As in the independent t-test datasheet, the data must be coded with a group variable. The data that will be used for the first part of this section is from Table 11.2, of Howell. There are 5 groups of 10 observations each - resulting in a total of 50 observations. The group variable will be coded from 1 to 5, for each group. Take a look at the following to get an idea of the coding.

Groups | Scores |

1 | 9 |

1 | 8 |

1 | 6 |

... | ... |

1 | 7 |

2 | 7 |

2 | 9 |

2 | 6 |

... | ... |

... | ... |

... | ... |

5 | 10 |

5 | 19 |

... | ... |

5 | 11 |

The coding scheme uniquely identifies the origin of each observation.

To complete the analysis,

- Select
**[Statistics => Compare Means => One-Way ANOVA...]**to launch the controlling dialog box. - Select and move "Scores" into the
**Dependent list:** - Select and move "Groups" into the
**Factor:**list - Click on
**[OK]**The preceeding is a complete spefication of the design for this oneway anova. The simple presentation of the results, as taken from the output window, will look like the following,

The analysis that was just performed provides minimal details
with regard to the data. If you take a look at the controlling
dialog box, you will find 3 additional buttons on the bottom
half - **[Contrasts...]**, **[Post Hoc..]**, and
**[Options...]**.

Selecting **[Options...]** you will find,

If **Descriptive** is enabled, then the descriptive statistics
for each condition will be generated. Making **Homogeneity-of-variance**
active forces a Levene's test on the data. The statistics from both
of these analyses will be reproduced in the output window.

Selecting **[Post Hoc]** will launch the following dialog box,

One can active one or multiple post hoc tests to be performed. The
results will then be placed in the output window. For example,
performing a **R-E-G-W F** statistic on the current data would
produce the following,

Finally, one can use the **[Contrasts...]** option to
specify linear and/or orthogonal sets of contrasts. One can
also perform trend analysis via this option. For example, we may
wish to contrast the third condition with the fifth,

For each contrast, the coefficients must be entered individually,
and in order. Once can also enter multiple contrasts, by using the
**[Next]** present in the dialog box. The result for the
example contrast would look like the following,

Further, one can use the **Polynomial** option to test
whether a specific trend in the data exists.

Factorial designs will be covered in the next section.