Grade 6 Mathematics
Develop statistical literacy and probabilistic reasoning through authentic data investigations and hands-on probability experiments. Students learn to collect, analyze, and interpret data while exploring chance and uncertainty.
By the end of these activities, students will be able to:
Understanding different data types helps students choose appropriate representations
Data that can be divided into categories
Data that can be counted in whole numbers
Data that can be measured and includes decimals
Data collected over time periods
Students conduct a complete statistical investigation from question formulation to data presentation and analysis.
Brainstorm statistical questions about school community. Focus on questions that anticipate variability in responses.
Design survey with both qualitative and quantitative questions. Consider sample size and data collection methods.
Collect data from different grade levels using systematic sampling. Record responses carefully and completely.
Organize data using appropriate graphs (bar, line, histogram). Calculate measures of central tendency.
Present findings to school administration with data-supported recommendations for school improvement.
Students analyze local weather data to identify patterns, calculate statistics, and make predictions about climate trends.
Collect local weather data for one month from reliable sources. Include temperature, rainfall, and other relevant measures.
Create multiple data representations (line graphs for temperature trends, histograms for rainfall distribution).
Calculate mean, median, mode, and range for temperature and rainfall. Identify outliers and discuss their significance.
Compare current month's data to historical averages. Discuss variations and potential causes.
Make predictions about future weather patterns. Discuss difference between climate and weather, data reliability.
Students design carnival games while exploring probability concepts, fairness, and the relationship between theoretical and experimental probability.
Design carnival games with different probability outcomes. Consider game rules, winning conditions, and prize structures.
Calculate theoretical probabilities for each game outcome. Determine expected win rates and fairness.
Build physical games using available materials. Ensure games can be tested multiple times reliably.
Test games with multiple trials to find experimental probabilities. Record results systematically.
Compare theoretical vs. experimental results. Present games to other classes and discuss probability concepts.
Students explore compound probability through systematic experiments involving multiple steps and create visual representations of outcomes.
Design experiments with two steps (e.g., flip coin then roll die, draw two balls). Define all possible outcomes.
Create tree diagrams showing all possible outcomes systematically. Label branches with probabilities.
Calculate theoretical probabilities for compound events using multiplication rule and tree diagrams.
Conduct experiments recording actual results. Use systematic listing to ensure all outcomes are captured.
Compare theoretical and experimental probabilities. Discuss why experimental approaches theoretical with more trials.
Essential terms students should understand and use correctly
The expected probability based on mathematical analysis
The actual probability observed through trials and experiments
An event that consists of two or more simple events
A visual representation showing all possible outcomes of compound events
The set of all possible outcomes in a probability experiment
The outcomes that satisfy the conditions of an event
A game where all players have equal probability of winning
A systematic error that affects the fairness or accuracy of data collection
A systematic approach to conducting statistical investigations
Ask statistical questions that anticipate variability in the data
Gather data systematically using appropriate methods and tools
Create graphs, calculate statistics, and identify patterns
Draw conclusions and make predictions based on the data
