ILBoys Data MothersAge Weight 2529 3005 2529 3686 2529 3714

ILBoys - Data

MothersAge	Weight
25-29	3005
25-29	3686
25-29	3714
20-24	2807
25-29	4054
15-19	3884
25-29	3005
20-24	2920
25-29	3236
20-24	3345
20-24	2948
25-29	3345
25-29	3997
20-24	3025
20-24	4026
20-24	4423
20-24	3487
20-24	3232
15-19	3005
15-19	3300
20-24	3575
25-29	3742
15-19	3232
20-24	3572
25-29	4167
20-24	2870
20-24	3374
15-19	3515
20-24	3232
20-24	3600
20-24	3025
25-29	4139
20-24	3232
25-29	3345
20-24	3837
15-19	3430
25-29	3544
15-19	4030
20-24	3600
20-24	3770
20-24	4394
25-29	4253
25-29	3374
25-29	3487
15-19	3629
25-29	3289
25-29	3535
15-19	3680
20-24	3090
25-29	3997
25-29	2892
15-19	2552
25-29	3487
20-24	2410
20-24	2920
20-24	3260
25-29	3260
25-29	3657
25-29	3515
20-24	2438
25-29	3856
15-19	3317
20-24	3165
20-24	3572
15-19	3884
20-24	3544
20-24	3608
15-19	3487
25-29	4564
25-29	4054
20-24	2336
20-24	3119
15-19	2778
20-24	3741
20-24	3119
15-19	3317
20-24	3260
20-24	3742
25-29	3629
20-24	3033
25-29	3390
15-19	3374
25-29	4335
20-24	3090
25-29	3520
20-24	3657
20-24	3920
25-29	3430
20-24	3742
15-19	2878
20-24	3912
25-29	4082
25-29	3119
15-19	3204
20-24	3430
20-24	2975
15-19	2990
25-29	4200
20-24	3656
20-24	2948
20-24	2948
20-24	3459
25-29	3657
25-29	3930
25-29	3232
25-29	2892
15-19	2580
25-29	3505
20-24	3232
25-29	3345
20-24	3430
20-24	3657
15-19	3459
15-19	3657
25-29	3058
25-29	3771
25-29	3317
25-29	3317
20-24	3033
20-24	3090
15-19	3827
25-29	3175
25-29	3289
20-24	3771
25-29	3317
15-19	2792
20-24	3130
25-29	3175
20-24	3033
25-29	3175
25-29	3459
25-29	3997
20-24	3260
15-19	2955
25-29	3232
25-29	3289
20-24	3175
25-29	3313
20-24	3771
15-19	2000
20-24	3255
25-29	2920
20-24	3572
25-29	3232
15-19	3147
25-29	4026
20-24	2977
25-29	3380
25-29	3033
20-24	3459
25-29	3750
20-24	3600
15-19	3374
25-29	3375
25-29	2778
25-29	3686
15-19	3430
25-29	3714
25-29	4253
15-19	2540
25-29	3827
20-24	3544
25-29	3250
25-29	3317
20-24	3827
20-24	3912
25-29	3289
25-29	4204
20-24	3289
15-19	3204
15-19	3033
20-24	3062
25-29	2807
20-24	3572
20-24	3515
20-24	3487
20-24	3289
25-29	4338
20-24	3250
20-24	3515
25-29	3289
20-24	3430
20-24	3747
25-29	3714
20-24	4005
25-29	4082
25-29	3686
25-29	3515
20-24	3260
25-29	3629
25-29	3296
20-24	3147
15-19	2863
25-29	3175
25-29	4139
25-29	3062
20-24	2523
25-29	3771
25-29	3714
15-19	2905
15-19	3997
25-29	3090
25-29	3575
20-24	3941
25-29	2975
25-29	2977
15-19	3119
25-29	3175
25-29	4423
25-29	4590
25-29	3430
25-29	3657
25-29	3657
25-29	2778
20-24	3515
20-24	2655
15-19	3119
25-29	3340
15-19	2863
15-19	3232
25-29	3317
25-29	3799
20-24	3941
15-19	3175
20-24	3005
15-19	2892
25-29	3374
25-29	3374
20-24	4139
25-29	3487
25-29	3260
20-24	3090
15-19	2920
25-29	3204
15-19	3515
25-29	3260
25-29	3970
20-24	3430
25-29	3969
15-19	3033
20-24	3107

Consider the following example. Suppose we are interested in determining if the age of the mother affects the birth weight of a baby. A random sample of boys born in Illinois in 2004 to mothers in the age ranges of 15-19, 20-24 and 25-29 years is obtained and their birth weights (in grams) are recorded in the file ILBoys. The following R code performs a one-way ANOVA using a permutation approach to determine test for a significant difference in mean birth weight between the age ranges of the mothers. On a slower computer, you may want to change B to a smaller number, say B = 10^4 - 1. Explain the permutation approach to one-way ANOVA in R code provided in the above example.

Solution

historically in a few working systems, an extra step was required after compilation - that of resolving the relative region of commands and statistics when a couple of item module become to be run at the same time and they cross-referred to every other\'s coaching sequences or statistics. This method become every so often known as linkage editing and the output known as a load module.