## Free Statistics

of Irreproducible Research!

Author's title
Author*The author of this computation has been verified*
R Software Modulerwasp_STARS_Bullying_Study_alt.wasp
Title produced by softwareChi-Square Test
Date of computationWed, 01 Sep 2010 14:55:43 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Sep/01/t1283352921caywyb9phhdy9lo.htm/, Retrieved Tue, 21 Mar 2023 06:58:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=79510, Retrieved Tue, 21 Mar 2023 06:58:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact215
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Chi-Square Test] [] [2010-09-01 14:55:43] [c92f5ba3a07bc76f136819ea4bf02652] [Current]
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Dataseries X:
b	77	182	77	180
g	58	161	51	159
g	53	161	54	158
b	68	177	70	175
g	59	157	59	155
b	76	170	76	165
b	76	167	77	165
b	69	186	73	180
b	71	178	71	175
b	65	171	64	170
b	70	175	75	174
g	166	57	56	163
g	51	161	52	158
g	64	168	64	165
g	52	163	57	160
g	65	166	66	165
b	92	187	101	185
g	62	168	62	165
b	76	197	75	200
g	61	175	61	171
b	119	180	124	178
g	61	170	61	170
b	65	175	66	173
b	66	173	70	170
g	54	171	59	168
g	50	166	50	165
g	63	169	61	168
g	58	166	60	160
g	39	157	41	153
b	101	183	100	180
g	71	166	71	165
b	75	178	73	175
b	79	173	76	173
g	52	164	52	161
g	68	169	63	170
b	64	176	65	175
g	56	166	54	165
b	69	174	69	171
b	88	178	86	175
b	65	187	67	188
g	54	164	53	160
b	80	178	80	178
g	63	163	59	159
b	78	183	80	180
b	85	179	82	175
g	54	160	55	158
b	73	180	NA	NA
g	49	161	NA	NA
b	54	174	56	173
g	75	162	75	158
b	82	182	85	183
g	56	165	57	163
b	74	169	73	170
b	102	185	107	185
b	64	177	NA	NA
b	65	176	64	172
g	66	170	65	NA
b	73	183	74	180
b	75	172	70	169
b	57	173	58	170
b	68	165	69	165
b	71	177	71	170
b	71	180	76	175
g	78	173	75	169
b	97	189	98	185
g	60	162	59	160
g	64	165	63	163
g	64	164	62	161
g	52	158	51	155
b	80	178	76	175
g	62	175	61	171
b	66	173	66	175
g	55	165	54	163
g	56	163	57	159
g	50	166	50	161
g	50	171	NA	NA
g	50	160	55	150
g	63	160	64	158
b	69	182	70	180
b	69	183	70	183
g	61	165	60	163
b	55	168	56	170
g	53	169	52	175
g	60	167	55	163
g	56	170	56	170
b	59	182	61	183
b	62	178	66	175
g	53	165	53	165
g	57	163	59	160
g	57	162	56	160
b	70	173	68	170
g	56	161	56	161
b	84	184	86	183
g	69	180	71	180
b	88	189	87	185
g	56	165	57	160
b	103	185	101	182
g	50	169	50	165
g	52	159	52	153
g	55	155	NA	154
g	55	164	55	163
b	63	178	63	175
g	47	163	47	160
g	45	163	45	160
g	62	175	63	173
g	53	164	51	160
g	52	152	51	150
g	57	167	55	164
g	64	166	64	165
g	59	166	55	163
b	84	183	90	183
b	79	179	79	171
g	55	174	57	171
b	67	179	67	179
g	76	167	77	165
g	62	168	62	163
b	83	184	83	181
b	96	184	94	183
b	75	169	76	165
b	65	178	66	178
b	78	178	77	175
b	69	167	73	165
g	68	178	68	175
g	55	165	55	163
b	67	179	NA	NA
b	52	169	56	NA
g	47	153	NA	154
g	45	157	45	153
g	68	171	68	169
g	44	157	44	155
g	62	166	61	163
b	87	185	89	185
g	56	160	53	158
g	50	148	47	148
b	83	177	84	175
g	53	162	53	160
g	64	172	62	168
g	62	167	NA	NA
b	90	188	91	185
b	85	191	83	188
b	66	175	68	175
g	52	163	53	160
g	53	165	55	163
g	54	176	55	176
g	64	171	66	171
g	55	160	55	155
g	55	165	55	165
g	59	157	55	158
g	70	173	67	170
b	88	184	86	183
g	57	168	58	165
g	47	150	45	152
g	55	162	NA	NA
g	48	163	44	160
b	54	169	58	165
b	69	172	68	174
g	59	170	NA	NA
g	58	169	NA	NA
g	57	167	56	165
g	51	163	50	160
g	54	161	54	160
g	53	162	52	158
g	59	172	58	171
b	56	163	58	161
g	59	159	59	155
g	63	170	62	168
g	66	166	66	165
b	96	191	95	188
g	53	158	50	155
b	76	169	75	165
g	54	163	NA	NA
b	61	170	61	170
b	82	176	NA	NA
b	62	168	64	168
b	71	178	68	178
F	60	174	NA	NA
b	66	170	67	165
b	81	178	82	175
b	68	174	68	173
b	80	176	78	175
F	43	154	NA	NA
b	82	181	NA	NA
F	63	165	59	160
b	70	173	70	173
g	56	162	56	160
g	60	172	55	168
g	58	169	54	166
b	76	183	75	180
g	50	158	49	155
b	88	185	93	188
g	89	173	86	173
g	59	164	59	165
g	51	156	51	158
g	62	164	61	161
b	74	175	71	175
b	83	180	80	180
b	81	175	NA	NA
b	90	181	91	178
b	79	177	81	178


 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'George Udny Yule' @ 72.249.76.132 R Engine error message Error in as.vector(data) : object 'b' not found Calls: array -> as.vector Execution halted 

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
R Engine error message & Error in as.vector(data) : object 'b' not found
Calls: array -> as.vector
Execution halted
\tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79510&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
Calls: array -> as.vector
Execution halted
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79510&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79510&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'George Udny Yule' @ 72.249.76.132 R Engine error message Error in as.vector(data) : object 'b' not found Calls: array -> as.vector Execution halted 

Parameters (Session):
par1 = 3 ; par2 = 2 ; par4 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 3 ; par3 = Pearson Chi-Square ;
R code (references can be found in the software module):
cat1 <- as.numeric(par1) #cat2<- as.numeric(par2) #simulate.p.value=FALSEif (par3 == 'Exact Pearson Chi Square by simulation') simulate.p.value=TRUEx <- t(x)(z <- array(unlist(x),dim=c(length(x[,1]),length(x[1,]))))(table1 <- table(z[,cat1],z[,cat2]))(V1<-dimnames(y)[[1]][cat1])(V2<-dimnames(y)[[1]][cat2])load(file='createtable')a<-table.start()a<-table.row.start(a)a<-table.element(a,'Tabulation of Results',ncol(table1)+1,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a, ' ', 1,TRUE)for(nc in 1:ncol(table1)){a<-table.element(a, colnames(table1)[nc], 1, TRUE)}a<-table.row.end(a)for(nr in 1:nrow(table1) ){a<-table.element(a, rownames(table1)[nr], 1, TRUE)for(nc in 1:ncol(table1) ){a<-table.element(a, table1[nr, nc], 1, FALSE)}a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable.tab')(cst<-chisq.test(table1, simulate.p.value=simulate.p.value) )a<-table.start()a<-table.row.start(a)a<-table.element(a,'Tabulation of Expected Results',ncol(table1)+1,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a, ' ', 1,TRUE)for(nc in 1:ncol(table1)){a<-table.element(a, colnames(table1)[nc], 1, TRUE)}a<-table.row.end(a)for(nr in 1:nrow(table1) ){a<-table.element(a, rownames(table1)[nr], 1, TRUE)for(nc in 1:ncol(table1) ){a<-table.element(a, round(cst$expected[nr, nc], digits=2), 1, FALSE)}a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable1.tab')a<-table.start()a<-table.row.start(a)a<-table.element(a,'Statistical Results',2,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a, cst$method, 2,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a, 'Chi Square Statistic', 1, TRUE)a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE)a<-table.row.end(a)if(!simulate.p.value){a<-table.row.start(a)a<-table.element(a, 'Degrees of Freedom', 1, TRUE)a<-table.element(a, cst$parameter, 1,FALSE)a<-table.row.end(a)}a<-table.row.start(a)a<-table.element(a, 'P value', 1, TRUE)a<-table.element(a, round(cst\$p.value, digits=2), 1,FALSE)a<-table.row.end(a)a<-table.end(a)table.save(a,file='mytable2.tab')