iNZight Tips & Tricks (available from Nayland.school.nz)

Ordering dataData IN/OUT as per normal, then right click on the column heading to:'Apply a function to a column' sort by column decreasing or increasing, or 'rename the column'

Filtering data - 'select cases'There are several options are available here:Remember if you stuff it up you can always 'filter data' - 'restore data set'

'Levels of a categorical variable'Good for situations where there are several groups in a category and you only want 2 groups to investigate.

'Numerical condition'Good for situations where there you want to remove some data such as outliers or for some reason (eg under age drinkers) from a numerical column.Remember you select data you want to keep.

'Row number'Good for removing specific data or outliers. eg. Order the data by a column, view the data and note the row number, then filter the data by that row number to remove the outlier.Good for testing the robustness of time series model

Data displayDrag Variable 1 and Variable 2 (usually one numerical and one categorical)Add in 'subset by' then move the slider bar to quickly flick between the different combinations of the category and subgroup (subset)Great to do when initially investigating data sets. "I wonder if..."

http://maths.nayland.school.nz/

Add to plotRemember you can always 'remove additions' to return

to basic plot

Code more variables adds colouring to the dot plot to show

another variable.

Also great to do when initially investigating data sets. "I wonder if..."

Change plot appearance to reduce size of dot plot points reduces the 'stacking tilt' which we sometimes see in the dot plot.

Manipulate VariablesSome great options here. Explore.Remember if it all goes wrong, just re-import your data again

'Convert to categorical'By default iNZight takes numerical data to be numerical, not categorical.If you have data that has categories identified numerically you can convert them to 'text'.This will be added to the data beside the numerical column (good idea to re-name it)

http://maths.nayland.school.nz/

'Transform variables'Useful when we are modelling, Bivariate or looking at multiplicative models in time series.

‘Collapse levels'When you want to combine groups within a category.eg Qualifications: we want to group ‘degree’ & ‘vocational’ together, and compare with ‘none’ & ‘school’ combined together.How?Select variable, select groups to combine, ‘collapse, then repeat for other group, ‘collapse’ then ‘all done’Another column will be added into the data set with the new groups. Useful for inference when we compare only two groups.

‘Re-Name levels'When you want to re-name groups (levels) within a category.Select your variable, then rename.Good if you have converted numerical to categorical and want to name groups more appropriately.

'Reshape the data'If you want to reorganise your data set without having to use Excel.

'Combine Categorical Variables'This is when you want to combine several categories together.

'Create New Variables'Good for excellence in time series eg spending per person.Be very careful you get the variable names correctly typed.The best way is to ‘click and drag’ the variables into the ‘new variable’ box (from the 'view variables' list - not the 'data view set'

http://maths.nayland.school.nz/

'Form Class Intervals'Handy when you want to create groups from a numerical column. Lots of choice over number of intervals and the method.eg. splitting into age groups.

'Re-name Variables'Pretty obvious what this does.

'Standardise Variables'This converts a variable into a standard normal distribution version. Good for noting how many standard deviations the data may be from the mean, and what possible outliers there may be.

Normal Variable

Standardised Variable

Link to census at school word doc on VIT's

!!!! NOTE !!!!If you have manipulated your data (as above) and then want to run one of the iNZight VIT modules you must export your data, ie save it, then re upload it into the VIT.Otherwise your changes will be lost.

This is straight forward to do, just remember where you saved it ready for the VIT

iNZight Inference & BootstrappingMost of this is covered in the AS3.10 Inference pages. Analysing a sample: Box plots, and sample statistics, bootstrapping, randomisation

iNZight Time Series

http://maths.nayland.school.nz/

Link to AS3.8 Time Series pages, Getting Started, Importing Data Trend, Decomposing, Recomposing, Seasonal Effects, Predictions, Comparing multiple variables, Combining variables, Robustness, Summary

http://maths.nayland.school.nz/