Introduction
To conduct data analysis using SPSS help and complete the research successfully, the researchers need to choose the right statistical method, in which the data can be represented and interpreted efficiently to conclude by meeting the research objectives. Selection of the appropriate statistical method mainly depends on the aim and objective of the study, the type and distribution of the data used and the nature of the observations.
Types of data & their techniques:
Hence, as per the data type, the researchers try to choose the method and statistical tool for further analysis and evaluation. In this regard, the mean is the arithmetic average for identifying the mean value and the median is the midpoint of the distribution. Mode is the most frequently occurring value and range is the difference between the highest and lowest value. Variance is highly utilised, which is the measure of spread, calculated as the mean of the squared differences of the observation from their mean. Standard deviation is the square root of the variance. As per the research aim and objective as well as the data type, the researchers try to choose the right method for conducting statistical analysis.
Types of data & effective techniques for analysing the data:
For analysing differences between the groups and variables, to analyse the multi-variant models, the researchers may choose the chi-square test, T-test, and ANOVA.
The above-mentioned tables are effective to identify the data type and the appreciate methods for conducting the statistical analysis. The SPSS experts are using SPSS data analysis widely for analysing the gathered data and information to develop the final report after critical evaluation. Apart from the study aim and objectives, there is a linkage between the type of the data and the existing statistical tool or further analysis, which will be represented further:
Hence, it is important for the researchers to identify the types of the gathered data and ensure quality data for analysing it to establish the final report. It is also essential for data analysts to access SPSS to get help with statistical analysis by using different methods. In the case of time series data, the researchers mainly focus on the graphical representation, which is charts, graphs and tables, so that the analysis can be developed as per the data representation through the graphs. The researchers use this method for forecasting analysis mostly and also to analyse particular variables over a specific period. On the other hand, descriptive statistics are also utilised for data analysis, which includes mean, median and mode, as well as standard deviation and variance.
In addition to this, correlation and regression are widely utilised techniques for analysing the impacts of the independent variables on the dependent variable in the data set. To test the alternative and null hypotheses in the research, the researchers mostly use this technique. Additionally, ANOVA is also used to consider multiple numbers of independent variables that have crucial impacts on the dependent variable. T-test or p-value analysis is also effective for analysing the significance of the data in the data set. Hence, the statistical analysis is effective for the researchers to perform well and interpret the data as per the statistical results.
Conclusion
Hence, the researchers must identify the research topic, its aim and objectives to analyse the data critically by choosing the right methods. SPSS is an integrated statistical software system, through which researchers can analyse a vast range of data. It would be beneficial for the data analysts to sort the data and handle it efficiently for identifying the type of data and aim to select the statistical analysis experts for further critical analysis.
