Embedded Files
Writing a statistical report
Writing a statistical report
When writing you report, no matter what type of data you're investigating, you will need to follow the PPDAC cylce. PPDAC stands for Problem, Plan, Data, Analysis an Conclusion. Below is a guide for what is expected in each section of your report. It is split up into "needed to achieve" - things that must be in your report for you to pass, and the "ways to improve your grade" - things you can add to help get you to a Merit or Excellence.
Remember, your overal grade is also heavily influenced by how well your report is written - is it easy to read and follow? Do you use correct spelling and grammar? Do you use statistical terminology correctly? etc.
Report writing guide
Report writing guide
To Achieve this standard, you need to answer each of "needed to achieve" questions in full sentence. Complete the "ways to improve your grade" to bump this up to Merit or Excellence.
There are videos in each section below which explain what needs to be written in each section of the report, to ensure that you pass. The videos do not include how to improve your grade beyond Achieved. You will need to use you knowledge from what you have learned in class to do that.
Need more practice?
There is a couple of 1500m Year 9 vs Year 11 datasets at the bottom of this page, that you can copy paste into NZGrapher to practice your analysis.
The final version of the Achieved level report from the videos below can be found here:
Statistics Achieved Exemplar.pdfProblem
Problem
Needed to achieve:
What is the problem you are trying to solve?
What is the "population" in this investigation?
Ways to improve your grade:
Nothing extra needed.
Problem: Achieved level example
Plan
Plan
Needed to achieve:
Who collected the data?
When was the data collected?
How was the data collected?
Include a copy of the data collection plan.
How did you get your sample?
What was the size of each group in your sample?
Ways to improve your grade:
Merit
Describe at least 2 sources of variation and how they were managed in the data collection plan.
Excellence
Additionally, describe at least 2 possible sources of variation that were not managed at all, or could have been managed better in the data collection process. Explain how not managing these sources of variation may have impacted the results of the experiment.
Click here for more information about sources of variation.
Plan: Achieved level example
Data
Data
Needed to achieve:
Provide a link to your sample data spreadsheet.
What is your numerical variable, and what is it measured in?
What is your categorical variable, and what are the options?
Ways to improve your grade:
Nothing extra needed.
Data: Achieved level example
How to insert your data into NZGrapher
Analysis
Analysis
Needed to achieve:
Create a dot plot box and whisker plot using NZGrapher. Your graph needs:
An appropriate title and labels.
Summaries.
High Box Plot.
Mean Dot.
Comment on what do you see?
Centre
Which group has the higher mean and median?
Spread
Which group has narrower boxes, and what does this mean in terms of consistency of the data?
Shape
Is the data left-skewed, right-skewed or symmetrical?
Overlap
Can you find a 75% / 50% overlap?
Comment on what do the numbers say?
Median
What are the medians, which one is bigger and by how much?
Mean
What are the means, which one is bigger and by how much?
Interquartile range (IQR)
What are the IQRs, which one is smaller and what does this mean in terms of consistency of the data?
Shape
For each group, are the mean and medians similar to one another? Or is the mean higher/lower than the median?
What does this mean in terms of the shape of the data?
Ways to improve your grade:
Merit
Decide if the difference found between the groups in your sample data is enough to make the call back in the population.
To make the call that the difference is reflected in the poplation you need to:
Add "DBM & OVS (Numbers)" to you graph.
Find the difference between medians (DBM)
Find the overall visible spread (OVS)
State which threshold you will use
Datasets of around 30: DBM needs to be greater than 1/3 of the OVS to make the call (or DBM x 3 > OVS).
Datasets of around 100: DBM needs to be greater than 1/5 of the OVS to make the call (or DBM x 5 > OVS)
Datasets of around 1000: DBM needs to be greater than 1/10 of the OVS to make the call (or DBM x 10 > OVS)
Only if the DBM and OVS meet the threshold, you can make the call.
Excellence
Identify any potential outliers, giving all possible data about them.
Identify a third variable that may have had an impact on the features of your data.
Analysis: Achieved level example
Conclusion
Conclusion
Needed to achieve:
Nothing needed.
Ways to improve your grade:
Merit
Answer the problem in full, with reference to the population.
Excellence
Justify the validity of the inference back in the population, with reference to sampling.
Practice Data
Practice Data
Below are two more examples of sample 1500m race data. Each dataset has data for 100 Year 9s and 100 Year 10s.
Page updated
Report abuse