HairEyeColor package:datasets R Documentation _H_a_i_r _a_n_d _E_y_e _C_o_l_o_r _o_f _S_t_a_t_i_s_t_i_c_s _S_t_u_d_e_n_t_s _D_e_s_c_r_i_p_t_i_o_n: Distribution of hair and eye color and sex in 592 statistics students. _U_s_a_g_e: HairEyeColor _F_o_r_m_a_t: A 3-dimensional array resulting from cross-tabulating 592 observations on 3 variables. The variables and their levels are as follows: No Name Levels 1 Hair Black, Brown, Red, Blond 2 Eye Brown, Blue, Hazel, Green 3 Sex Male, Female _D_e_t_a_i_l_s: The Hair x Eye table comes rom a survey of students at the University of Delaware reported by Snee (1974). The split by 'Sex' was added by Friendly (1992a) for didactic purposes. This data set is useful for illustrating various techniques for the analysis of contingency tables, such as the standard chi-squared test or, more generally, log-linear modelling, and graphical methods such as mosaic plots, sieve diagrams or association plots. _S_o_u_r_c_e: Snee (1974) gives the two-way table aggregated over 'Sex'. The Sex split of the 'Brown hair, Brown eye' cell was changed in R 2.6.0 to agree with that used by Friendly (2000). _R_e_f_e_r_e_n_c_e_s: Snee, R. D. (1974) Graphical display of two-way contingency tables. _The American Statistician_, *28*, 9-12. Friendly, M. (1992a) Graphical methods for categorical data. _SAS User Group International Conference Proceedings_, *17*, 190-200. Friendly, M. (1992b) Mosaic displays for loglinear models. _Proceedings of the Statistical Graphics Section_, American Statistical Association, pp. 61-68. Friendly, M. (2000) _Visualizing Categorical Data._ SAS Institute, ISBN 1-58025-660-0. _S_e_e _A_l_s_o: 'chisq.test', 'loglin', 'mosaicplot' _E_x_a_m_p_l_e_s: require(graphics) ## Full mosaic mosaicplot(HairEyeColor) ## Aggregate over sex (as in Snee's original data) x <- apply(HairEyeColor, c(1, 2), sum) x mosaicplot(x, main = "Relation between hair and eye color")