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3.2 FSMQ Data Analysis (9993)

Data Analysis (9993)

 You should learn:Including:
Statistical diagrams
  • Box and whisker plot
  • Back-to-back stem and leaf diagram
  • Histogram
  • Cumulative frequency diagram
  • Grouping of data
  • Ideas of symmetry, skew and multi-modal distributions. Measures of skewness are not required.
Measures of location and spread
  • Mean ( , median, mode
  • Upper and lower quartiles
  • Percentiles
  • Range and inter-quartile range
  • Standard deviation ( and )
  • Outliers
  • Comparing and contrasting data sets
  • Using a calculator to find and
Bivariate data
  • Scatter diagrams
  • Ideas of positive, negative and no correlation
  • Pearson's product moment correlation coefficient (r)
  • Regression lines and the equation of the line of best fit
  • Use of mean values
  • Using a calculator to find r and regression line coefficients. Interpretation of these results
  • Understanding that correlation does not imply causation
  • Understanding that r is only a measure of linear correlation
Normal distribution
  • Features of a normal distribution; to include continuous data, symmetry and 2/3rds and 95% rules
  • Standard normal distribution with mean 0 and standard deviation 1
  • Use of tables to find probabilities and expected frequencies
  • Understanding how a theoretical distribution can be a model for a real population