Research Presentation
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Communicating research findings effectively is as important as conducting the research itself. Whether presenting to peers, writing a paper, or creating a poster, clear and accurate presentation ensures your work contributes to scientific knowledge and can be understood and evaluated by others.
Components of a Research Paper
IMRaD Structure
Most scientific papers follow the IMRaD format:
- Introduction: Background, research question, hypothesis, significance
- Methods: How the study was conducted (detailed enough to replicate)
- Results: What was found (data, statistics, figures)
- Discussion: What the results mean, limitations, future directions
| Section | Purpose | Key Elements |
|---|---|---|
| Abstract | Summarize entire paper | Background, methods, key results, conclusions (150-300 words) |
| Introduction | Provide context and rationale | Literature review, gap in knowledge, research question, hypothesis |
| Methods | Enable replication | Participants, materials, procedure, statistical analysis |
| Results | Present findings objectively | Data, statistical tests, figures, tables (no interpretation) |
| Discussion | Interpret and contextualize | Meaning of results, limitations, implications, future research |
| References | Credit sources | All cited works in consistent format (APA, MLA, etc.) |
Data Visualization
Choosing the right type of graph or chart is crucial for effectively communicating your data.
| Data Type | Best Visualization | Example Use |
|---|---|---|
| Trends over time | Line graph | Temperature changes over months |
| Comparisons between groups | Bar chart | Test scores by treatment group |
| Parts of a whole | Pie chart | Budget allocation by category |
| Relationship between variables | Scatter plot | Height vs. weight correlation |
| Distribution of data | Histogram | Frequency of test scores |
| Range and quartiles | Box plot | Comparing distributions across groups |
Principles of Effective Data Visualization
- Label everything: Axes, units, legend, title
- Keep it simple: Avoid chartjunk and unnecessary decoration
- Be honest: Start axes at zero when appropriate, don't manipulate scales
- Use appropriate scales: Linear vs. logarithmic based on data
- Include error bars: Show variability when relevant
- Caption figures: Brief description that enables understanding without reading full text
Statistical Reporting
Key Statistics to Report
- Sample size (n): Number of participants or observations
- Measures of central tendency: Mean, median, or mode
- Measures of variability: Standard deviation, range, IQR
- Test statistic: t, F, chi-square, etc.
- p-value: Probability of results if null hypothesis is true
- Effect size: Magnitude of the difference or relationship
- Confidence intervals: Range of plausible values
Example Statistical Report
"Students in the experimental group (M = 82.3, SD = 8.2) scored significantly higher than the control group (M = 74.6, SD = 9.1), t(48) = 3.14, p = .003, d = 0.89."
This includes: both group means, standard deviations, test statistic with degrees of freedom, p-value, and effect size (Cohen's d).
Oral Presentations
Structure of a Research Presentation
- Opening: Hook audience, state research question (1-2 minutes)
- Background: Why this matters, what's known (2-3 minutes)
- Methods: Brief overview of approach (2-3 minutes)
- Results: Key findings with visuals (5-7 minutes)
- Conclusions: Main takeaways, implications, limitations (2-3 minutes)
- Questions: Engage with audience (varies)
Presentation Best Practices
- Know your audience: Adjust technical language accordingly
- Less text, more visuals: Slides support speech, don't replace it
- Practice timing: Rehearse multiple times
- Speak to the audience: Not to your slides
- Anticipate questions: Prepare for likely inquiries
- Have backup slides: Additional data for detailed questions
Scientific Posters
Poster Layout
Effective posters typically include:
- Title: Large, clear, informative (visible from 4-6 feet)
- Authors and affiliations: Below title
- Introduction: Brief background and objectives
- Methods: Condensed but complete
- Results: Focus on figures and tables with brief text
- Conclusions: Key findings and implications
- References: Abbreviated list of key sources
- Acknowledgments: Funding, assistance, etc.
Scientific Writing Style
Key Principles
- Clarity: Use precise language, define technical terms
- Conciseness: Eliminate unnecessary words
- Objectivity: Report findings without bias or emotion
- Passive voice (when appropriate): "The solution was heated" (methods)
- Past tense: For methods and results ("we measured," "results showed")
- Present tense: For established facts and conclusions
- Hedging: Appropriate qualifiers ("suggests," "may indicate")
Citations and Academic Integrity
When to Cite
- Direct quotes (use quotation marks)
- Paraphrased ideas from sources
- Data or statistics from other studies
- Theories, methods, or frameworks developed by others
- Images, figures, or tables from other sources
You don't need to cite: Common knowledge, your own original ideas, or results from your own study.
ACT/SAT Connection
Understanding research presentation helps with:
- Reading and interpreting scientific passages
- Analyzing data presented in graphs and tables
- Evaluating conclusions based on evidence
- Understanding experimental summaries
- Writing evidence-based arguments
Examples
Example 1: Choosing Appropriate Visualizations
Problem: A researcher collected data on plant growth under three different light conditions over 8 weeks. What type of graph(s) should be used to present this data?
Solution:
This data has two aspects to communicate:
1. Change over time: A line graph would best show how each group's growth changed over the 8 weeks. Use three different lines (one per light condition) with time on the x-axis and plant height on the y-axis.
2. Comparison between groups: To compare final heights across conditions, a bar chart with error bars showing standard deviation would be effective.
Best approach: Use a line graph as the primary visualization (shows both trends over time AND allows comparison), with perhaps a supplementary bar chart comparing final heights with statistical significance indicated.
Essential elements:
- Clear title: "Plant Height Over 8 Weeks Under Different Light Conditions"
- Labeled axes: "Time (weeks)" and "Plant Height (cm)"
- Legend identifying each light condition
- Error bars showing variability (if applicable)
Example 2: Writing an Abstract
Problem: Write an abstract for a study that investigated whether listening to classical music while studying improves test performance. The study had 60 college students randomly assigned to music or silence conditions, studying for 30 minutes before a vocabulary test. The music group scored higher (M = 78.2) than the silence group (M = 72.1), p = .04.
Solution:
Sample Abstract:
"This study examined the effect of classical music on academic performance during studying. Sixty college students were randomly assigned to study vocabulary words for 30 minutes either while listening to classical music (n = 30) or in silence (n = 30). Participants then completed a vocabulary test. Results indicated that students who studied with classical music (M = 78.2, SD = 10.3) scored significantly higher than those who studied in silence (M = 72.1, SD = 11.7), t(58) = 2.12, p = .04, d = 0.55. These findings suggest that classical music may enhance learning, possibly by reducing stress or improving focus. However, the moderate effect size indicates individual differences may play a role. Future research should examine whether the effect persists over longer study periods and with different types of academic material."
Key elements included: Background/purpose, methods summary, key results with statistics, and brief interpretation with limitations.
Example 3: Improving a Graph
Problem: A student creates a bar graph showing average test scores for three groups but receives feedback that the graph is misleading. The y-axis starts at 70 instead of 0, making a 5-point difference appear dramatic. How should this be fixed?
Solution:
The Problem: Starting the y-axis at 70 instead of 0 visually exaggerates differences. For example, if Group A scored 75 and Group B scored 80, starting at 70 makes Group B's bar appear twice as tall as Group A's, when the actual difference is only about 7%.
Solutions:
Option 1: Start the y-axis at 0 to show proportional differences accurately. This is the most honest approach for bar charts.
Option 2: If starting at 0 compresses the data too much, use a broken axis (indicated by a break symbol //) but clearly note this in the caption.
Option 3: If the focus is on differences rather than absolute values, consider reporting the differences directly or using a different visualization (like showing change from baseline).
Additional improvements:
- Add error bars to show variability
- Include sample sizes for each group
- Add a descriptive caption
- If statistical tests were performed, indicate significant differences (e.g., with asterisks)
Example 4: Reporting Statistics
Problem: Convert these raw results into a properly formatted statistical report: "Group 1 average was 45.3 with SD of 6.2 and n=40. Group 2 average was 51.7 with SD of 7.1 and n=40. The t-test gave t=4.31 and p=0.00004."
Solution:
Formatted Report:
"Participants in the experimental condition (M = 51.7, SD = 7.1, n = 40) demonstrated significantly higher scores than those in the control condition (M = 45.3, SD = 6.2, n = 40), t(78) = 4.31, p < .001, d = 0.96."
Key formatting notes:
- M (mean) and SD (standard deviation) italicized
- Degrees of freedom in parentheses after t: t(78) where df = n1 + n2 - 2
- p-value rounded appropriately (p < .001 rather than p = 0.00004)
- Effect size (Cohen's d) calculated and included: d = (51.7-45.3)/6.65 = 0.96 (large effect)
- Descriptive context provided ("significantly higher")
The pooled SD for Cohen's d: sqrt[(6.2² + 7.1²)/2] = 6.67
Example 5: Creating Presentation Slides
Problem: You have 10 minutes to present research on the effectiveness of a new study technique. Create an outline for your slides and identify what should appear on each.
Solution:
Slide 1 - Title (30 sec):
- Title: "The Effects of Spaced Repetition on Long-Term Retention"
- Your name and affiliation
- Date
Slide 2 - Research Question (1 min):
- The problem: Students forget material quickly
- Research question: "Does spaced repetition improve retention compared to massed practice?"
- Key visual or hook
Slide 3 - Background (1.5 min):
- Brief literature review (2-3 key findings)
- Gap in knowledge
- Hypothesis
Slide 4 - Methods (2 min):
- Participants: n, demographics
- Design diagram or flowchart
- Key procedures
Slide 5-6 - Results (3 min):
- Main graph showing key finding
- Statistical results
- Secondary findings if relevant
Slide 7 - Conclusions (1.5 min):
- Key takeaway (1-2 sentences)
- Limitations
- Implications for practice
- Future directions
Slide 8 - Questions:
- "Thank you - Questions?"
- Contact information
Backup slides: Detailed methodology, additional data, references
Practice
1. In the IMRaD structure, where would you report the statistical tests used and their results?
A) Introduction B) Methods C) Results D) Discussion
2. Which type of graph would best show the relationship between hours of sleep and test scores for 100 students?
A) Pie chart B) Line graph C) Scatter plot D) Bar chart
3. Which element should NOT typically appear in a scientific abstract?
A) Research question B) Key results C) Detailed methodology D) Main conclusions
4. A graph showing percentage of budget allocated to different departments would best use a:
A) Scatter plot B) Line graph C) Pie chart D) Histogram
5. What does a p-value of 0.03 indicate?
A) There is a 3% chance the results are correct B) There is a 3% probability of obtaining these results if the null hypothesis is true C) The effect size is 0.03 D) 3% of participants showed the effect
6. Which section of a research paper would include limitations of the study?
A) Introduction B) Methods C) Results D) Discussion
7. Error bars on a graph typically represent:
A) Mistakes in data collection B) Missing data points C) Variability in the data D) Outliers
8. When presenting research orally, slides should primarily contain:
A) Complete sentences from your script B) Visuals and key points C) All your data tables D) Full paragraphs of explanation
9. Which is an example of appropriate hedging language in scientific writing?
A) "This definitely proves that..." B) "These results suggest that..." C) "It is obvious that..." D) "This conclusively demonstrates..."
10. In a scientific paper, which statement requires a citation?
A) "Water freezes at 0 degrees Celsius" B) "Our study found a mean score of 75.3" C) "Previous research found that sleep deprivation impairs memory" D) "Participants were tested in a quiet room"
Click to reveal answers
- C) Results - Statistical test outcomes go in Results. Methods describes which tests were planned; Discussion interprets what the results mean.
- C) Scatter plot - Scatter plots show relationships between two continuous variables and can reveal correlations.
- C) Detailed methodology - Abstracts should be concise (150-300 words) and include only a brief summary of methods, not detailed procedures.
- C) Pie chart - Pie charts show parts of a whole, making them ideal for budget allocation percentages that sum to 100%.
- B) There is a 3% probability of obtaining these results if the null hypothesis is true - This is the correct definition of p-value. It's not the probability of being correct.
- D) Discussion - Limitations are discussed in the context of interpreting results and suggesting future research.
- C) Variability in the data - Error bars typically show standard deviation, standard error, or confidence intervals.
- B) Visuals and key points - Slides support your speech; they shouldn't contain everything you say.
- B) "These results suggest that..." - Hedging acknowledges uncertainty and avoids overstating conclusions.
- C) "Previous research found that sleep deprivation impairs memory" - This references others' findings and requires citation. Common knowledge and your own results don't need citations.
Check Your Understanding
1. Why is it important that the Methods section of a research paper be detailed enough for replication? What problems arise when methods are poorly described?
Show answer
Detailed methods are essential for several reasons: (1) Replication - Science advances through verification. Other researchers must be able to repeat your study to confirm findings. Without sufficient detail, replication is impossible. (2) Evaluation - Readers need to assess whether your methods are sound before trusting conclusions. Poor descriptions prevent proper evaluation of validity. (3) Troubleshooting - If results differ in replications, detailed methods help identify why. (4) Building on work - Future researchers may want to extend your work with modifications. Problems with poor methods descriptions include: inability to verify findings leading to distrust, potential for hidden biases going undetected, wasted resources as others try to recreate unclear procedures, and slower scientific progress as foundational studies can't be confirmed or built upon.
2. Explain the difference between statistical significance and practical significance. Why is it important to report effect sizes alongside p-values?
Show answer
Statistical significance indicates whether an observed effect is likely due to chance (typically p < .05). However, with large enough samples, even tiny differences become statistically significant. Practical significance concerns whether the effect is large enough to matter in the real world. For example, a drug might produce a statistically significant 0.5-point improvement on a 100-point pain scale (p < .001 with n = 10,000), but this difference is too small to be clinically meaningful.
Effect sizes (like Cohen's d, r, or eta-squared) quantify the magnitude of an effect independent of sample size. Reporting both helps readers understand: (1) Is this effect real? (p-value) and (2) Is this effect meaningful? (effect size). Guidelines for Cohen's d: small = 0.2, medium = 0.5, large = 0.8. A study might find p = .04 (significant) but d = 0.1 (tiny effect), meaning the effect, while real, may not be worth implementing in practice.
3. How can data visualizations be manipulated to mislead readers? Describe three common techniques and how to identify them.
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1. Truncated Y-axis: Starting the y-axis at a value other than zero exaggerates differences. A bar going from 50 to 52 looks like a doubling if the axis starts at 50, when it's actually a 4% increase. Detection: Always check where axes start. For bar charts especially, starting above zero is often misleading.
2. Manipulated scales: Using different scales on comparison graphs, or non-linear scales without indication, can distort perception. Logarithmic scales make exponential growth look linear. Detection: Compare axis ranges, check for scale breaks, look for linear vs. log notation.
3. Cherry-picking time ranges: Showing only the portion of time series data that supports a claim. Stocks might show 6 months of gains while hiding 5 years of losses. Detection: Ask what the full dataset looks like, be suspicious of convenient start/end points.
Other techniques: Using 3D effects that distort proportions, inconsistent intervals, unlabeled or misleading legends, showing correlation as causation through visual juxtaposition, or using area/volume to represent linear quantities (making differences appear squared or cubed).
4. Compare and contrast written research papers, oral presentations, and scientific posters as methods of communicating research. When is each most appropriate?
Show answer
Written Papers:
- Strengths: Complete detail, permanent record, allows deep analysis, readers control pace
- Limitations: Time-intensive to read, no immediate interaction
- Best for: Formal publication, complete documentation, reaching global audience
Oral Presentations:
- Strengths: Dynamic delivery, real-time Q&A, can gauge audience understanding, persuasive potential
- Limitations: Time-limited, audience can't review later, presenter dependent
- Best for: Conferences, preliminary findings, engaging specific audiences, explaining complex ideas
Posters:
- Strengths: Visual summary, one-on-one discussion possible, viewers control depth of engagement
- Limitations: Limited detail, dependent on presenter availability, must distill extensively
- Best for: Conference poster sessions, networking, preliminary/ongoing work, visual data
Effective researchers use all three, adapting content and style to each format's strengths. A project might be presented as a poster at a conference, given as a talk at a department meeting, and published as a journal article - each serving different communication goals.
🚀 Next Steps
- Review any concepts that felt challenging
- Move on to the next lesson when ready
- Return to practice problems periodically for review