This course will help you understand how excel can be used in statistical analysis. Although you may use statistical software in data analysis, gaining more understanding on excel in statistical analysis will help you working with statistical software.

E-views is one of the powerful statistical software. It is a modern econometric, statistics, and forecasting package that offers powerful analytical tools within a flexible, easy-to-use interface. Using EViews, you can quickly and efficiently manage your data, perform econometric and statistical analysis, generate forecasts, or model simulations, and produce high quality graphs and tables for publication or inclusion in other applications.

Stata is one of the powerful statistical software and commonly used by many researchers. Stata is a general-purpose statistical software package for data manipulation, visualization, statistics, and automated reporting. It is a complete, integrated software package that provides all your data science needs—data manipulation, visualization, statistics, and automated reporting.

SAS is one of the powerful statistical software. It is used for data management, advanced analytics, multivariate analysis, business intelligence, criminal investigation, and predictive analytics. With this software, you can access data in almost any format, including SAS tables, Microsoft Excel tables, and database files, manage and manipulate your existing data to get the data that you need, such as subset your data, combine it with other data, and create new columns.

AMOS is statistical software, and it stands for ‘Analysis of a Moment Structures’. It is also known as ‘Analysis of covariance or causal Modelling Software’. AMOS is an added SPSS module, and is specially used for Structural Equation Modelling, path analysis, and confirmatory factor analysis.

Mplus is a statistical modelling program that provides researchers with a flexible tool to analyse their data. Mplus offers researchers a wide choice of models, estimators, and algorithms in a program that has an easy-to-use interface and graphical displays of data and analysis results. Mplus allows the analysis of both cross-sectional and longitudinal data, single-level and multilevel data, data that come from different populations with either observed or unobserved heterogeneity, and data that contain missing values. Analyses can be carried out for observed variables that are continuous, censored, binary, ordered categorical (ordinal), unordered categorical (nominal), counts, or combinations of these variable types. In addition, Mplus has extensive capabilities for Monte Carlo simulation studies, where data can be generated and analysed according to any of the models included in the program.

‘Mixed methods’ ‘multimethodology’ or ‘multimethod’ research is a research approach whereby researchers use more than one method by mixing both the qualitative and quantitative data, methods, methodologies, and/or paradigms in a research study or set of related studies.