Results, Discussion, APA
Editing, and Defense
By Dr. James Lani
Introduction/Literature Review
Methodology
Results
Discussion
Results
Quantitative
Quantitative Results
Clean data!!! (thanks Dr. Bob Newman)
Descriptive statistics (e.g., frequencies, percentages,
means, and standard deviations)
Conduct analyses (e.g., examine assumptions, conduct
analyses 1-by-1, interpret analyses, create meaningful
tables and figures with descriptive labels and titles)
Summary (e.g., so readers have the highlights; clear
support or non-support for the hypotheses)
Clean Data
Conduct descriptives to see if they’re reasonable.
Get rid of outliers (i.e., univariate and multivariate).
Impute missing data (e.g., impute means, multiple
imputation).
Look at normality (and transform if necessary).
Descriptive Statistics
Describes who you have and the
average scores for the entire sample-
for generalizability purposes.
It’s a good double check for
consistent numbers of observations.
Descriptive Statistics
Frequencies and Percentages for Demographic Characteristics of Participants
Variable n %
Gender
Male
Female
Age
21-30
31-39
40-49
50 or over
Education
High school diploma or GED
Associate’s degree
Bachelor’s degree
Doctorate
XX
XXX
X
XX
XXX
XXX
XX
XX
XXX
XX
X
XX.X
XX.X
X.X
XX.X
XX.X
XX.X
XX.X
XX.X
XX.X
XX.X
X.X
Quantitative Results Write-Up Example
Null Hypothesis 1: There is no significant difference in the presence of organizational
change readiness factors associated with the successful outcomes of organizational
change initiatives between men and women.
To investigate null hypothesis 1, and to determine if there is a significant difference in
the presence of organizational change readiness factors associated with the successful
outcomes of organizational change initiatives between men and women, a between-
subjects analysis of variance (ANOVA) was conducted. Prior to analysis, the
assumptions of an ANOVA were assessed for all four dependent variables. Normality
was assessed with the examination of scatterplots and the assumption was met.
Homogeneity of variance was assessed with Levene’s test of equality of variance; the
result of the test was not significant, verifying the assumption of equality of variance.
The result of the ANOVA on Variable 2 was not statistically significant, F (X, XXX) =
0.09, p = .XXX, suggesting that statistical differences do not exist on Variable 2 by
gender (male vs. female). There was not a statistically significant difference in the
Variable 2 scores of males (M = X.XX, SD = X.XX) and females (M = X.XX, SD = X.XX).
The results of the ANOVA are summarized in Table 1.
Quantitative Results Write-Up Example
Table 1
ANOVA on Variable 1 by Gender (Male vs. Female)
Source SS MS F (X,XXX) P n2
Variable 1
Between X.XX X.XX X.XX .XXX .XX
Error X.XX X.XX
Qualitative
Qualitative Results
Line number documents.
Thematize narrative (provide 3+ representative
excerpts).
Kappa inter-rater reliability.
Grounded Theory: Open-Axial-Selective coding.
The results should make sense to a lay reader.
Qualitative ResultsMarker Mean Kappa (and Frequency) for Bill, Detert, and Reid Cases.
Bill Case Detert Cases Reid Case
(59 excerpts) (82 excerpts) (106 excerpts)
Marker (Themes) Kappa (Freq) Kappa (Freq) Kappa (Freq)
1. Body Symptoms .52 (1.14)** .46 (2.64)** .16 (4.00)
2. Downplaying Negativity .12 (1.07) .05 (0.93) .09 (3.00)
3. Avoiding Responsibility .20 (1.86) .04 (2.29) .03 (1.79)
4. Distancing Language .76 (3.00)*** .07 (2.29) .12 (3.64)
5……
20. Stepping Back .15 (2.43) .07 (3.86) .08 (5.43)
21. Putting Pieces Together .27 (2.86)* .15 (5.14) .25 (3.79)*
22. Almost, But Not Quite .12 (2.43) .05 (4.79) .03 (3.29)
23. Deciding to Act Diff. .07 (0.79) .32 (6.57)* .11 (2.64)
24. Noticing Change .62 (6.64)*** .32 (6.21)* .44 (8.36)**
25. Asserting Needs .04 (0.21) .25 (5.71)* .31 (7.36)*
26. Coming to Solution .07 (1.43) .11 (1.36) .03 (1.71)
Note. ****Almost perfect agreement, ***Substantial agreement, **Moderate agreement, *Fair
agreement, according to Landis & Koch (1977). Unless otherwise specified, each coefficient has
a slight level of agreement.
Inter-rater Reliability
Calculation of a Kappa Statistic for Theme 1 Between Rater 1 and Rater 2
Rater 1
Rater 2 Present Absent Subtotal
Present A B A+B
Absent C D C+D
Subtotal A+C B+D A+B+C+D
Observed Agreement = (A + D)
Expected Agreement = (((A + B) * (A + C)) + ((C + D) * (B + D))) / (A + B + C + D)
Kappa = ((observed agreement) – (expected agreement)) / ((A + B + C + D) – (expected agreement))
Note. A, B, C, and D are the frequencies in which a marker is identified in same excerpt between rater 1 and rate 2.
Results Summary
Give them the highlights of the findings.
Paint a picture of what was found.
Make it comprehensible.
Discussion
Discussion
Introduce the chapter.
Reiterate the results with clear support or non-support for the hypotheses.
Do the results fit into the existing literature or is this something new?
Implications of the results for both theory and practice.
Limitations of the study.
Recommendations for future research (what you would do if you had all of
the time, money, and energy in the world).
Conclusions—summarize the discussion chapter here.
APA Editing
APA Editing
Formatting: table of contents, tables and
figures, references.
Level of headings.
Should all be past tense.
References all cross-checked.
Retain an editor!
Dissertation
Defense
Dissertation Defense
Be prepared (just like comps, but easier).
Get all the committee’s questions out of the way
prior to the meeting (if possible).
Run through your PowerPoint with colleague/
partner and incorporate their feedback.
Relax!
Questions
&
Answers
1-1 Personalized
Dissertation Consulting
Info@StatisticsSolutions.com
877-437-8622
Reserve your spot
now!
Our calendar is filling up fast, so
reserve your spot on our schedule to
ensure your turnaround time.
877-437-8622
Info@StatisticsSolutions.com

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Results, Discussion, APA Editing, and Defense

  • 1. Results, Discussion, APA Editing, and Defense By Dr. James Lani
  • 5. Quantitative Results Clean data!!! (thanks Dr. Bob Newman) Descriptive statistics (e.g., frequencies, percentages, means, and standard deviations) Conduct analyses (e.g., examine assumptions, conduct analyses 1-by-1, interpret analyses, create meaningful tables and figures with descriptive labels and titles) Summary (e.g., so readers have the highlights; clear support or non-support for the hypotheses)
  • 6. Clean Data Conduct descriptives to see if they’re reasonable. Get rid of outliers (i.e., univariate and multivariate). Impute missing data (e.g., impute means, multiple imputation). Look at normality (and transform if necessary).
  • 7. Descriptive Statistics Describes who you have and the average scores for the entire sample- for generalizability purposes. It’s a good double check for consistent numbers of observations.
  • 8. Descriptive Statistics Frequencies and Percentages for Demographic Characteristics of Participants Variable n % Gender Male Female Age 21-30 31-39 40-49 50 or over Education High school diploma or GED Associate’s degree Bachelor’s degree Doctorate XX XXX X XX XXX XXX XX XX XXX XX X XX.X XX.X X.X XX.X XX.X XX.X XX.X XX.X XX.X XX.X X.X
  • 9. Quantitative Results Write-Up Example Null Hypothesis 1: There is no significant difference in the presence of organizational change readiness factors associated with the successful outcomes of organizational change initiatives between men and women. To investigate null hypothesis 1, and to determine if there is a significant difference in the presence of organizational change readiness factors associated with the successful outcomes of organizational change initiatives between men and women, a between- subjects analysis of variance (ANOVA) was conducted. Prior to analysis, the assumptions of an ANOVA were assessed for all four dependent variables. Normality was assessed with the examination of scatterplots and the assumption was met. Homogeneity of variance was assessed with Levene’s test of equality of variance; the result of the test was not significant, verifying the assumption of equality of variance. The result of the ANOVA on Variable 2 was not statistically significant, F (X, XXX) = 0.09, p = .XXX, suggesting that statistical differences do not exist on Variable 2 by gender (male vs. female). There was not a statistically significant difference in the Variable 2 scores of males (M = X.XX, SD = X.XX) and females (M = X.XX, SD = X.XX). The results of the ANOVA are summarized in Table 1.
  • 10. Quantitative Results Write-Up Example Table 1 ANOVA on Variable 1 by Gender (Male vs. Female) Source SS MS F (X,XXX) P n2 Variable 1 Between X.XX X.XX X.XX .XXX .XX Error X.XX X.XX
  • 12. Qualitative Results Line number documents. Thematize narrative (provide 3+ representative excerpts). Kappa inter-rater reliability. Grounded Theory: Open-Axial-Selective coding. The results should make sense to a lay reader.
  • 13. Qualitative ResultsMarker Mean Kappa (and Frequency) for Bill, Detert, and Reid Cases. Bill Case Detert Cases Reid Case (59 excerpts) (82 excerpts) (106 excerpts) Marker (Themes) Kappa (Freq) Kappa (Freq) Kappa (Freq) 1. Body Symptoms .52 (1.14)** .46 (2.64)** .16 (4.00) 2. Downplaying Negativity .12 (1.07) .05 (0.93) .09 (3.00) 3. Avoiding Responsibility .20 (1.86) .04 (2.29) .03 (1.79) 4. Distancing Language .76 (3.00)*** .07 (2.29) .12 (3.64) 5…… 20. Stepping Back .15 (2.43) .07 (3.86) .08 (5.43) 21. Putting Pieces Together .27 (2.86)* .15 (5.14) .25 (3.79)* 22. Almost, But Not Quite .12 (2.43) .05 (4.79) .03 (3.29) 23. Deciding to Act Diff. .07 (0.79) .32 (6.57)* .11 (2.64) 24. Noticing Change .62 (6.64)*** .32 (6.21)* .44 (8.36)** 25. Asserting Needs .04 (0.21) .25 (5.71)* .31 (7.36)* 26. Coming to Solution .07 (1.43) .11 (1.36) .03 (1.71) Note. ****Almost perfect agreement, ***Substantial agreement, **Moderate agreement, *Fair agreement, according to Landis & Koch (1977). Unless otherwise specified, each coefficient has a slight level of agreement.
  • 14. Inter-rater Reliability Calculation of a Kappa Statistic for Theme 1 Between Rater 1 and Rater 2 Rater 1 Rater 2 Present Absent Subtotal Present A B A+B Absent C D C+D Subtotal A+C B+D A+B+C+D Observed Agreement = (A + D) Expected Agreement = (((A + B) * (A + C)) + ((C + D) * (B + D))) / (A + B + C + D) Kappa = ((observed agreement) – (expected agreement)) / ((A + B + C + D) – (expected agreement)) Note. A, B, C, and D are the frequencies in which a marker is identified in same excerpt between rater 1 and rate 2.
  • 15. Results Summary Give them the highlights of the findings. Paint a picture of what was found. Make it comprehensible.
  • 17. Discussion Introduce the chapter. Reiterate the results with clear support or non-support for the hypotheses. Do the results fit into the existing literature or is this something new? Implications of the results for both theory and practice. Limitations of the study. Recommendations for future research (what you would do if you had all of the time, money, and energy in the world). Conclusions—summarize the discussion chapter here.
  • 19. APA Editing Formatting: table of contents, tables and figures, references. Level of headings. Should all be past tense. References all cross-checked. Retain an editor!
  • 21. Dissertation Defense Be prepared (just like comps, but easier). Get all the committee’s questions out of the way prior to the meeting (if possible). Run through your PowerPoint with colleague/ partner and incorporate their feedback. Relax!
  • 24. Reserve your spot now! Our calendar is filling up fast, so reserve your spot on our schedule to ensure your turnaround time. 877-437-8622 Info@StatisticsSolutions.com