In TI nspire CX, the application Lists & Spreadsheet provided a convenient Excel list interface for data input.

The data can also be named by columns and recalled from the Calculator application. Statistical functions can then be applied. Using a sample from the classical TI-89 statistics guide book on determining the interaction between two factors using 2-way ANOVA, the same output is obtained from the TI nspire CX.

In R, data are usually imported from CSV file using read.csv() command. There are also other supported formats including SPSS and Excel. For more casual data entry that command line input is suffice, raw data are usually stored into list variable using c() command. Working with ANOVA for data entry in this way is not as straightforward because dimension is required for the analysis on data stored in the list variable.

To accomplish the ANOVA, factor data types are used in conjunction with list variable. The below is the same TI example completed in R. Firstly we define the list variable in a fashion of the order by club (c1 = driver, c2 = five iron) then brand (b1-, b2-, b3-, with the last digit as the sample number), i.e.

{c1,b1-1}; {c1,b1-2}; {c1,b1-3}; {c1,b1-4};

{c1,b2-1}; {c1,b2-2};…

{c2,b1-1}; {c2,b1-2};…

Two Factor variables are then created, one for club (with twelve 1’s followed by twelve 2’s), and another for brand (1 to 3 each repeating four times for each sample, and then completed by another identical sequence).

These two Factor variables essentially represent the position (or index in array’s term) of the nth data value in respect of the factor it belongs to, and can be better visualized in the following table.

Finally, the 2-way ANOVA can be performed using the following commands.

Interaction plot in R.

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