This section examines hypothesis testing, and calculating and interpreting basic parametric and non-parametric tests. You will learn the difference between a null and alternative hypothesis, and how to set up the hypothesis (the specific symbolic components that are often used in testing hypotheses). You will explore the difference between one- and two-tailed testing, and also determine the importance of the P-value for setting up proper hypothesis testing. Type I and Type II errors should be understood in the context of hypothesis testing, and how increasing or decreasing the level of rejection can lead to greater levels of certain types of errors.
The second part of this section is an introduction to cross-tabulations, Chi-Square, t-tests, and One-Way ANOVA parametric and nonparametric measures. Importance is placed on calculating these tests through the use of statistical software, as well as analyzing and interpreting their results. In addition to manipulating computations, the conceptual basis of each test will be explored.
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- Submitted On 24 Jan, 2015 11:43:27