assingment computer literacy R
COMPUTER LITERACY
R ASSIGNMENT
DR. NORHAIZA AHMAD
MEMBERS’ NAMES:
- AISYAH AMIRAH BINTI AHMAD SENUSI (A11SC0273)
- FARZANA IZZAH BINTI ADNAN (A11SC0277)
- FARAH HANI BINTI ABD. GHANI (A11SC0276)
Question 1
(a) > x<-function(x){sqrt(4-x^2)}
> integrate(x,lower=2,upper=-2)
-6.283185 with absolute error < 4e-09
(b) > x<-function(x){1/(3+5*(sin(x)))}
> integrate(x,lower=0,upper=pi/2)
0.2746531 with absolute error < 6.5e-13
Question 2
(a) > derv.exp<-expression(x^2)
> (D.sc<-D(derv.exp,"x"))
2 * x
(b) > derv.exp<-expression((exp(-x))/(sinh(x+x)))
> (D.sc<-D(derv.exp,"x"))
-(exp(-x)/(sinh(x + x)) + (exp(-x)) * (cosh(x + x) * (1 + 1))/(sinh(x +
x))^2)
Question 3
> babies<-read.table("babies.q3",header=T,as.is=T)
> babies[1:5,]
id pluralty outcome date gestation sex wt parity race age ed ht wt1 drace
1 15 5 1 1411 284 1 120 1 8 27 5 62 100 8
2 20 5 1 1499 282 1 113 2 0 33 5 64 135 0
3 58 5 1 1576 279 1 128 1 0 28 2 64 115 5
4 61 5 1 1504 999 1 123 2 0 36 5 69 190 3
5 72 5 1 1425 282 1 108 1 0 23 5 67 125 0
dage ded dht dwt marital inc smoke time number
1 31 5 65 110 1 1 0 0 0
2 38 5 70 148 1 4 0 0 0
3 32 1 99 999 1 2 1 1 1
4 43 4 68 197 1 8 3 5 5
5 24 5 99 999 1 1 1 1 5
Question 4
> x<-rnorm(100,0,1)
> x
[1] 0.66426518 1.32463798 0.18390495 -0.50739395 -0.32761690 -0.94710933
[7] -1.60879575 0.40648129 -0.42158523 -0.81931179 0.38012498 0.10348897
[13] 1.05122055 0.85748798 -1.45021850 -0.77088122 2.39590308 0.14131842
[19] -0.65599891 -0.98453112 0.18785770 -2.11442231 -0.41971988 -0.27564302
[25] -0.30330891 0.89596651 0.62050534 -1.20238396 -0.87387674 -0.28649259
[31] -0.46161906 1.01095503 0.11949346 2.77057480 -1.24946221 0.60218937
[37] 2.16856132 0.75450506 0.34867124 -0.06279886 0.16349332 -0.74800316
[43] 1.03793095 -1.11999053 -0.66736287 -0.89460342 -0.97898667 0.20463144
[49] 0.23319416 -1.38966466 0.08877128 -1.21221526 -1.61306333 -1.58689705
[55] 0.61353762 -0.47469510 -0.57286766 -1.27037462 -1.10790503 -0.15405104
[61] 0.49222820 -0.04227585 0.72528947 0.22534818 0.87954661 0.02249063
[67] -0.89100850 0.68539877 -0.06833181 -0.92120277 -0.68517348 1.11299754
[73] -0.80420763 -1.27880703 0.49046840 -0.19224708 -1.25453419 1.12085443
[79] 1.00592337 -1.00369928 0.98571454 1.34093906 2.60182568 -0.14442275
[85] 0.07065799 -0.68135065 0.12812765 2.36910380 -0.31105465 0.13709190
[91] 0.14547627 0.10480672 -1.69649405 -1.11452572 -0.55567620 -0.24481844
[97] -0.08232927 -0.14956652 -0.61587933 0.81028382
> mean(x)
[1] -0.07487211
> sd(x)
[1] 0.9780099
> y<-x[x>1.96]
> y
[1] 2.395903 2.770575 2.168561 2.601826 2.369104
> round(y,3)
[1] 2.396 2.771 2.169 2.602 2.369
Question 5
> x<-rgamma(100,1,0.5)
> x
[1] 4.260310039 5.161828702 0.178508625 0.794944991 6.156563019
[6] 0.065213129 8.166430557 1.058992473 0.662019672 1.917848315
[11] 0.067234901 3.985343463 5.607803287 3.655106952 6.029411885
[16] 1.363434974 5.203354335 0.170016154 0.468475217 1.802581309
[21] 4.104034788 4.900111895 0.271174448 2.034655359 3.761122488
[26] 1.701057469 2.703632990 0.313170885 3.019345148 3.291411656
[31] 0.216997529 6.463661339 0.004904021 5.122877364 11.956829922
[36] 2.326096969 2.738524715 1.801716226 2.524460562 0.850983015
[41] 1.215211632 3.239266753 0.809548965 1.020435564 11.078195420
[46] 1.773823933 0.125534325 1.309265473 0.915610160 1.049931216
[51] 3.663821013 3.354079349 1.461265728 8.193491926 3.905475731
[56] 6.072669062 0.313557658 4.441272673 1.483356349 0.445959084
[61] 0.301214415 0.659198061 2.942940806 4.925215045 3.950198618
[66] 0.836913735 0.539867049 1.326292405 3.774878831 0.093130565
[71] 0.300241714 1.630549893 2.029828370 2.963794180 0.879513970
[76] 0.602208384 0.951387028 1.418430865 2.452201537 2.792431482
[81] 0.723570409 0.124517420 2.441801693 2.862514224 0.512565249
[86] 0.473791358 4.898091069 1.313295108 2.652728602 4.133944167
[91] 2.943888428 0.188794027 1.193569690 0.645013623 4.032885485
[96] 0.566435333 1.406020562 0.069741759 1.510117937 1.322321354
> x<-rgamma(100,1,0.5)
> hist(x)
Question 6
(a) > A<-matrix(c(3,1,-4,2),ncol=2)
> A
[,1] [,2]
[1,] 3 -4
[2,] 1 2
(b) > t(A)
[,1] [,2]
[1,] 3 1
[2,] -4 2
(c) > solve(A)
[,1] [,2]
[1,] 0.2 0.4
[2,] -0.1 0.3
(d) > b<-matrix(c(6,-3),ncol=1)
> b
[,1]
[1,] 6
[2,] -3
> z<-solve(A)
> z
[,1] [,2]
[1,] 0.2 0.4
[2,] -0.1 0.3
> x<-z%*%b
> x
[,1]
[1,] -2.775558e-16
[2,] -1.500000e+00