Correlation Between Variables And Variables

2076 Words9 Pages
Statistics Assignment Seven This paper will use inferential statistics to test two different research questions. There will be two different types of statistical test that will be used. The first statistical test will be a Chi-Square for independence and the second statistical test will be a Pearson r test. Both tests will have the seven hypotheses testing steps explained, a descriptive discussion of the variables, possible errors, critique of research methods and implications for research and nursing practice will be provided. Research Scenario A: Question 1: Step 1 selection of test statistics Null hypothesis The null hypothesis is a statement that explains there is no relationship between two variables (Salkind, 2013). Using the…show more content…
The sample population within this research scenario consist of a total of 50 participants. Participants were male and female ages 22 to 91, which inclueded 22 male participants and 28 female participants. The participants were categorized and ranked according to the NIofH Hypertension Category. Therefore, the participants for NIofH Hypertension category 1 = optimal 160/=>100 included 7 participants. In addition, the categories for those who engage in weekly moderate activity consisted of 20 of the 50 participants and those who do not engage in weekly moderate activity consists of 30 of the 50 participants. Independent variable and level of measure The independent variable is the presumed cause which has an effect on the dependent variable (Loiselle et al., 2011). The presumed cause within the research scenario is NIofH Hypertension Category. The level of measure for the variable NIofH Hypertension Category is an ordinal level of measure. NIofH Hypertension Category is an ordinal level of measure because there are four categories which include NIofH Hypertension category 1 = optimal 160/=>100 (Loiselle et al., 2011). These four categories have ranking, however, there is no equal distance between the categories therefore, the variable is of a ordinal level of measure (Loiselle et al., 2011). Dependent variables and level of measure The dependent variable is the expected outcome which is
Open Document