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University of Phoenix QNT 561 Applied Business Research and

Aug 3rd, 2014
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  1. University of Phoenix QNT 561 Applied Business Research and Statistics Study Guides and Answers
  2. www.paperscholar.com
  3. DIRECT LINK TO THIS STUDY GUIDE:
  4. http://www.paperscholar.com/university-phoenix-qnt-561-applied-business-research-statistics-study-guides-answers/
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  9. DESCRIPTION FOR THIS STUDY GUIDE:
  10. University of Phoenix
  11. QNT 561 Applied Business Research and
  12. Statistics Study Guides and Answers
  13. This course prepares students to apply statistics and probability concepts to business decisions. Students learn important criterion for developing effective research questions, including the creation of appropriate sampling populations and instruments. Other topics include descriptive statistics, probability concepts, confidence intervals, sampling designs, data collection, and data analysis – including parametric and nonparametric tests of hypothesis and regression analysis.
  14. Week One: Descriptive Statistics and Probability Distributions
  15. • Compute descriptive statistics for given data sets.
  16. • Apply probability concepts related to discrete and continuous probability.
  17. Week Two: Research and Sampling Designs
  18. • Formulate effective research questions.
  19. • Construct a research design appropriate to given research questions.
  20. • Apply the central limit theorem to sample means.
  21. • Construct confidence intervals for a mean.
  22. Week Three: Research Methods and Business Decisions
  23. • Apply concepts of probability to business decisions.
  24. Week Four: Data Collection
  25. • Determine appropriate measurement scales for a given research design.
  26. • Construct effective questionnaires and surveys.
  27. Week Five: Data Analysis
  28. • Conduct one- and two-sample tests of hypotheses.
  29. • Perform variance and chi-square analyses.
  30. Week Six: Correlation, Linear Regression, and Multiple Regression Analysis
  31. • Perform correlation, linear regression, and multiple regression analysis.
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