SPSS data analysis made easy. Become an expert in advanced statistical analysis with SPSS.
What you’ll learn
- perform simple operations with data: define variables, recode variables, create dummy variables, select and weight cases, split files
- built the most useful charts in SPSS: column charts, line charts, scatterplot charts, boxplot diagrams
- perform the basic data analysis procedures: Frequencies, Descriptives, Explore, Means, Crosstabs
- test the hypothesis of normality (with numeric and graphic methods)
- detect the outliers in a data series (with numeric and graphic methods)
- transform variables
- perform the main one-sample analyses: one-sample t test, binomial test, chi square for goodness of fit
- perform the tests of association: Pearson and Spearman correlation, partial correlation, chi square test for association, loglinear analysis
- execute the analyses for means comparison: t test, between-subjects ANOVA, repeated measures ANOVA, nonparametric tests (Mann-Whitney, Wilcoxon, Kruskal-Wallis etc.)
- perform the regression analysis (simple and multiple regression, sequential regression, logistic regression)
- compute and interpret various tyes of reliability indicators (Cronbach’s alpha, Cohen’s kappa, Kendall’s W)
- use the data reduction techniques (multidimensional scaling, principal component analysis, correspondence analysis)
- use the main grouping techniques (cluster analysis, discriminant analysis)
Requirements
- the SPSS package (version 18 or newer recommended)
- very basic knowledge of statistics (mean, standard deviation, confidence interval, significance level, things like that)
Description
Become an expert in statistical analysis with the most extended SPSS course at Udemy: 146 video lectures covering about 15 hours of video!
Within a very short time you will master all the essential skills of an SPSS data analyst, from the simplest operations with data to the advanced multivariate techniques like logistic regression, multidimensional scaling or principal component analysis.
The good news – you don’t need any previous experience with SPSS. If you know the very basic statistical concepts, that will do.
And you don’t need to be a mathematician or a statistician to take this course (neither am I). This course was especially conceived for people who are not professional mathematicians – all the statistical procedures are presented in a simple, straightforward manner, avoiding the technical jargon and the mathematical formulas as much as possible. The formulas are used only when it is absolutely necessary, and they are thoroughly explained.
Are you a student or a PhD candidate? An academic researcher looking to improve your statistical analysis skills? Are you dreaming to get a job in the statistical analysis field some day? Are you simply passionate about quantitative analysis? This course is for you, no doubt about it.
Very important: this is not just an SPSS tutorial. It does not only show you which menu to select or which button to click in order to run some procedure. This is a hands-on statistical analysis course in the proper sense of the word.
For each statistical procedure I provide the following pieces of information:
- a short, but comprehensive description (so you understand what that technique can do for you)
- how to perform the procedure in SPSS (live)
- how to interpret the main output, so you can check your hypotheses and find the answers you need for your research)
The course contains 56 guides, presenting 56 statistical procedures, from the simplest to the most advanced (many similar courses out there don’t go far beyond the basics).
The first guides are absolutely free, so you can dive into the course right now, at no risk. And don’t forget that you have 30 full days to evaluate it. If you are not happy, you get your money back.
So, what do you have to lose?
Who this course is for:
- students
- PhD candidates
- academic researchers
- business researchers
- University teachers
- anyone looking for a job in the statistical analysis field
- anyone who is passionate about quantitative research
