Introduction - (Minimum two to four paragraphs or approximately one page) (1) Offers narrative synopsis of (a) demographics and (b) characteristics of study's population or sample. (2) Defines number of participants; (a) Gender, (b) Age, and Level (if applicable); (c) Structure or environment (if applicable); and (d) array of visual organizers, tables, charts, and graphs.

Narrative summary of the population or sample characteristics and demographics-(1) Narrative synopsis of data gathered. (2) Arranges and presents descriptive and coded data using visual graphic organizers (tables, histograms, graphs, and/or bar charts).

Quantitative: (1) Descriptive or graphical comparisons of study-relevant groupings and frequencies at the sample level. (2) Tests of assumptions to assess sample distribution (skewness and kurtosis data and charts), normality, and homogeneity of variance if the planned analysis includes parametric techniques. (3) Justification given if nonparametric techniques are employed.

Qualitative: (1) Number of interviews, (2) How long they were. (3) How many pages in the transcript. (4) How many observations made. (5) How long they were. (6) How many pages of field notes. (7) How many times a code, network diagram, model appeared in transcript. (8) How many observations were made. (9) How long they were. (10) How many pages of field notes were typed up. (11) Arranges and presents descriptive and coded data using visual graphic organizers. (12) Descriptive or graphical comparisons of study-relevant groupings and frequencies at the sample level.

Data Analysis Procedures-(number of pages as needed) (1) Presents description of process used to analyze the data.

Quantitative- (1) Data analysis procedures framed relative to each H. (2) Provides validity/reliability of data in statistical terms, (3) Describe power analysis & test(s) of assumptions for statistical tests. (3) Justifies how analysis aligns with t hypothesis(es), (4) Is appropriate for the design, (7) Discuss the limitations this places on the results. (5) Justifies how analysis aligns with H.

Qualitative-(1) Justifies how analysis aligns with RQ(s). (2) Includes description of coding process. (3) How codes related to themes. (4) examples of codes & themes with corresponding quotations. (5) How codes developed into themes. (6) Provides evidence of initial codes and themes in an Appendix. (7) Explains/ justifies differences why data analysis section does not match what was approved in C3 (if appropriate). (8) Describes approaches to ensure validity/reliability including (a) expert panel review of questions, (b) practice interviews, (c) member checking, and (d) triangulation of data. (9) Identifies sources of error, missing data, or outliers and potential effects on the data.

Results (number of pages as needed)

Quantitative. (1) Presents analysis of data (a) non-evaluative, (b) unbiased, (c) organized manner to H. (2) List RQ(s) in order. (3) Answer H(s) in the order listed. (4) Data & the analysis presented in a narrative, non-evaluative, unbiased, organized manner by H(s). (5) Results of each statistical test presented in appropriate statistical format with tables, graphs, and charts. (6) Includes appropriate graphic organizers such as tables, charts, graphs, and figures. (7) Findings presented by hypothesis using section titles. (8) Presented in order of significance. (9) Sufficient quantity/ quality of the data/information appropriate the research design presented in analyses to answer H. (10) Inferential statistics, tests of normality, tests of assumptions, test statistics and p-value reported for each H. (11) Control variables reported & discussed. (12) Secondary data treatment of missing values described. (13) Results of analysis presented in appropriate narrative, tabular, graphical and/or visual format. (14) Outlier responses explained as appropriate. (14) If using thematic analysis, coding & theming process completely described. (15) Sufficient quantity/ quality of the data/information appropriate the research design presented in analyses to answer the RQ(s). (16) Quotes substantiate stated findings and narrative picture required. (17) Data analysis includes narrative story for (a) narrative analysis. (b) Case study summary for case study. (c) Model or theory for grounded theory.

Qualatative: (1) Fully described/displayed using techniques specific to the design & analytic method used. (2) Data sets summarized including counts & examples of participant’s responses for thematic analysis. (Other approaches may be summarized in matrices or visual formats appropriate to the form of analysis). (3) Outlier responses explained. (4) Findings may be thematic analysis presented as themes using section titles: Narrative: stories as models or theories (5) Grounded theory, and as visual models or narrative stories for case studies. (13) Results of analysis presented in appropriate narrative, tabular, graphical and/or visual format. (14) If using thematic analysis, coding & theming process completely described. (15) Sufficient quantity/ quality of the data/information appropriate the research design presented in analyses to answer the RQ(s). (16) Quotes substantiate stated findings and narrative picture required. (17) Data analysis includes narrative story for (a) narrative analysis. (b) Case study summary for case study. (c) Model or theory for grounded theory.

Summary (Minimum one to two pages) (1) Presents a clear & logical summary of data (2) Separates the factual information from interpretation.

Quantitative: (1) Summarizes statistical data and results of statistical tests in relation to the research questions/hypotheses.

Qualitative: (1) Summarizes data & data analysis in relation to the RQ(s). (2) Summarizes data across RQ(s) for case studies, narratives, and grounded theory. (3) Discusses limitations how interpretation of results may be effected by the limitations. (4) Provides concluding section and transition to C5.

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Chapter 4: Data Analysis