STA10003: Foundations of Statistics Work Integrated Learning Assignment Part 2

Assignment Part 2

The Industry Scenario

You are a new graduate researcher at the Department of Health Victoria. You have been given a dataset of Geelong Mental Health Service clients to analyse. These clients attended an intervention program designed to improve the participant’s anxiety coping strategies. Extent of anxiety coping was recorded at the beginning and end of the intervention program, with external self-perception and internal self-perception also recorded at the end of the intervention program. Demographic data was also collected for each client, regarding their gender and birth order. You have been tasked with conducting the initial analysis of some variables using SPSS and to write brief reports.

For Assignment Part 2 you are required to complete the first three questions by producing the appropriate analyses using SPSS and writing the relevant report for each question. Reports are to follow the style used in the examples in the learning materials. You are also required to complete question 4, which contains short answer questions.

For each of the first three questions requiring SPSS, you should include the relevant output immediately following your report.

Questions

1. Internal Self-Perception

A researcher at the Department of Health Victoria was investigating internal self-perception. Previous research indicated that for Europeans the average internal self-perception score was 6.3. The researcher predicted that there is a difference in internal self-perception between Australians and Europeans. The variable SP_internal measures internal self-perception. This variable was scored on a scale from 0 to 20, with higher scores representing greater levels of internal selfperception. Conduct a one sample t-test using the SP_internal variable to test the researcher’s prediction. Produce the relevant SPSS output and write a one-sample t-test report based on your SPSS output in the style presented in the course materials. Examples of reports can also be found in Reading G: Report writing for One-sample t-test & Binomial Test. Include the relevant SPSS output with your answer.

2a: External Self-Perception

A researcher at the Department of Health Victoria was investigating external self-perception. The researcher predicted that males have a lower level of external self-perception than females. The variable SP_external measures external self-perception. This variable was scored on a scale from 0 to 20, with higher scores representing greater levels of external self-perception. Conduct an independent samples t-test using the SP_external and Gender variables to test the researcher’s claim. Produce the relevant SPSS output and write an independent samples t-test report based on your SPSS output in the style presented in the course materials. Examples of reports can also be found in Reading H: Reporting independent samples t-tests. Include the relevant SPSS output with your answer.

2b: Assumption Checking for the independent samples t-test

Check and comment on all the assumptions of the independent samples t-test produced in Q2a and make a recommendation about the independent samples t-test. Include the relevant SPSS output with your answer.

3a: Anxiety Coping

A researcher at the Department of Health Victoria was investigating the outcome of an intervention program designed to improve the participant’s anxiety coping strategies. The researcher hypothesized that participants in the intervention program would have better anxiety coping after completing the intervention program. The variable AnxCope1 is a measure of each client’s anxiety coping at the beginning of the intervention program. The variable AnxCope2 is a measure of each client’s anxiety coping at the end of the intervention program. Both variables were scored on a scale from 0 to 20 with higher scores representing a greater use of anxiety coping strategies. Produce the relevant SPSS output and write a paired samples t-test report based on your SPSS output in the style presented in the course materials. Examples of reports can also be found in Reading J: Reporting paired samples t-tests. Include the relevant SPSS output with your answer.

3b: Assumption Checking for the paired samples t-test

Check and comment on all the assumptions of the paired samples t-test produced in Q3a and make a recommendation about the paired samples t-test. Include all relevant output with your answer.

4: Does not require SPSS

A human resources manager at a market research company found that staff, on average, responded to 24 phone calls per day. A manager at one of the company’s call centers wants to know if the number of phone calls per day that their staff respond to is different to 24 phone calls per day. The call center manager asks a random sample of staff at their call center to record how many phone calls they take each day.

(a) What type of statistical test should the call center manager use to investigate the hypothesis?

(b) Explain why this statistical test would be appropriate?

(c) If a Type I Error occurred what specific conclusion would the call center manager make?

(d) The call center branch manager conducted the appropriate statistical test and obtained a p value of 0.052. Based on this result the call center branch manager concluded that there is no evidence to suggest that the number of phone calls per day that their staff respond to is not different to 24 phone calls per day. Is this conclusion valid or not valid? Explain why this conclusion is valid or not valid.

Brief Summary of Assessment Requirements

The STA10003: Foundations of Statistics – Assignment Part 2 focuses on developing students’ ability to apply statistical techniques using SPSS software and interpret outputs in a professional reporting format. The context revolves around a dataset of Geelong Mental Health Service clients, collected to assess the effectiveness of an intervention program aimed at improving anxiety coping strategies.

Students were required to:

• Conduct statistical analyses (one-sample t-test, independent samples t-test, and paired samples t-test) based on given research hypotheses.
• Check statistical assumptions for each test and provide valid recommendations.
• Write detailed, professional-style reports following examples provided in course materials.
• Answer short theoretical questions (Q4) related to hypothesis testing concepts, such as test selection, Type I error, and interpretation of p-values.

The assessment’s key learning objectives included:

• Applying statistical methods for data-driven decision-making.
• Interpreting SPSS outputs accurately.
• Demonstrating critical understanding of statistical assumptions.
• Developing clear and concise reporting skills following academic standards.

Step-by-Step Guidance by the Academic Mentor

The Academic Mentor guided the student systematically through each part of the assessment, ensuring both technical and analytical understanding:

Step 1: Understanding the Research Context and Data Variables

The mentor first helped the student understand the dataset explaining variables such as SP_internal, SP_external, Gender, AnxCope1, and AnxCope2. This stage ensured the student recognized which statistical tests aligned with each research hypothesis.

Step 2: Conducting the One-Sample t-Test (Question 1)

• The mentor demonstrated how to perform a one-sample t-test in SPSS to compare the mean internal self-perception score of Australians with the population mean of 6.3.
• Emphasis was placed on verifying assumptions such as normality using descriptive plots.
• The mentor then guided the student in writing a structured statistical report, covering the hypothesis, t-value, degrees of freedom, significance level, and interpretation of results in APA style.

Step 3: Performing the Independent Samples t-Test (Question 2a & 2b)

• The mentor explained how to set Gender as the grouping variable and SP_external as the test variable in SPSS.
• The process included checking assumptions such as equality of variances using Levene’s test.
• The student learned to interpret whether males had significantly lower external self-perception than females.
• For assumption checking, the mentor emphasized documenting normality and homogeneity tests and making an evidence-based recommendation regarding the test validity.

Step 4: Conducting the Paired Samples t-Test (Question 3a & 3b)

• The mentor assisted in comparing AnxCope1 (pre-intervention) and AnxCope2 (post-intervention) scores to determine whether the intervention improved anxiety coping.
• The paired samples t-test procedure was demonstrated in SPSS, followed by guidance on interpreting the mean difference, t-statistic, and significance value.
• For assumption checking, the mentor helped the student examine normality of difference scores and determine whether parametric testing was appropriate.

Step 5: Addressing Theoretical Questions (Question 4)

• The mentor explained the logic behind test selection highlighting why a one-sample t-test is suitable when comparing a sample mean to a known population mean.
• Concepts of Type I Error and p-value interpretation were clarified to strengthen the student’s understanding of statistical decision-making.
• The mentor guided the student in articulating whether the manager’s conclusion in Q4(d) was statistically valid, emphasizing the boundary condition (p = 0.052).

Final Outcome and Learning Achievements

Through mentor guidance, the student successfully:

• Conducted all required SPSS analyses accurately and presented outputs clearly.
• Produced professional-style reports aligned with academic standards and APA reporting guidelines.
• Demonstrated a strong grasp of statistical testing assumptions, hypothesis evaluation, and result interpretation.
• Developed analytical reasoning and practical SPSS proficiency essential for real-world data analysis in health and social science research.

Learning Objectives Covered:

• CLO1: Application of descriptive and inferential statistical methods.
• CLO2: Proficiency in using SPSS for statistical analysis.
• CLO3: Development of critical thinking and professional reporting skills.
• CLO4: Understanding of data interpretation for evidence-based decision-making.

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