Being a component of data analytics, Statistical Analysis includes the study of data processing from the collection of data to the interpretation of it. It interprets the patterns and trends of the quantitative data. This analysis is used for statistical modelling, interpreting the research, or for coming up with study and survey designs.
Statistical Analysis Services in the UK help the students pursuing their PhD research in subject domains including business, economics, and other statistical domains. For statistical analysis, it is important to specify the hypothesis (either null or alternative) of your research along with the accurate details regarding the sample size, procedure of sampling, and research design.
Mean is considered to be the simplest and quickest method of statistical analysis and is also called average. It can provide a concise perspective and help in determining the overall trend represented by the sample data collected.
However, there is a downside to this method of statistical analysis too. Although a mean can provide the central point of the sample data, it is not a standalone method of statistical analysis. Especially when it is a large data with significant differences.
Next is the standard deviation method of statistical analysis (SD). The SD is used for two reasons; that is, to check the data spread around the estimated mean and to check the data dispersion (whether or not for the clustered data).
The standard deviation helps in validating mean and data distribution. If the standard deviation is high. Then the data needs to be distributed or organized again; whereas, a low score of standard deviation implies otherwise.
Regression analysis for statistical data analyses the relationship between the dependent and independent variables used in the data sample collected. Also, the regression analysis helps in defining the causal relationship among these variables to see how one variable affects the other.
Along with it, correlation analysis (to measure the linear relationship and association between the variables) as well as the predictive analysis (to make assumptions about future relationship between the variables) are also conducted to test the strength of relationship between the independent and dependent variables.
Hypothesis testing or T-testing does the work which regression analysis can not: it tests the relationship between two sets of variables on a random basis. As it is clear by the name, it tests the hypothesis which means it tests whether a specific argument about the research can be supported by testing the variables.
Tests like ANOVA, chi square and t-test are used so that the data can be analysed and compared against various arguments or hypotheses set for the data. It helps in determining the chances of the argument being held or not.
SEM is used to analyze the structural relationships between various variables including independent, dependent,moderating, mediating, and so on which are used in creating the conceptual framework. SEM analysis can be conducted through using softwares like AMOS or SmartPLS. In these analysis tests, Bentler-Bonett Normed Fit Index (NFI) value is estimated to see whether the relationship constructed or predicted between the dependent and independent variables is a good fit or not. If the NFI value is closer to 1 then it is considered a good fit; whereas, NFI closer to 0 depicts otherwise.
When the research is based on a larger data size which is hard to be divided into different data sets to analyse it, many researchers prefer to determine a smaller data size. This is called sample size determination which is an important statistical data analysis method.
Based on the method of analysis, the data size needs to be decided. The sample size needs to be determined considering the budget, time, and research purpose so that an accurate data size can be determined without wasting the efforts and resources.
We have a team of statisticians who have provided successful statistical analysis services to over 37k scholars in the UK and 56k PhD candidates overall. Through all this experience and tasks, our experts can now understand your research requirements well with informed insight.
Our services are always on-time and no, we are not exaggerating it. As soon as you place the order request and make the payment, the task gets assigned to our expert who starts working on your project immediately. The timeline provided to you is based on the complexity of the analysis and thus, we do not give unnecessary excuses later.
Based on the data collection, estimation, organization, manipulation, and interpretation, our statisticians select the most suitable method of statistical analysis for your sample data. The step-by-step procedure is carried forward to keep the analysis detailed and to the point which makes it easily understandable.
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