How to Perform Statistical Analyses for a Dissertation Data Using SPSS Software

SPSS stands for Statistical Package for the Social Sciences that reflects the original market of the social sciences but it is also very popular in many other fields that include the health sciences as well as marketing. Since it was first introduced, this software has come a long way and made its place truly and well among serious users. Now, SPSS is a widely used program for dissertations and statistical analysis in social science, market researchers, health researchers, survey companies, government, education researchers, marketing organizations, data mining and many other fields too.
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The best thing about this software is that it allows even the ordinary researchers to conduct their own statistical analysis most comfortably. In addition to this, data management like case selection, file reshaping, creating derived data and data documentation are key parts of the base software.

Some of the statistics included in the base software that help in performing statistical analysis  include:
·         Descriptive statistics: Cross tabulation, Frequencies, Descriptives, Explore, Descriptive Ratio Statistics
·         Bivariate statistics: Means, t-test, ANOVA, Correlation (bivariate, partial, distances), Nonparametric tests, Bayesian
·         Prediction for numerical outcomes: Linear regression
·         Prediction for identifying groups: Factor analysis, cluster analysis (two-step, K-means, hierarchical), Discriminant
·         Geo spatial analysis, simulation
·         R extension (GUI)

It would not be wrongto say that SPSS has gone a long way in simplifying statistical analysis and most of the users can now make use of the software without needing expert assistance. It can be used for descriptive statistics such as frequencies, measures of central tendency, and measures of dispersion while it can also be used for inferential statistics like correlation, regression, and analysis of variance. All this provides students and researchers a chance to use the data and analyze it most easily without any chance of making mistakes in the results.

It is necessary to know while performing analysis that descriptive statistics offer more information about the sample used in the research, while on the other hand, inferential statistics are used to make deductions or predictions about the general research population from which the sample was taken. Depending on the objectives, research questions, or hypotheses, the various tests like T-test, Chi-square test, Person correlation and Spearman rank-order correlation as well as others can be used to work out the data most effectively.

Before actually using this software, students and researchers need to know that this platform offers the most advanced statistical analysis, a vast library of machine learning algorithms, text analysis, open source extensibility, integration with big data and seamless deployment into applications. All this makes it very easy to use as well as flexible so that users at all levels can use it for their projects.

With this application, not it has become easy to users to turn data into actionable insights with predictive analytics. All they need to do is to learn which analytical capabilities will enable them to find the greatest value in your data and make confident, accurate business decisions. the better users learn to use the SPSS software, the better analysis they can obtain and the better results they can look forward to in the class. 
Albert Barkley

Hello, my name is Albert Barkley. I am working as education consultant with a UK based firm after completion of my PhD. I like to write on different social, tech and education trends.

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