Introduction to making an inference
Inzight is the software to analyse data
An activity from Census At School: Kiwi Kaper
Achievement Standard clarification
91264 Use statistical methods to make an inference
Making a statistical ‘call’ (inference)
Plan: sampling (why did you choose this sampling process?)
(ObviousSpecificEvidenceMeaning) (Acronym: OSEM)
Conclusion (answer to your posed question)
Sampling variability statement: ( you must write)
Introduction to making an inferenceFollowing are address of links. To easily view the video clips go to the individual page of this site.

Inzight is the software to analyse dataHow to get it and install?Or use NZGrapher NZ Grapher server address_RC (only can be accessed within RC network) 
An activity from Census At School: Kiwi Kaper

Achievement Standard clarification91264 Use statistical methods to make an inferenceUpdated August 2015. This document has been updated to address issues that have arisen from moderation. ProblemThe investigative question that is posed must involve a comparison and needs to include the variable, the population groups being compared,r the population parameter the inference will be about and the direction of the comparison. A suitable question would be Is the median height of NZ year 12 boys greater than the median height of NZ year 12 girls? Plan and DataThe investigation involves selecting random samples from the population groups and using information from the samples to make an inference about the population groups. Students must demonstrate an understanding of the population from which the sample will be taken. AnalysisThe informal confidence intervals for the population medians must be used to answer the investigative comparison question. At Merit and above the informal confidence intervals must be interpreted in context. For example, ‘I am pretty sure that the median height for NZ year 12 boys is somewhere between xxx and yyy’. The discussion of the sample distributions must be about the distributions of the variables, for example the heights of NZ year 12 boys and NZ year 12 girls, and needs to include numerical values and associated units. The basis of the discussion will be the visual evidence, so students need to be looking at the sample distributions and discussing distinctive features of the distributions. Sample statistics could be used to justify the observations made from the visual interpretation. ConclusionStudents must make an inference, which will be a conclusion about the population medians based on the samples taken from the population. The conclusion must be consistent with the analysis. It will answer the posed investigative question and will involve making a call about the population medians. The informal confidence intervals need be used to make an inference about the population medians. If there is no overlap in the informal confidence intervals, an appropriate inference is that the population median for ‘A’ is greater than/less than the population median for ‘B’. If there is an overlap in the intervals there is not enough evidence to make a call that the population median for ‘A’ is greater than/less than the population median for ‘B’. An understanding relating to sampling variability and variability of estimates must be evident. Another sample could give different statistics and different informal confidence intervals. For the inference, the informal confidence intervals are still likely to capture the population parameter. 
Posing a statistical question is an important skill which should be learnt in depth. Scroll up….. 

Plan 
Data 
AnalyseInterpret Box Plot 
Making a statistical ‘call’ (inference)

Sampling variations and developing the concept of confidence interval 
Informal Confidence interval (outcome of sampling variability)
Short clip from Chris Wild's video on Sampling variability 
Footprints can be imagined showing the movements of the ‘medians’. Medians of different samples. 
Uncertainty of our measurement = gives rise to the variability of measurement outcomes = confidence interval = margin of ‘error’ For example, your teacher says, ‘that measurement is 1.67 m’. Do you think it is exactly 1.67m? Answer is ‘NO’. Better statement would be , ‘that measurement is ‘close’ to 1.67m. 
Analysis: 
Analysis: 
Analysis: 
Analysis: 
Inference: 
Conclusion (answer to your posed question) 
Animation clips on Sampling variability with sample size=10 & 100Sampling variability statement: ( you must write)Note:(During the final report writing students tend to forget to write about the sampling variability) 
NZ Grapher: instruction 
Other important site links for information 
PSSS and OSEM (describing distribution of data)
