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University of Phoenix QNT 351 Quantitative Analysis For Business Study Guides and Answers PaperScholar Study Aids
Guide Last Updated: February 23, 2015
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University of Phoenix QNT 351 Quantitative Analysis For Business Study Guides and Answers

University of Phoenix QNT 351 Quantitative Analysis For Business Study Guides and Answers

 

University of Phoenix
QNT 351 Quantitative Analysis For Business Study Guides and Answers

This course integrates applied business research and descriptive statistics. Students will learn to apply business research and descriptive statistics in making better business decisions. Other topics include examination of the role of statistics in research, statistical terminology, the appropriate use of statistical techniques, and interpretation of statistical findings in business and research.

Understanding the Meaning of Statistics

Explain the role of statistics in business research and its application in business decision making.
Differentiate between qualitative and quantitative variables.
Differentiate among the four levels of measurement and how they are used in data collection for research.
Describing Data

Present qualitative and quantitative data in tables and charts.
Calculate central tendency and dispersion.
Describe the shape of data distribution in charts—box plot, stem and leaf plot, dot plot, and so on.
Probability Concepts and Continuous Probability

Explain discrete and continuous probability, rules of probability, and classical, empirical, and subjective approaches to probability.
Describe characteristics of standard normal distribution.
Calculate area between two data values and area above or below a certain value.
Hypothesis Testing

Apply the steps in testing a research hypothesis.
Compare the means of two or more groups.
Calculate the correlation between two variables.
Integrating Research and Statistics

Select an appropriate statistical test for analysis research data based on research questions and data type.
Interpret data analysis results to reach conclusions.
Make a recommendation about a problem based on data analysis results and conclusions drawn.