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    100% Discount || SPSS GUI Understanding and User Training

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    SPSS GUI Understanding and User Training

    Requirements

    • very basic knowledge of statistics (mean, standard deviation, confidence interval, significance level, things like that)
    • Access to SPSS software is recommended

    Description

    If you are an absolute beginner and don’t know anything about SPSS, this course is for you. After completing it, you will know how to create an SPSS data set, how to work with your data (select cases, split files, weigh data etc.), how to summarize and visualize your data with charts and tables, how to compute the statistical indicators for your data series, and also how to perform a couple of statistical tests (the ch-square test for association and the independent samples t test). In a word, you will have a solid idea about how SPSS works and what you can do with it. In this course, an introduction to the SPSS software program is provided. We’ll take a look at how to get started in SPSS, including creating variables and entering data. After that, we’ll cover creating value labels and entering some basic data. Modifying data files, including adding and sorting variables is then covered. After this, a number of descriptive statistics are covered, including bar graphs, stem and leaf plots, and measures of central tendency. Finally, the course concludes with hypothesis testing, with coverage of the Pearson r correlation coefficient.

    This SPSS data analysis course was created for one reason, which is to help anyone without statistics or mathematics background to analyze data in SPSS, choose the right descriptive statistics technique and write up the result of the findings with confidence. The course covers everything from entering data into SPSS to interpreting the result and offers easy step-by-step guide to mastering descriptive statistics in SPSS.

    Who this course is for:

    • Anyone interested in learning more about IBM SPSS, one of the most commonly used statistical software programs
    • students and graduate students in statistics and social sciences (psychology, sociology, marketing etc.)


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