Public learning track
Data Presentation, Cleaning, and Outlier Analysis
8 lessons
Goal
Construct and interpret statistical diagrams, calculate frequency densities in histograms, identify outliers, and clean raw data.
Featured Diagrams
Categorising Data: Quantitative, Qualitative, Discrete, and Continuous
8 lessons
0 of 8 done
- Categorising Data: Quantitative, Qualitative, Discrete, and ContinuousUp next
- Histograms: Frequency Density and Unequal Class WidthsNot started yet
- Estimating Frequencies and Probabilities from HistogramsNot started yet
- Cumulative Frequency Curves, Medians, and PercentilesNot started yet
- Outlier Detection and Box-and-Whisker PlotsNot started yet
- Comparing Data Distributions Using Box PlotsNot started yet
- Cleaning Data: Dealing with Missing Data and AnomaliesNot started yet
- Critiquing Data Presentation TechniquesNot started yet
Standards Covered
- L1General Certificate of Education Advanced Level (UK A-Level) · Maths · Grade 11[Interpret diagrams for single-variable data, including understanding that area in a histogram represents frequency] [Connect to probability distributions]
- L4General Certificate of Education Advanced Level (UK A-Level) · Maths · Grade 11[Recognise and interpret possible outliers in data sets and statistical diagrams] [Select or critique data presentation techniques in the context of a statistical problem] [Be able to clean data, including dealing with missing data, errors and outliers]
Curriculum Framework
11th Grade · Math · UK A-Level
39
4 lessons
Critically Evaluating Data Representation
40
4 lessons
Damped Oscillations
42
6 lessons
de Moivre's Theorem: Proof and Powers
43
8 lessons
Definite Integrals and Applications of Area