This course is intended to deliver a working knowledge with SPSS. Students are not expected to have previous programming or “highly” statistical analysis skills. But, a basic understanding of statistical functions is necessary. The emphasis in this course will be upon understanding statistical concepts and applying and interpreting tests of statistical inference. Content will include but not be limited to: data and data files, data screening, scaling, visual representations of data, descriptive statistics, correlation and simple regression, sampling distributions, and the assumptions associated with and the application of selected inferential statistical procedures, which includes: T-tests, chi-square, and one-way ANOVA. This course will not cover advanced statistical methods, but will provide student with a firm foundation to address these areas in his/her dissertation research. A working knowledge of SPSS statistical software is a vital skill for anyone involved in quantitative research. Students will develop the fundamental skills needed to prepare data sets for analysis, and to conduct simple descriptive and graphic analyses and report those analyses. Computer software (SPSS) will be employed to assist in the analysis of data for this course.