LCHL Analysing data graphically and numerically, interpreting and drawing inferences from data
I should be able to:
Foundation Level
– interpret graphical summaries of data
– relate the interpretation to the original question
– recognise how sampling variability influences the use of sample information to make statements about the population
– use appropriate tools to describe variability, drawing inferences about the population from the sample
– interpret the analysis
– relate the interpretation to the original question
Ordinary Level
– recognise how sampling variability influences the use of sample information to make statements about the population
– use appropriate tools to describe variability drawing inferences about the population from the sample
– interpret the analysis and relate the interpretation to the original question
– interpret a histogram in terms of distribution of data
– make decisions based on the empirical rule
– recognise the concept of a hypothesis test
– calculate the margin of error (1/Sq. Root(n) ) for a population proportion*
* The margin of error referred to here is the maximum value of the radius of the 95% confidence interval.
– conduct a hypothesis test on a population proportion using the margin of error
Higher Level
– build on the concept of margin of error and understand that increased confidence level implies wider intervals
– construct 95% confidence intervals for the population mean from a large sample and for the population proportion, in both cases using z tables
– use sampling distributions as the basis for informal inference
– perform univariate large sample tests of the population mean (two-tailed z-test only) ka1.7.4.a
– use and interpret p-values
* The margin of error referred to here is the maximum value of the radius of the 95% confidence interval.
Project Maths Presentation: Inferential Statistics
Overview of Inferential Statistics
Inferential Statistics Sample Questions
Inferential Statistics Summary Sheet
A Guide to the Statistics on the Leaving Cert