Creswell_Research_Design_ Qualitative Quantitative and Mixed Methods Approaches 2018 5th Ed

Data Analysis
Tell the reader about the types of statistical analyses that will be implemented on the dataset.
Report the descriptive statistics. Some descriptive statistics that are commonly reported include
frequencies (e.g., how many male and female participants were in the study?), means and standard
deviations (e.g., what’s the mean age of the sample; what are the group means and corresponding
standard deviation values for the primary outcome measures?).
Indicate the inferential statistical tests used to examine the hypotheses in the study. For experimental
designs with categorical information (groups) on the independent variable and continuous information
on the dependent variable, researchers use t tests or univariate analysis of variance (ANOVA), analysis
of covariance (ANCOVA), or multivariate analysis of variance (MANOVA—multiple dependent
measures). (Several of these tests are mentioned in Table 8.3, which was presented earlier.) In factorial
designs where more than one independent variable is manipulated, you can test for main effects (of each
independent variable) and interactions between independent variables. Also, indicate the practical
significance by reporting effect sizes and confidence intervals.
For single-subject research designs, use line graphs for baseline and treatment observations for abscissa
(horizontal axis) units of time and the ordinate (vertical axis) target behavior. Researchers plot each data
point separately on the graph, and connect the data points with lines (e.g., see Neuman & McCormick,
1995). Occasionally, tests of statistical significance, such as t tests, are used to compare the pooled mean
of the baseline and the treatment phases, although such procedures may violate the assumption of
independent measures (Borg & Gall, 2006).
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