Grade 12 Advanced Statistics - Medium
A medium grade 12 worksheet for Advanced Statistics.
Worksheet snapshot
- Advanced Statistics
- Key concepts: Understanding core advanced statistics concepts for Grade 12; Applying advanced statistics strategies appropriate to Grade 12
- Students develop fluency with advanced statistics at Grade 12 level, applying strategies more independently and solving increasingly complex problems.
- Apply it: Advanced Statistics at the Grade 12 level connects to everyday situations students encounter: problem-solving in daily life, making sense of quantities and relationships, and building mathematical literacy for future learning.
- For the data set { 1, 8, 13, 14, 14, 14, 15, 18 }, find the mean.
- For the data set { 0, 1, 1, 1, 3, 6, 16, 18, 19 }, find the mean.
- For the data set { 1, 4, 7, 7, 9, 13, 17 }, find the mean.
About Advanced Statistics
Advanced statistics includes distributions, hypothesis testing, confidence intervals, regression analysis, and inferential statistics. Students learn to analyze data, make inferences, and understand statistical reasoning.
Statistics is essential for understanding research, making data-driven decisions, and being an informed citizen. Advanced statistics underlies research in all fields from medicine to social science.
Statistics & Inference
Summarize data, interpret distributions, and make inferences using probability models and sampling; interpret correlation and simple regression.
This medium level worksheet:
Use sampling methods; compute/apply probability models; interpret correlation coefficients and simple linear regression outputs.
Key Concepts
- Center, spread, shape of distributions
- Sampling/bias and probability links
- Correlation/regression interpretation
Prerequisite skills
Mean/median/mode; percent/ratio reasoning; graph interpretation.
Teaching Strategies
Use real data sets; emphasize context with statistics; discuss bias/study design; use technology for regression/plots.
Assessment ideas
Test distribution understanding (normal, binomial). Include hypothesis test problems. Ask students to interpret confidence intervals. Use regression analysis tasks. Include study design and bias identification.
Common Challenges
Correlation vs. causation confusion; misreading scatterplots; ignoring variability/sample size.
Real-World Applications
Surveys, experiments, business/science data analysis.
Extension Activities
Collect data, compute summaries, fit a line, and interpret; critique a media graph; simulate sampling variability.
Parent Tips
When you see a graph or claim, ask about sample size, possible bias, and whether correlation implies causation.