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Weekly tasks or assignments (Individual or Group Projects) will be due by Monday, and late submiss

 1000-1500 words  APA FORMAT 7TH EDITION PLEASE WATCH FOR OV SCORE

Weekly tasks or assignments (Individual or Group Projects) will be due by Monday, and late submissions will be assigned a late penalty in accordance with the late penalty policy found in the syllabus. NOTE: All submission posting times are based on midnight Central Time.

Key Assignment

Choose any available disclosed database for SPSS to develop a short research paper that utilizes the concepts presented in this course. Keep your paper simple, and use only one statistical test. To accomplish this, complete the following:

  • Write 1 paragraph that introduces your research question, data set, and scenario.
  • Create 1 quantitative research question and its associated hypotheses. Your research question should use inferential statistics.
  • Write a 1-paragraph explanation of the methods used to answer your research question. Your explanation should provide the type of test you are conducting, why this test is appropriate to answer your research question, and what assumptions you have made about your data set (e.g., parametric vs. non-parametric, normality, outliers, and so on).
  • Write 1 paragraph that provides your calculated descriptive statistics (e.g., measure of center, measure of spread) about your variable(s) and/or group(s).
  • Use SPSS to complete the analyses you described in the methods paragraph.
  • In multiple paragraphs, write the results from your analyses using proper APA formatting. Include all of the key tables and plots that are required to answer your research question. Properly label each graph and table, and reference each item within your text.
  • Write 1 paragraph to explain how your results answer your questions.
  • Include in your paper a title page, abstract, conclusion, and references.
  • Submit your Word document, data file, and SPSS output file. 

NOTE: You may not use the same combination of tests and data sets that were already submitted in this course. 

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