AQA GCSE Statistics Paper 2

Types of Data

• 3.2.1 Data Terminology and Classification
• 3.2.2 Data Grouping and Categorization
• 3.2.3 Explanatory and Response Variables

Data Sources and Reliability

• 3.2.4 Primary and Secondary Data
• 3.2.5 Data Collection Methods
• 3.2.6 Reliability and Validity

Population and Sampling

• 3.2.8 Populations, Sample Frames, and Samples
• 3.2.9 Defining Populations
• 3.2.10 Judgement and Opportunity Sampling

Data Collection Planning

• 3.2.14 Key Considerations in Data Collection

Managing Data Problems

• 3.2.15 Handling Missing and Incorrect Data
• 3.2.16 Data Cleaning Techniques
• 3.2.17 Extraneous Variables and Control Groups

Pictorial Data Representation

• 3.3.1 Creating and Comparing Pictorial Representations
• 3.3.2 Advanced Pictorial Representations 2 notes
  • Interpreting Population Pyramids and Choropleth Maps
  • Comparative Pie Charts and 2D and 3D Representations

Graphical Data Representation

• 3.3.3 Constructing and Interpreting Charts and Graphs 3 notes
  • Representing Data and Comparing Bar Charts
  • Interpreting Charts, Distributions and Cumulative Frequency
  • Frequency Density and Unequal-Width Histograms

Visualisation Formats and Misrepresentation

• 3.3.4 Selecting Appropriate Visualisations
• 3.3.5 Identifying Graphical Misrepresentation

Comparing and Selecting Representations

• 3.3.6 Extracting and Comparing Values Across Formats
• 3.3.7 Justifying Representation Choices

Averages

• 3.4.1 Average Calculations 2 notes
  • Mode, Median and Arithmetic Mean
  • Weighted Mean, Geometric Mean and Mean Seasonal Variation
• 3.4.2 Average Selection

Skewness

• 3.4.3 Skewness Determination

Measures of Spread and Outliers

• 3.4.4 Measures of Spread
• 3.4.5 Outlier Identification

Trends and Moving Averages

• 3.4.6 Trend Identification

• 3.4.7 Lines of Best Fit

• 3.4.8 Spearman's Rank Correlation

Estimates of Probabilities

• 3.4.9 Probability Estimates

Probability and Expected Frequencies

• 3.5.1 Probability Comparisons
• 3.5.2 Expected Frequencies
• 3.5.3 Relative and Absolute Risks

Experimental and Theoretical Probability

• 3.5.4 Bias Identification
• 3.5.5 Probability Convergence
• 3.5.6 Probability Diagrams

Comparing Data Sets

• 3.5.7 Central Tendency Comparisons
• 3.5.8 Spread Comparisons
• 3.5.9 Sample and Population Comparisons

Formal Probability Notation

• 3.5.11 Independent Events Notation
• 3.5.12 Conditional Probability Notation

Skewness and Outliers

• 3.5.13 Skewness Interpretation
• 3.5.14 Outlier Interpretation

• 3.5.15 Seasonal and Cyclic Trends

Rates of Change and Index Numbers

• 3.5.16 Rates of Change Interpretations
• 3.5.17 Rates of Change Calculations
• 3.5.18 Index Numbers

Correlation

• 3.5.19 Correlation Vocabulary
• 3.5.20 Correlation Strength
• 3.5.21 Correlation Versus Causation

Correlation Coefficients

• 3.5.22 Spearman's Rank Interpretation
• 3.5.23 Pearson's Correlation Coefficient
• 3.5.24 Correlation Coefficient Comparisons

Binomial Distribution and Bias

• 3.5.25 Bias Analysis
• 3.5.26 Binomial Distribution Characteristics

Normal Distribution and Quality Assurance

• 3.5.27 Normal Distribution Properties
• 3.5.28 Normal Distribution Probabilities
• 3.5.29 Quality Assurance Lines

Estimating Population Characteristics

• 3.5.31 Population Characteristic Estimates
• 3.5.32 Population Mean Estimates
• 3.5.33 Population Proportion Predictions

Sample Size and Reliability

• 3.5.35 Sample Size Impacts
• 3.5.36 Sample Mean Distributions

3.6.1 Initial Planning

• Initial Planning Strategies

3.6.2 Data Collection

• Data Collection Constraints

3.6.3 Data Processing and Presentation

• Data Processing and Presentation Techniques

3.6.4 Interpretation of Results

• Result Interpretation

3.6.5 Evaluation and Review

• Evaluation and Review Processes