Team D Reflection
Jennifer Napier, Jean Gilmore, Ashley Stark, Stephanie Allison, Scott Counihan
QNT/351
February 2, 2015
Daniel Puente
Team D Reflection This week in class was spent focusing on a handful of different concepts. For example, we learned about the five steps which are required while testing a research hypothesis. We were introduced to the concept of comparing the means of two or more groups. Finally, we were taught how to calculate the correlation between two variables. Our understanding of these three topics is expressed below.
Hypothesis Testing
Hypothesis testing is commonly used when analyzing two or more groups. When assessing a theory, you need to report both the changeability in your sample and how sizable your sample is. Based on this knowledge, you would like to make a judgment of whether any characteristics you see are relevant or by chance. The process is properly done through an action called hypothesis testing. There are five steps in the process of testing:
1. Develop a theory – specify the assumption
2. Specify the Alternative Hypothesis
3. Select the sampling delivery and specify the test statistic
4. Figure out the test statistic and comparable P-Value
5. Prepare a determination and describe the results
Means of Groups
The function of comparing the means of two or more groups is used to determine the probability of an event given two distinctively but independent sample data sets with equal variances. The concept does tie into forming and ultimately testing a hypothesis when there are two sample sets of data to the mean and has value in that the value of the distance itself shows a corresponding value to the probability of occurrence. Comparing means between groups is an important method for curriculum evaluation by policy analysts and public administrators. In addition, it can be a useful tool in singling out discrimination and other social problems.
Correlation
The definition of the coefficient of correlation is that of a measure of strength of the linear relationship between two variables (Lind, 2011). In order to understand something like this we need to know the characteristics of the coefficient of correlations. Another definition is that it shows the direction and strength of the linear relationship between the two interval or ratio-scale variables. When we do calculate the
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