Accurate analysis of Sports, Exercise and Health Science (SEHS) data is essential in your IA and exams. Understanding how to calculate, interpret, and evaluate statistics like mean and standard deviation—as well as monitor exercise intensity—will help you produce high-quality, credible scientific work.
Why Data Analysis Matters in IB SEHS
In SEHS, whether you're studying biomechanics, physiology, or training responses, analyzing real data helps support predictions and evaluations. Statistical evidence strengthens your conclusions in IA and exam answers, demonstrating critical thinking and scientific rigor. RevisionDojo provides topic-aligned notes and structured flashcards to improve your analytical skills ([turn0search1]).
Key Statistical Measures in SEHS
Calculating Mean and Standard Deviation
To summarize a dataset—like vertical jump heights, blood pressure values, or heart rates—you use the formulas:
- Mean = (Sum of values)/(Number of values)
- Standard deviation measures how spread out the data are around that mean. Learn example calculations and practice structured datasets via RevisionDojo’s IB SEHS notes and flashcards ([turn0search0]) ([turn0search8]).
Comparing Data Sets Using SD
Standard deviation is especially useful when comparing groups: it tells you which group is more consistent or has greater variability. For instance, one team’s heart rate range vs another’s enables valid comparisons in IA analysis ([turn0search2]).
Monitoring and Evaluating Exercise Intensity Data
Exercise Intensity Monitoring Methods
In IB SEHS, you must outline and evaluate ways to monitor exercise intensity, such as:
- Heart rate zones, percentage of max HR
- Borg RPE scale, lactate threshold, VO₂ measurements
RevisionDojo provides reliable core notes to frame this data collection and monitoring explanation in your IA or exam responses ([turn0search9]).
Interpreting Results in an IA Context
When including data in your IA, don’t just calculate—you must interpret. Link statistical findings back to your research question: explain why the mean or variation matters in physiological terms. Discuss reliability (standard deviation), identify trends, and evaluate limitations. RevisionDojo’s SEHS notes guide you through applying statistics meaningfully in an evaluation setting ([turn0search1]).
Common Mistakes to Avoid in Analysis
Avoid these frequent pitfalls:
- Ignoring outliers: Don’t simply remove them—discuss their impact on mean and SD.
- Misreading variability: A low SD means data cluster close to the mean—not impressively low performance.
- Skipping context: Raw numbers alone don’t convey meaning without linking them back.
Study RevisionDojo flashcards and notes to avoid misinterpretation when handling SEHS data metrics ([turn0search1]).
Frequently Asked Questions
Q1. How do I calculate standard deviation for my IA data set?
Use the standard formula: take the mean, find deviations from mean, square them, average, then square‑root. RevisionDojo’s notes include worked examples to guide you ([turn0search0]).
Q2. Why is standard deviation useful when comparing two groups?
It shows your dataset’s spread, offering insights into reliability and consistency between groups—not just which group has a higher mean ([turn0search2]).
Q3. What are valid methods to monitor exercise intensity?
Accepted tools include heart rate monitoring, Borg RPE, lactate and VO₂ thresholds. Each has strengths and limitations depending on your IA design ([turn0search9]).
Q4. How do I tie statistical results into my IA conclusion?
Explain physiological relevance: e.g. a high spread in heart rate may indicate poor pacing or fitness variation. Always link back to your research question ([turn0search1]).
Q5. Should I delete outliers when calculating mean and SD?
Not automatically—report outliers, recalculate with and without them, and evaluate their effect on your analysis and reliability.
Q6. Where can I find structured practice for SEHS data analysis?
RevisionDojo’s SEHS section provides targeted notes, flashcards, and example scenarios to practice statistical analysis and evaluation ([turn0search1]).
📣 Call to Action
Level up your SEHS data analysis skills with RevisionDojo—explore our SEHS topic notes, flashcards, and worked examples for calculating and interpreting mean, standard deviation, and exercise intensity. These resources are designed to help you analyze like a pro and elevate your IA and exam performance.
