Question

ID	AREA	GENDER	BW	WDI	TDI	RISK
101	2	2	78	4	14	4,58E-04
102	2	2	65	6	10	9,23E-06
201	1	1	58	6	10	2,07E-04
202	1	2	67	10	22	4,93E-04
301	2	1	47	6	16	4,09E-05
302	2	2	112	15	15	8,04E-06
401	2	1	75	0	3	1,80E-05
403	2	1	70	0	8	4,11E-05
501	1	1	59	5	10	6,36E-04
502	1	1	68	2	4	4,76E-04
503	1	1	48	4	9	1,18E-03
510	1	2	84	7	10	1,64E-03
511	1	1	48	0	2	3,66E-04
602	1	1	50	2	6	1,08E-05
603	1	1	52	3	13	4,50E-05
604	1	2	38	0	6	3,79E-05
605	1	2	75	0	5	3,40E-04
607	1	2	85	0	3	6,35E-06
608	1	1	55	2	7	1,91E-05
609	1	2	79	3	18	3,42E-05
801	1	1	63	1	3	2,14E-04
802	1	1	68	0	8	1,04E-03
901	2	2	64	10	20	2,34E-04
1001	2	2	85	4	11	2,76E-04
1002	2	1	55	0	4	1,16E-04
1101	1	1	58	0	5	1,29E-05
1102	1	2	72	0	13	2,71E-05
1304	1	1	52	4	8	1,48E-03
1306	1	2	80	2	6	7,88E-04
1307	1	1	70	0	3	5,91E-04
1309	1	1	68	7	14	2,59E-03
1310	1	2	70	4	8	3,09E-05
1313	1	2	65	4	7	1,29E-03
1401	2	1	54	0	2	1,44E-05
1402	2	1	63	0	5	3,10E-05

Test if cancer risks statistically differ between areas (urban & non-urban) and genders (females and males). urban : 1 nonurban :2 female :1 male:2

Answer 1

Save the excel file in your working directory

Using R

risk <- read.csv("risk.csv",header=TRUE)
risk$RISK <- as.numeric(risk$RISK)

## for comparison between areas
t.test(risk$RISK[risk$AREA==1], risk$RISK[risk$AREA==2] )

Welch Two Sample t-test

data:  risk$RISK[risk$AREA == 1] and risk$RISK[risk$AREA == 2]
t = -0.59192, df = 18.991, p-value = 0.5609
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -10.223452   5.715876
sample estimates:
mean of x mean of y 
 17.29167  19.54545 

p-value = 0.5609 > 0.05

hence we fail to reject the null hypothesis

we conclude that there is not significant difference between area.

## for gender

t.test(risk$RISK[risk$GENDER==1], risk$RISK[risk$GENDER==2] )

        Welch Two Sample t-test

data:  risk$RISK[risk$GENDER == 1] and risk$RISK[risk$GENDER == 2]
t = -2.2054, df = 31.596, p-value = 0.03483
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -13.9175761  -0.5490906
sample estimates:
mean of x mean of y 
 14.90000  22.13333 

P-VALUE = 0.0348 < 0.05

hence we reject the null hypothesis

we conclude that there is significant difference between genders