Predicting Our Weather: A Data Analysis Project
Inquiry Framework
Question Framework
Driving Question
The overarching question that guides the entire project.How can mathematical analysis of historical weather patterns help us make reliable predictions about future weather trends in our local area?Essential Questions
Supporting questions that break down major concepts.- How can we use mathematical concepts like mean, median, and mode to analyze weather data?
- What patterns can we identify in historical weather data?
- How reliable are weather predictions based on mathematical analysis?
Standards & Learning Goals
Learning Goals
By the end of this project, students will be able to:- Analyze weather data using mean, median, and mode.
- Identify patterns in historical weather data.
- Evaluate the reliability of weather predictions based on mathematical analysis.
math
Entry Events
Events that will be used to introduce the project to studentsEmergency Weather Alert
Students receive a fictional emergency alert about an impending severe weather event, but the data is incomplete or contradictory. They must use their math skills to analyze the available information and advise the community on how to prepare.Portfolio Activities
Portfolio Activities
These activities progressively build towards your learning goals, with each submission contributing to the student's final portfolio.Statistical Weather Analysis
Students calculate the mean, median, and mode for both high and low temperatures from their collected data.Steps
Here is some basic scaffolding to help students complete the activity.Final Product
What students will submit as the final product of the activityA summary report detailing the calculated mean, median, and mode for high and low temperatures, along with a brief interpretation of what these values indicate about the typical temperature range during the data collection period.Alignment
How this activity aligns with the learning objectives & standardsCovers 6.SP.4 (Calculate measures of center (mean, median) and describe overall pattern).Trend Tracker: Visualizing and Predicting
Students create a visual representation of their temperature data using a line graph and analyze the distribution to predict temperature trends.Steps
Here is some basic scaffolding to help students complete the activity.Final Product
What students will submit as the final product of the activityA line graph displaying high and low temperatures over the two-week period, accompanied by a written analysis of observed trends and a prediction for the next three days.Alignment
How this activity aligns with the learning objectives & standardsCovers 6.SP.4 (Relate the choice of measures of center to the shape of the data distribution and the context in which the data were gathered).Rubric & Reflection
Portfolio Rubric
Grading criteria for assessing the overall project portfolioWeather Prediction Project Rubric
Statistical Weather Analysis
Focuses on the student's ability to accurately calculate and interpret statistical measures related to weather data.Statistical Accuracy
Accuracy of calculations of mean, median, and mode for high and low temperatures.
Exemplary
4 PointsCalculations are completely accurate, demonstrating a sophisticated understanding of statistical measures. Shows meticulous attention to detail.
Proficient
3 PointsCalculations are mostly accurate with only minor errors, demonstrating a thorough understanding of statistical measures.
Developing
2 PointsCalculations contain some errors, indicating an emerging understanding of statistical measures. Needs some guidance to correct errors.
Beginning
1 PointsCalculations contain significant errors or are incomplete, indicating a limited understanding of statistical measures. Requires significant support.
Report Clarity and Interpretation
Clarity and completeness of the summary report explaining the meaning of the calculated values.
Exemplary
4 PointsReport is exceptionally clear, insightful, and thoroughly explains the meaning of mean, median, and mode in the context of the temperature data. Demonstrates an innovative and nuanced understanding.
Proficient
3 PointsReport is clear, complete, and explains the meaning of mean, median, and mode in the context of the temperature data.
Developing
2 PointsReport is somewhat unclear or incomplete, with a basic explanation of the meaning of mean, median, and mode. Shows a developing understanding.
Beginning
1 PointsReport is unclear, incomplete, and lacks a clear explanation of the meaning of mean, median, and mode. Requires substantial improvement.
Trend Tracker: Visualizing and Predicting
Assesses the student's ability to visualize weather data, identify trends, and make informed predictions.Graph Accuracy and Clarity
Accuracy and clarity of the line graph displaying temperature data. Proper labeling and scaling are essential.
Exemplary
4 PointsLine graph is exceptionally accurate, visually appealing, and easy to interpret. Demonstrates meticulous attention to detail in labeling and scaling, enhancing data representation.
Proficient
3 PointsLine graph is accurate, clear, and easy to interpret, with proper labeling and scaling.
Developing
2 PointsLine graph contains some inaccuracies or is somewhat unclear, with minor issues in labeling or scaling. Requires refinement for better clarity.
Beginning
1 PointsLine graph is inaccurate, unclear, or difficult to interpret, with significant issues in labeling and scaling. Requires significant revision.
Trend Analysis and Prediction
Quality of the trend analysis and justification for temperature predictions. Focuses on identifying patterns and providing logical support for predictions.
Exemplary
4 PointsTrend analysis is insightful and comprehensive, providing a well-reasoned and compelling justification for temperature predictions. Demonstrates exceptional critical thinking and innovative application of data.
Proficient
3 PointsTrend analysis is thorough and provides a logical justification for temperature predictions based on observed patterns.
Developing
2 PointsTrend analysis is basic and provides a limited justification for temperature predictions. Requires more in-depth analysis and reasoning.
Beginning
1 PointsTrend analysis is weak or missing, with little to no justification for temperature predictions. Requires substantial improvement in analytical skills.