Statistical insight (Link statistics to research is the key to showing your statistical insight.)

further depth of thinking demonstrated with clear contextual links

greater understanding of sampling variability (explain how bootstrapping works)

understanding of coverage of the confidence interval(s)

no errors demonstrated in understandings, interpretation or explanation of findings/data.

http://2013stats.wikispaces.com/3.10+Merit shows how you could end up with Merit.
Please note the standard of excellence will increase, as you now have some experience with this type of assessment.

Research into background of context to give purpose to the investigation

Comparison question includes:

Variable that is being examined (eg. height in cm)

Groups that are being compared (eg. Year 11 boys and Year 11 girls)

Population that inferences are being made about (eg. New Zealand Year 11 boys and New Zealand Year 11 girls)

Population Parameter / Sample Statistic (eg. DIFFERENCE in median and mean heights between boys and girls. Choose the best measure and compare the two)

Prediction of what students expect to see in their analysis and why

Note: you are using a sample statistic to estimate a population parameter (median)

Plan

as per 3.8 and 3.9

Data

State the source and explain the units etc

Analysis

iNZight graphs (Code extra variables, perhaps remove outliers IF they are ERRORS!)

Comparative statements will include discussion about the difference in medians AND means

Justify your choice of mean or median, do BOTH and compare.

Comparative statements will make contextual links back to the population and initial research (the “so what?” factor)

Randomisation could be used as another way of checking there is a difference.

Conclusion

Interpretation of formal confidence interval

Sample TO=> population link strong

Some level of uncertainty evident (“pretty sure”)

Population parameter identified

Correct call, with justification

Should reflect investigative question

Call based on whether zero is contained within the interval or not - Direction of evidence (if zero outside of interval)

Linking back to the context and using initial research to help explain what this means (the “so what?” factor)

## Excellence Skills: All of the below are included.

- Statistical insight (Link statistics to research is the key to showing your statistical insight.)
- further depth of thinking demonstrated with clear contextual links
- greater understanding of sampling variability (explain how bootstrapping works)
- understanding of coverage of the confidence interval(s)
- no errors demonstrated in understandings, interpretation or explanation of findings/data.

http://2013stats.wikispaces.com/3.10+Merit shows how you could end up with Merit.Please note the standard of excellence will increase, as you now have some experience with this type of assessment.

## Problem

Comparison question includes:Variablethat is being examined (eg. height in cm)Groupsthat are being compared (eg. Year 11 boys and Year 11 girls)Populationthat inferences are being made about (eg. New Zealand Year 11 boys and New Zealand Year 11 girls)Population Parameter / Sample Statistic(eg. DIFFERENCE in median and mean heights between boys and girls. Choose the best measure and compare the two)Predictionof what students expect to see in their analysis and why## Plan

## Data

## Analysis

## Conclusion

http://learnandteachstatistics.wordpress.com/2013/04/29/median/

## Some extra activities for Excellence Students to develop their understanding

The blog about the median from Dr. Nic suggests this video...

http://learnandteachstatistics.wordpress.com/2013/04/29/median/

Language: http://www.stats.gla.ac.uk/steps/glossary/basic_definitions.html#param

## Marking a Students Work

The above is for Year 10: What we are up against is that students do not remember doing it in Year 10!

The table is from: http://new.censusatschool.org.nz/wp-content/uploads/2013/02/TSG12_Arnold.pdf

Just a random note: If the Median and Mean are different then the data is skewed.