The reader is introduced to the maths library and several mathematical operators including addition, subtraction, multiplication, division, whole number division, finding the remainders, using pi and calculating the square root of a number. They also look at the difference between integers and floating point numbers and use rounding to display number to a set number of decimal places as they complete the eight challenges in this chapter.

SQL databases are widely used in industry and this final chapter of Part I teaches the reader how to link to an SQL database using SQLite 3. It explains what a relational database is, the use of primary keys and it shows how to create a table, import the data into Python and run selection queries. The seven challenges allow the reader to put these new skills into practice.

In many programming languages subprograms incorporate both functions and procedures, however, in Python these are combined into a simple single subprogram and it is not necessary to define the type. The reader is shown how to call subprograms, return values from a subprogram and use variables in subprograms. They complete six challenges and use menus to make the programs user-friendly.

Tkinter allows the reader to create a graphical user interface (GUI) that incorporates windows, buttons, text boxes and lists boxes. The nine challenges allow the reader to experiment with layouts they like to create a more user-friendly interface.

The user starts to experiment and use the example code to write simple coded solutions using Python. They learn how to incorporate input and print statements and combine strings and variables to produce meaningful programs. There are eleven challenges to complete and the answers are provided for each challenge given.

In this chunky challenge the reader makes an on-screen version of the board game “Mastermind”. The computer will automatically generate four colours from a list of possible colours, which the user must guess correctly to win the game. The skills they need include: input and display data, lists, random choice from a list, if statements, loops (while and for) and subprograms.

Drawing shapes and patterns with the Python turtle allows readers to practise using loops and helps them learn computational thinking skills where they have to spot repeating patterns. The nine challenges allow them to put these skills into practice.

Building on their knowledge of lists, readers are shown how to create and amend two-dimensional lists and dictionaries. They complete nine challenges to practise creating two-dimensional lists and dictionaries, selecting specific rows, columns or individual values, adding new data or altering existing data.

Saving data to an external file is an essential skill allowing programs to have multiple practical real-world uses. This chapter shows the reader how to save data to text files as well as import data from text files into Python so it can be manipulated. By working through the six challenges the reader learns how to implement these important new skills.

Readers learn about numeric arrays and data types such as integer, long, floating-point and double. They are shown how to import the array library, define an array in Python, append data, extend and combine arrays, remove items from an array along with sort and reverse arrays. They complete eight challenges to explore using numeric arrays in Python.

The reader is shown more examples about how to use and manipulate strings. They experiment with concatenation, finding the length of a string, displaying part of a string, changing the case to either upper or lower case as they complete seven engaging challenges.

The t-test is a work horse of a lot of statistical analysis in HCI. There are a lot of myths about how robust it is to deviations from normality and other assumptions. However, when faced with practical data, particularly those coming from usability studies, the claims of robustness do not stand up. This chapter reevaluates the t-test as a test for an effect on the location of data. This leads to considering robust measures of location, such as trimmed or Winsorized means and associated Yuen–Welch test as a robust alternative to the traditional t-test.