JuliaForDataAnalysis/appB.jl
2021-12-29 16:08:09 +01:00

67 lines
1.9 KiB
Julia

# Bogumił Kamiński, 2021
# Codes for appendix B
# Code for exercise 3.1
using Statistics
using BenchmarkTools
aq = [10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58
8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76
13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71
9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84
11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47
14.0 9.96 14.0 8.1 14.0 8.84 8.0 7.04
6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25
4.0 4.26 4.0 3.1 4.0 5.39 19.0 12.50
12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56
7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91
5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89];
@benchmark [cor($aq[:, i], $aq[:, i+1]) for i in 1:2:7]
@benchmark [cor(view($aq, :, i), view($aq, :, i+1)) for i in 1:2:7]
# Code for exercise 3.2
function dice_distribution(dice1, dice2)
distribution = Dict{Int, Int}()
for i in dice1
for j in dice2
s = i + j
if haskey(distribution, s)
distribution[s] += 1
else
distribution[s] = 1
end
end
end
return distribution
end
function test_dice()
all_dice = [[1, x2, x3, x4, x5, x6]
for x2 in 2:11
for x3 in x2:11
for x4 in x3:11
for x5 in x4:11
for x6 in x5:11]
two_standard = dice_distribution(1:6, 1:6)
for d1 in all_dice, d2 in all_dice
test = dice_distribution(d1, d2)
if test == two_standard
println(d1, " ", d2)
end
end
end
test_dice()
# Code for exercise 3.3
plot(scatter(data.set1.x, data.set1.y, legend=false),
scatter(data.set2.x, data.set2.y, legend=false),
scatter(data.set3.x, data.set3.y, legend=false),
scatter(data.set4.x, data.set4.y, legend=false))