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“Research is to see what everybody else has seen, and to think what nobody else has thought.”
– Albert Szent-Gyorgyi (Nobel Prize Recipient)
Research is the quest for knowledge driven along with a passion for the empirical understanding of phenomena. The systematic understanding of the occurrences and scientific exploration of the facts falls under the category of research. It is a scientific study undertaken by the scholars for further knowledge on the myriad specialisations all around with a particular focus on the facts and scientific explanation of phenomena. While this explanation requires elucidation of facts and phenomena, all scientific methodology must follow the study of variables. The measurement of variables to scientifically determine the course and purpose of research requires the assignment of data or value to the variables so that they become standards of measurement to conduct the research. The variables and their measurement have the potential of changing the face of the entire research and thus need to handled and measured with caution, using the standardized scientific techniques.
Research is primarily divided into two categories based on the methods of data analysis – qualitative and quantitative research. Quantitative research used the scientific data analysis techniques for measuring the variables in research that have a numerical value attached to them, such as age or monthly income. These variables are measured using numbers and can be used for a quantitative research design. Quantitative research essentially deals with the explanation of phenomena all around us by the collection of numerical data and analysing those using scientific and mathematical (usually statistical) techniques.
Designing research in a way so that the variables can be measured quantitatively to explain their research purpose and yield better results is a technique that many researchers use. The social sciences, especially education and psychology, take generous help from the quantitative research design to measure the variables of research that seem non-numerical at first. But assigning a numerical value to the variables leads to effective data analysis techniques within the purview of quantitative research, and as explanations hold water when explained through numbers and specific values, it is best to take refuge of a quantitative research design for thorough explanation and analysis of results.
Statistical data analysis was earlier carried out manually using long and elaborate methods of calculation. Since the dawn of the digital age, several software and statistical analysis tools for computing and calculating large data sets have come to help in the quantitative research design. SPSS Amos is one such software for statistical data analysis, developed by IBM.
SPSS stands for Software Package for Social Sciences and was initially known as PASW or Predictive Analytics Software. It is essentially a software system that can be used through the menu system or command syntax. SPSS has two platforms, namely SPSS Statistics and SPSS Amos. The benefits of using SPSS for research are as follows.
IBM has developed SPSS Amos as an efficient structural equation modelling software that deftly handles all the statistical data analysis techniques for quantitative research. Standard multivariate analysis methods such as regression, correlation, and variance and factor analysis are made easier with the help of SPSS Amos. The graphical, as well as programmatic user interfaces of SPSS Amos, enables the researcher to create behavioural and attitudinal models that reflect complex relationships within data precisely as per the research requirements.
A standalone software, SPSS Amos is only available for the Windows operating systems all across the globe and can be used even if the SPSS Statistics is not installed on the computer. The file types usually associated with SPSS Amos end with the extension ‘.amw’ that is essentially the Amos model file that contains the model diagram. The official user license for SPSS Amos needs to be renewed annually, usually in the month of August. Despite being a very user-friendly software, one can learn a lot from the online SPSS Amos tutorials and videos for the beginners in the initial stages of using SPSS Amos in research.
SPSS Amos is primarily designed as a software system for analysing statistical data for structural equation modelling, covariance structure modelling and path analysis. It is a very apt tool for data analysis in quantitative research, especially for the disciplines like healthcare and medicine, social sciences, business planning and strategising, program evaluation, education, and psychology. It also provides options for improving the parameters and creating multiple data sets for analysis.
The usage of SPSS Amos in quantitative research is varied and plenty. Here is why it is so suitable for the data analysis sections of quantitative research and used widely among researchers all around the globe.
SPSS Amos effectively analyses the patterns of linear regression for the data analysis in quantitative research. It also entails analysis through ANOVA and ANCOVA for data analysis. What’s more, SPSS Amos is designed to read and interpret data from a number of sources including MS Excel and other SPSS databases.
The three user interfaces of SPSS Amos enables the researchers to create precise models with the datasets. Using these models, the researchers can then build apt behavioural and attitudinal patterns of data interpretation through the data that is provided to the system. SPSS Amos also allows the researchers to specify, access, deliver and estimate the models and provide several exploration methods to select the model most relevant to the dataset of the research.
The researchers adept in the programming languages as well as the novices can easily create the graphical and non-graphical models using the simple interface of SPSS Amos that has simple drag and drop down lists. Creating graphical and non-graphical models through SPSS Amos is thus devoid of hassles and does not require drawing an elaborate path diagram.
The structural equation modelling software allows the researcher to develop valid relationships between the models and thus find striking patterns relevant to his or her research. The automated path diagrams in SPSS Amos help the researcher uncover unlikely relationships between the variables and open newer perspectives of the analysis and interpretation of data in research.
The software also has the functions of estimation in case of missing data due to its advanced bootstrapping routine. Censored and categorical data is also put on estimation for analysis through SPSS Amos. The missing values can also be attributed to the variable scores, and the researchers can create one or multiple data sets by using the regression imputation methods offered by SPSS Amos.
A top-notch software for data analysis that handles multivariate factoring with ease, SPSS Amos is thus trusted by many academics all around the globe and has thus emerged as the leading software platform for structural equation modelling in quantitative research.
For knowing other functionality aspects of SPSS Amos, visit the link
Other data analysis and visualisation tools are
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