AP Statistics 10 Minute Review

Introduction

• Purpose: Highlight key points and tips for AP exam, not exhaustive.

Describing Data

• Common Plots: Box plots, dot plots, histograms, stem plots.
• Description Components:
  • Shape: Skewness, unimodal/bimodal.
  • Spread: Range, IQR, standard deviation.
  • Center: Mean or median.
  • Outliers: Beyond 2 standard deviations or outside 1.5 IQR fence.
• Five Number Summary: Min, max, Q1, median, Q3.
• Scatter Plots: Describe strength, direction, shape, and outliers.

Collecting Data

• Sampling Methods:
  • Simple Random Sample: Randomly pick from entire population.
  • Stratified Sampling: Group by important variable, then sample.
  • Cluster Sampling: Randomly pick groups, sample everyone in chosen group.
  • Convenience Sampling: Easy, not fully random.
  • Systematic Sampling: Regular interval selection (e.g., every 10th item).
• Types of Bias:
  • Non-response Bias: Differences between respondents and non-respondents.
  • Undercoverage: Not sampling entire population.
  • Voluntary Response: Strong opinions from respondents.
  • Response Bias: Influence of survey situation.
  • Wording Bias: Question phrasing affecting responses.
• Experiments vs. Observational Studies:
  • Experiments: Random assignment, can show causality.
  • Observational Studies: Observe outcomes without intervention, show association.

Probability

• Distribution:
  • Identify type (Binomial, Geometric, Normal) and parameters.
  • Understand sampling vs. population distribution.
• Conditional Probability and Independence: Importance in probability calculations.
• Transformations:
  • Multiply by Constant: Affects mean and standard deviation.
  • Random Selection: Affects standard deviation based on number of selections.
• Adding Random Variables:
  • Add means directly.
  • Add standard deviations using a modified Pythagorean theorem (independent variables).

Hypothesis Testing

• Conditions: Random, independent, normal (for z/t tests), expected counts (for chi-squared).
• Naming and Execution:
  • Name test clearly (e.g., One Prop Z-Test, Two Sample Mean T-Test).
  • State null and alternative hypotheses.
  • Show test statistic and p-value.
  • Write conclusion in context.
• Confidence Intervals: Similar to hypothesis testing, show interval instead of p-value.

Conclusion

• Important Topics: Focused on FRQs and key concepts.
• Additional Resources: Mention of further videos for hypothesis testing details.