Data Analysis & Research Design Evaluation 1

Questions

1. A research question is something a research study aims to answer by collecting relevant data following scientific research process. This question is designed to assess your understanding of this scientific research process, how it is used to plan and conduct a research study to answer a specific research question (as explained in the relevant ilecture). Your research question should be about Physical Activity and First Year Curtin Students. You will then plan a hypothetical study to answer it and you are going to do this by providing answers to the questions.

a) What is your Research Question?

b) What is the aim of your proposed study? What benefits it will have?

c) Name a suitable study design & tell us how it is suitable for your research question?

d) What will be the inclusion criteria for your study participants?

e) Which sampling method you will choose? and why?

f) How will you recruit participants?

g) What are your independent and dependent variables?

h) What are three other factors/variables you will collect information about and why?

i) Provide measurement scale & units/categories for each variable you described in the part above?

2. Choose a variable from the data file you have created for this assessment (yes, it is your choice of a suitable variable) and carry out all the checks to assess if it shows roughly normal distribution in the population, represented by the provided sample. Provide a brief description for each check under the relevant SPSS output. At the end provide an overall conclusion. (Useful tip; lab 3 is a good guide but explanations are in the relevant ilecture). Both output and Description are required, 0 mark if any of the two are missing.

3. From the data file you had to create for this assessment choose two variables that are suitable for investigating the Bivariate Association. Perform the suitable analysis and provide a short report. No need to test or report on any assumptions. Both output and brief report are required, 0 mark if any of the two are missing.

4. From the data file you had to create for this assessment:

a) Provide a suitable descriptive statistic and a graph for a continuous variable. Provide a description of your graph (2-4 lines) (2 marks)

b) Provide a suitable descriptive statistic and a graph for a categorical variable. Provide a description of your graph (2-4 lines) (2 marks)

c) Choose suitable data to provide a scatterplot. Provide a description of your scatterplot (2-4 lines) (2 marks)

d) Choose suitable data to provide a cross tabulation. Provide a description of your cross tabulation (2-4 lines). (2 marks).

e) Choose a categorical variable and perform recoding to create a binary variable. Provide a frequency table showing labels, values and frequencies of your new binary variable (1 mark).

f) Choose a continuous variable and perform recoding to create a binary variable. Provide a frequency table showing labels, values and frequencies of your new binary variable (1 mark).

5. From the datafile you had to create for this assessment choose two variables that are suitable for investigating a possible bivariate Correlation. Perform the suitable analysis and provide a short report. No need to test or report on any assumption. Both output and brief report are required, 0 mark if any of the two are missing.

Please note there is no ‘Mode’ in the table below. Use ‘Frequencies’ to obtain mode.

1. Mean, Median & Mode: For a normal and symmetric all three should be equal or similar.

2. Skewness & Kurtosis (statistics): For a perfect Normal distribution, the skewness and kurtosis statistics should be zero (or close to zero). Rough rule of thumb is if these are within –1 and +1 pulse rates would indicate normal distribution in the population represented by this sample.

3. Skewness & Kurtosis (z-scores):

• Calculate z-score for skewness (z _s ) & report if it is within ± 1.96 or not? (i.e. less than 1.96 and greater than -1.96)

Skewness z-score = Skewness statistic/ Skewness std. error

z _s = 0.379 / 0.241 = 1.57 & yes within ± 1.96

• Calculate z-score for kurtosis (z _k) & report if within ± 1.96 or not?

Kurtosis z-score = Kurtosis statistic/Kurtosis std. error

z _k = -.518 / 0.478 = -1.08. Yes within ± 1.96

4. Shapiro-Wilk test of Normality: What is this test for & how will the result be interpreted in light of its Significance value/p value?

SW test is commonly used to assess any departures from normality, even for small samples. P value for SW test is .023 so the assumption of normality is violated.

SW tests the null hypothesis that sample represents a population where the test variable (i.e. Pulse rate During Exam) is normally distributed.

• If p value is 0.05 or higher we retain null and assumption is not violated
• If p= <.05 we reject null and normality assumption is violated.

The assumption of normality may be violated here but the overall conclusion should not be based on just SW test.

5. Histogram: How would you interpret this graph below?

Histogram below looks symmetric; there is one peak and two ‘tails’ which are similar in length. There are no extreme values either on the lower end or on the higher end. Details in Lecture 3A especially from assessment point of view.

NOTE: You may not get a normal curve overlay with Explore function but you can add this by double clicking inside the Histo gram and then clicking Show Distribution Curve on the top menu; (just hover your cursor in the entire length of bottom row till you find it).

You can also use Chart Builder to obtain histogram with normal curve overlay as we did in earlier labs.

6. Stem and Leaf Plot: How would you describe your graph?

• Based on the above Stem and Leaf plot above how many students had pulse rate of 66 beats/min and how many with 98 beats/min during exam? Five students and no one, respectively.

• What were the lowest and highest heart rates during the exam? 48 and 100, respectively.

7.a) How will you describe the Normal Q-Q plot below?

Points are not too far off the diagonal line. For a perfect Normal distribution all the points will fall on the diagonal line (rarely happens with real data). If the variable has a skewed distribution the points have a curved shape. Details in Lecture 3A especially from assessment point of view.

7.b) How will you describe Detrended Normal Q-Q Plot below?

As the name ‘Detrended’ suggests data points should be roughly scattered all over the place above and below the horizontal line with no specific trend. N umber of points above and below the horizontal line should be roughly similar. Now what does trend mean here and what we should be on the lookout for is discussed in the lecture 3A. 

Assessment Requirements – Summary

This assessment required students to demonstrate their understanding of the scientific research process and apply statistical analysis techniques using SPSS. The tasks were divided into multiple parts:

1. Research Question & Study Design

   • Formulate a research question around Physical Activity and First Year Curtin Students.
   • State the aim, benefits, and appropriate study design.
   • Define inclusion criteria, sampling method, and recruitment strategy.
   • Identify independent/dependent variables and additional factors.

   • Provide measurement scales and categories.

2. Normality Testing

   • Select a variable and check for normal distribution using SPSS.
   • Interpret Mean, Median, Mode, Skewness, Kurtosis, z-scores, Shapiro-Wilk test, histogram, stem-and-leaf plot, and Q-Q plots.

   • Provide both SPSS outputs and written explanations.

3. Bivariate Association

   • Choose two variables to test for an association.

   • Perform the appropriate analysis and provide SPSS output with a short report.

4. Descriptive Statistics & Graphs

   • Provide statistics and graphs for continuous and categorical variables.
   • Include scatterplots, cross-tabulation, and recoding into binary variables with frequency tables.

   • Interpret each visual briefly.

5. Bivariate Correlation

   • Select two variables to test correlation.
   • Present SPSS results and provide a short interpretation.

Assessment focus:

• Applying statistical concepts in practice.
• Interpreting SPSS outputs accurately.
• Linking statistical results with research questions.
• Academic communication and critical interpretation.

Mentor’s Step-by-Step Guidance Approach

The academic mentor supported the student through a systematic process:

1. Clarifying Requirements

   • Explained the structure of the assessment and the importance of balancing both conceptual understanding (research design) and practical application (SPSS analysis).

2. Developing the Research Question

   • Guided the student in formulating a clear, measurable research question related to physical activity and first-year students.

   • Helped align the research aim, benefits, and study design with the question.

3. Defining Variables & Measurement

   • Mentor demonstrated how to identify independent and dependent variables, along with three additional control factors.

   • Discussed correct measurement scales (nominal, ordinal, interval, ratio) and units for each.

4. SPSS Normality Checks

   • Walked the student through running normality tests in SPSS.
   • Explained step by step how to interpret skewness, kurtosis, z-scores, Shapiro-Wilk test, histograms, and Q-Q plots.

   • Highlighted the importance of using multiple checks before concluding normality.

5. Bivariate Association & Correlation

   • Helped choose variables logically connected to the research question.
   • Explained how to run chi-square, correlation, or other suitable tests.

   • Reviewed how to write short, precise interpretations of SPSS outputs.

6. Descriptive Statistics & Graphs

   • Mentor illustrated how to generate descriptive statistics and select the right type of graph for each variable.
   • Showed how to recode categorical/continuous variables into binary form.

   • Guided the student in writing short, insightful descriptions of graphs and tables.

7. Final Review & Report Writing

   • Ensured all SPSS outputs were included and matched with explanations.
   • Checked for clear academic writing, logical flow, and APA-style formatting.
   • Reinforced the importance of critical interpretation, not just reporting numbers.

Outcome & Learning Objectives Achieved

By the end of the assessment, the student successfully:

• Formulated a research question with clear aim and study design.
• Identified relevant variables, sampling methods, and measurement scales.
• Applied SPSS to test normality, run bivariate associations, correlations, and produce descriptive statistics with graphs.
• Interpreted results clearly, linking them back to the research context.
• Produced a structured, well-explained assignment that met academic requirements.

Learning Objectives Covered:

• Understanding research design and its role in answering scientific questions.
• Applying SPSS techniques for data analysis and interpretation.
• Evaluating statistical outputs critically rather than relying on one test.
• Developing academic writing and communication skills to present findings effectively.
• Building confidence in independent research and data analysis.

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