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 test will be a Person r test. Both test will have the seven hypotheses testing steps explained, descriptive discussion of the variables, possible errors and 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 difference between two variables (Salkind, 2013). Using the research question, a
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This test is selected as the research question is looking for the association between is NIofH Hypertension Category which is the independent variables and ordinal level of measurement and engagement in weekly moderate activity which is the dependent variable and is nominal level of measurement (Loiselle et al., 2011). There are two different samples and the researcher is interested in if there is an association between the two samples. A Chi-Square for independence test looks at the association between two samples that are both of a categorical level of measurement (Salkind, 2013). Lastly, the statistics assignment seven outline provided a cross tabulation SPSS output of frequencies and a Chi-Square test output. The SPSS output has four columns that consist of the independent variable NIofH Hypertension Category and two rows that consist of the dependent variable engagement in weekly moderate activity (Salkind, 2013). A Chi-Square test for independence contains two variables that are categorical, the independent variable in the column and the dependent variable in the row, within the cells are frequency of responses (Salkind, 2013). The goal of a Chi-Square for independence is to test if there is a relationship or association between two categorical variables (Salkind,
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At a level of significance of 0.05 the researcher is accepting a possible type I error 5 cases out of a 100 and 95 cases out of 100 a true null hypothesis (Loiselle et al., 2011).

Step 3: Selection of one-tailed or two-tailed test

The selection for a one-tailed or two-tailed test is not required for a Chi-Square for independence test (Salkind, 2013). Chi-Square test has both variables that are of a categorical level of measurement therefore, there is no direction (Salkind, 2013).

Step 4: Excel output of test statistic

The output for the Chi-Square for independence test is provided in the Statistic assignment seven outline and obtained from an SSPS output. Please refer to Statistics assignment seven to see the SPSS output for the Chi-Square tables.

Step 5: Degrees of freedom

The degrees of freedom (df) for a Chi-Square for independence is calculated as the number of rows subtracted by one multiplied by the number of columns subtracted by one (Salkind, 2013). From the SSPS output in assignment seven outline there are two rows and 4 columns. df = (Rows-1) (Coloums-1) df= (2-1)(4-1) df= (1)(3) df= 3

Therefore, the degree of freedom (df) is 3.

Step 6: Critical