis will aid researchers in describing, summarizing, presenting, and interpreting the findings of their research. Statistical analysis enables you to decide on various factors, such as how to design a study, whether to take a sample of the population or the entire population into consideration, the method to use for data collection and observation, and how to describe the data.