Data Analysis & Research Design Evaluation 2

Important Instructions

1. Must read Submission Guidelines (with FAQs) BEFORE you start.
2. There is a Source Datafile in Assessment folder. You must obtain your randomly selected 333 cases from this data file. For how to do this, a short video & a written step by step guide are posted in assessment folder.
3. Zero mark will be awarded if you use source data file to run analysis. You must run analysis on your random selection of 333 cases.
4. You must provide SPSS output under every question (Copy & Paste) along with your report. No mark for any question if SPSS output or your report is missing. No SPSS output = No mark
5. You must use this template document to provide SPSS output under every question along with your report/written answer. We only need this file so submit this completed template ONLY in PDF or MS Word document (No zip folder, no Pages, no other additional files). Also do not dump all your SPSS output all together at the end. Marker is not going to search & sort the output if you have not provided it under every question.
6. You must run all tests as taught in the computer labs (No Googling for the instructions as googled instructions will not produce the output in the required format.)
7. Use of any Artificial 1ntelligence (AI) tools (as listed under AI & This Unit tab on Blackboard) is strictly prohibited, and zero will be awarded if you used AI for any answer.
8. Note on “Assumptions”: You will NOT check for any test assumption under any circumstances for any question. Reporting on any assumption is NOT required and does not carry any mark. If you do not know what an ‘assumption’ is, view the ilectures where each statistical test is explained.
9. You can choose a different selection of 333 cases for every assessment question or use the same selection for all questions; it is up to you.
10. Report Writing: For every question, please state the variable/s you have chosen, name of the test along with the purpose of the analysis, provide descriptive statistic/s, inferential statistic/s, decision on rejecting/retaining H0, statistical significance and conclusion. Refer to the respective ilectures and computing lab handouts and notes for guidance.

Questions

1 (4.5 marks) Choose suitable variable/s to run Mann-Whitney u test. Provide output and a report on your data analysis. 

2 (6 marks) Choose suitable variable/s to run Wilcoxon Signed Rank test. Provide output and a report on your data analysis. 

3 (4.5 marks) Choose suitable variable/s to run One-Way ANOVA. Provide output and a report on your data analysis including findings of post-hoc analysis if required. 

4 (3.5 marks) Choose suitable variable/s to run Pearson’s Chi squared test. Provide output and a report on your data analysis. 

5 (6.5 marks) Choose suitable variable/s to run Independent Samples t test. Provide output and a report on your data analysis. 

6 (6.5 marks) Choose suitable variable/s to run Paired Samples t test. Provide output and a report on your data analysis. 

7 (6 marks) Choose suitable variable/s to run Pearson’s Correlation analysis. Provide output and a report on your data analysis.  

8 (5.5 marks) Choose suitable variable/s to run Kruskal-Wallis ANOVA. Provide output and a report on your data analysis. 

9 (5.5 marks) Choose suitable variable/s to run Spearman’s Rho analysis. Provide output and a report on your data analysis. 

10 (1.5 marks) ‘Insight’ is a student feedback survey that is open towards the end of semester and allows students to provide feedback about their learning experience. Response rate/number of students who take part in this survey has been on decline and is currently around 15%. Each respondent was asked what they think could be one drawback or consequence due to this very low response rate. Five most insightful responses (pun intended) are coded as A, B, C, D & E (Variable: Problems due to Low Response). Replace each code/letter with a LABEL and then provide a suitable graph. No mark if you provide a suitable graph but no labels (meaning no mark if your graph is showing A, B, C, D & E. instead of showing five problems due to low response rate. No need to describe this graph.

Assessment Summary: Data Analysis and Research Design Evaluation

Assessment Overview

This assessment focused on applying quantitative research design and statistical analysis using SPSS software. Students were required to select a random sample of 333 cases from a provided dataset and conduct a series of statistical tests, each addressing specific types of research questions. The task aimed to evaluate students’ ability to perform correct statistical analyses, interpret SPSS outputs, and report findings professionally in a structured research format.

Key Assessment Requirements

1. Data Sampling

   • Obtain a random sample of 333 cases from the provided data file (not use the full dataset).

   • Follow the guide and video tutorial to extract data correctly.

   • Using the entire data file would result in zero marks.

2. SPSS Analysis and Reporting

   • Each question required a different statistical test to be conducted in SPSS.

   • Students had to paste SPSS output directly under each question, followed by a written report.

   • Reports needed to include:

     • Variables used

     • Purpose of the test

     • Descriptive and inferential statistics

     • Hypothesis testing outcome (reject or retain H₀)

     • Significance level and conclusion

3. Submission Rules

   • Use the provided template document only.

   • Submit one Word or PDF file, no ZIP or additional attachments.

   • Do not combine all SPSS outputs at the end; each must appear under its respective question.

   • No checking of test assumptions was required.

4. Statistical Tests to be Covered

   • Q1: Mann-Whitney U test

   • Q2: Wilcoxon Signed Rank test

   • Q3: One-Way ANOVA (+ post-hoc if required)

   • Q4: Pearson’s Chi-square test

   • Q5: Independent Samples t-test

   • Q6: Paired Samples t-test

   • Q7: Pearson’s Correlation

   • Q8: Kruskal-Wallis ANOVA

   • Q9: Spearman’s Rho correlation

   • Q10: Graphical representation of labeled survey data (no written explanation required)

5. Restrictions and Academic Integrity

   • No AI tools were allowed.

   • Only SPSS procedures demonstrated in lab sessions could be used.

   • Assumptions testing was explicitly excluded from the scope.

Academic Mentor’s Step-by-Step Guidance Process

The academic mentor guided the student through each phase methodically to ensure conceptual understanding and technical accuracy. The mentoring process was divided into three key stages: Preparation, Execution, and Reporting & Review.

Stage 1: Preparation and Planning

1. Understanding the Instructions
The mentor began by carefully reviewing the submission guidelines with the student. Emphasis was placed on:

• The correct use of random sampling (333 cases only)

• Avoiding direct use of the source dataset

• Maintaining SPSS output alignment with each question

The mentor clarified the importance of academic integrity, ensuring no AI-generated or externally sourced instructions were used.

2. Dataset Familiarisation
The student was shown how to import the dataset into SPSS and identify variable types (scale, ordinal, nominal) a critical step for selecting suitable statistical tests.

3. Random Sampling Procedure
Using the video and written guide, the mentor demonstrated how to generate a random sample of 333 cases using SPSS’s Select Cases function. This step ensured that the student’s analysis complied with the unique data requirement.

Stage 2: Execution of Statistical Analyses

For each question, the mentor adopted a structured approach — explaining the purpose, test selection, SPSS procedure, and interpretation.

Question 1: Mann-Whitney U Test

• Purpose: Compare two independent groups on an ordinal or non-normally distributed continuous variable.

• The mentor explained how to define the grouping variable and run the test through Analyze → Nonparametric Tests → Independent Samples.

• SPSS output interpretation covered U value, Asymp. Sig., and mean ranks.

Question 2: Wilcoxon Signed Rank Test

• Purpose: Compare two related samples (e.g., pre-test vs post-test).

• The mentor guided through Analyze → Nonparametric Tests → Related Samples.

• The interpretation focused on positive/negative ranks and the p-value to decide on H₀.

Question 3: One-Way ANOVA

• Purpose: Compare means across three or more independent groups.

• The mentor instructed how to check Analyze → Compare Means → One-Way ANOVA and how to run post-hoc tests (Tukey’s or Bonferroni) if significance was found.

• The student learned to report F-statistic, p-value, and between-group variance interpretation.

Question 4: Pearson’s Chi-Square Test

• Purpose: Examine the relationship between two categorical variables.

• Conducted through Analyze → Descriptive Statistics → Crosstabs → Chi-square.

• The mentor helped interpret expected counts, χ⊃2; value, and significance level.

Question 5: Independent Samples t-Test

• Purpose: Compare means of two independent groups for a continuous variable.

• Procedure: Analyze → Compare Means → Independent-Samples T Test.

• The mentor emphasized how to report t-value, degrees of freedom (df), and p-value, followed by the conclusion on H₀.

Question 6: Paired Samples t-Test

• Purpose: Compare means of two related measures.

• Steps shown via Analyze → Compare Means → Paired-Samples T Test.

• Interpretation included mean difference, t-statistic, and significance.

Question 7: Pearson’s Correlation

• Purpose: Determine the strength and direction of a linear relationship between two continuous variables.

• Analyze → Correlate → Bivariate.

• The mentor explained the meaning of r-value and p-value, and how to discuss positive or negative correlations.

Question 8: Kruskal-Wallis ANOVA

• Purpose: Compare medians of three or more independent groups when assumptions of ANOVA are violated.

• Run via Analyze → Nonparametric Tests → Independent Samples.

• Reported Chi-square statistic, df, and p-value.

Question 9: Spearman’s Rho Correlation

• Purpose: Measure the monotonic relationship between two ordinal variables.

• Analyze → Correlate → Bivariate (select Spearman).

• The mentor guided on interpreting Spearman’s rho coefficient (rs) and direction of relationship.

Question 10: Graphical Representation

• Purpose: Visualize coded responses (A–E) from the student survey.

• The mentor instructed replacing letter codes with descriptive labels (e.g., Low response reduces feedback accuracy).

• Created a suitable bar or pie chart under Graphs → Chart Builder.

• Reminder: No marks if labels were missing, regardless of chart quality.

Stage 3: Reporting, Review, and Submission

1. Report Writing Guidance
The mentor trained the student to write a concise yet complete report under each question. Each response included:

• Name of the test and its purpose

• Variables used and type of data

• Descriptive statistics (mean, median, or frequency)

• Inferential statistics (test statistic, p-value)

• Decision on H₀ (reject or retain)

• Conclusion in plain language

2. Integration of SPSS Outputs
The mentor ensured each output (tables, graphs) was correctly pasted below its respective answer. This formatting compliance was critical for full marks.

3. Final Quality Review
Before submission, the mentor reviewed the file to ensure:

• Correct test procedures

• No missing outputs

• No inclusion of assumption tests

• File saved in the correct format (Word/PDF only)

Outcome and Learning Achievements

Through this structured mentoring process, the student successfully:

1. Completed all ten statistical analyses correctly, adhering to the specified reporting format.

2. Developed practical SPSS skills for running nonparametric and parametric tests.

3. Enhanced understanding of when to use specific statistical tests based on variable types and research design.

4. Improved analytical reporting skills, interpreting statistical outputs into meaningful conclusions.

5. Complied with academic integrity standards, ensuring originality and ethical handling of data.

6. Achieved the learning objectives of the unit, including:

   • Designing and executing quantitative data analyses

   • Drawing valid conclusions from empirical data

   • Applying statistical reasoning to real-world research questions

   • Demonstrating professional reporting and documentation practices

Conclusion

This assessment bridged theoretical knowledge and practical analytical skills. Under the academic mentor’s guidance, the student gained confidence in executing SPSS-based analyses, interpreting results accurately, and presenting findings systematically. The final submission not only met the university’s technical and academic requirements but also reflected a solid understanding of research design, statistical reasoning, and evidence-based reporting, essential competencies for data-driven academic and professional success.

Get Expert Guidance with This Sample Solution

Looking for help understanding your Data Analysis & Research Design assessment? You can download this sample solution to see how professional academic writers approach each section, structure their analysis, and interpret SPSS results. It’s the perfect study companion to help you understand statistical concepts and reporting formats more effectively.

Important Note: This sample is strictly for reference and learning purposes only. Submitting it as your own work may result in plagiarism penalties or academic misconduct. Always use samples responsibly to enhance your understanding, not to replace original work.

If you need a 100% original, plagiarism-free, custom-written solution tailored to your specific dataset, topic, or assessment guidelines, our team of expert academic writers is ready to help. Get a professionally crafted report that meets your university standards and submission requirements.

Why Choose Our Custom Assignment Help?

• Written from scratch by qualified academic experts

• Fully compliant with your university’s marking criteria

• Plagiarism-free guarantee with full originality check

• Delivered on time with unlimited revision support

Take the next step towards academic success — learn from the sample, or get your own personalized solution today.

Download Sample Solution                   Order Fresh Assignment