Reference no: EM132218503

Q1:

Discussion questions must utilize one or more credible US based sources from within the past 5 years and be 2 paragraphs in length.

Q2: Compare Non-Parametric Tests

Describe and compare non-parametric tests with other commonly used distribution-based tests; and describe why such tests are critical. Use credible resources to support why the tests are critical.

Q3: Correlation and Causality

Discuss why correlations do not necessarily mean causality. Describe two variables that may be highly correlated, but do not indicate causality; and describe under what circumstances correlation leads to causality.

Q4: Linear Regression

Regression analysis is usually performed using quantitative data of both dependent and independent variables. Can it be done for categorical data? Using scholarly citations, differentiate regression analysis for quantitative vs. categorical data.

Q5: Generating Hypotheses

In statistics, usually hypotheses are created before the data is examined. However, in today's high data output environment, many findings may be examined further after the data is analyzed. Do you think that it is a good approach to generate such hypotheses after the data has been analyzed? Why or why not?

Q6: Analysis of Variance

Analysis of variance is a widely used methodology, across various disciplines, to test more than two means. Citing scholarly articles, describe why such methodology is so useful and what kind of data can be analyzed using such methodology.