tests/testthat/test-calculate.R

In vungocbinh2009/thongke: Simple statistic package

library(thongke)
library(testthat)

test_that("Test các trường hợp cụ thể", {
  # In ra để không mất dòng dưới
  estimate_mean_t(
    mean = 39.8, alpha = 0.01, n = 15, s = sqrt(0.144)
  )
  estimate_mean_norm(
    sigma = 3, n = 36, alpha = 0.05, mean = 66
  )
  print("===================================================")
  estimate_mean_norm(
    sigma = 3, n = 36, alpha = 0.05, mean = 66, alternative = "min"
  )
  print("===================================================")
  estimate_mean_norm(
    sigma = 3, n = 36, alpha = 0.05, mean = 66, alternative = "max"
  )
  # Đáp số: 65,02 - 66,98
  print("===================================================")
  estimate_mean_t(
    mean = 39.8, alpha = 0.01, n = 15, s = sqrt(0.144)
  )
  print("===================================================")
  estimate_mean_t(
    mean = 39.8, alpha = 0.01, n = 15, s = sqrt(0.144), alternative = "min"
  )
  print("===================================================")
  estimate_mean_t(
    mean = 39.8, alpha = 0.01, n = 15, s = sqrt(0.144), alternative = "max"
  )
  # Đáp số: 39,5023 - 40,0977
  print("===================================================")
  estimate_var(n = 30, s = 0.032, alpha = 0.025)
  print("===================================================")
  estimate_var(n = 30, s = 0.032, alpha = 0.025, alternative = "min")
  print("===================================================")
  estimate_var(n = 30, s = 0.032, alpha = 0.025, alternative = "max")
  # Đáp số: 0.000649 - 0.001851
  print("===================================================")
  estimate_prop(n = 100, f = 0.6, alpha = 0.1)
  print("===================================================")
  estimate_prop(n = 100, f = 0.6, alpha = 0.1, alternative = "min")
  print("===================================================")
  estimate_prop(n = 100, f = 0.6, alpha = 0.1, alternative = "max")
  # Đáp số: 0.52 - 0.68
  print("===================================================")
  sample_size_mean(
    sigma = 3, alpha = get_alpha(1.64), eps = 0.5
  )
  # Đáp số: 96.826
  print("===================================================")
  sample_size_prop_1(
    f = 0.64, alpha = get_alpha(1.64), eps = 0.02
  )
  # Đáp số: 1549.2
  print("===================================================")
  sample_size_prop_2(eps = 0.02, alpha = get_alpha(1.64))
  # Đáp số: 1681
  print("===================================================")
  test_mean_norm(
    sigma = 5.2, alpha = 0.05, n = 100,
    mean = 27.56, mean_0 = 26, alternative = "neq"
  )
  # Đáp số: T=3 - c=1.96 - Bác bỏ
  print("===================================================")
  data <- c(19, 18, 22, 20, 16, 25)
  test_mean_t(
    mean = mean(data), mean_0 = 21.5, alternative = "neq",
    n = 6, alpha = 0.05, s = sqrt(var(data))
  )
  # Đáp số: T=-1.16 - c=2.571 - Chấp nhận
  print("===================================================")
  test_prop(f = 0.4, p_0 = 0.45, alpha = 0.05, n = 200, alternative = "neq")
  # Đáp số: T=-1.43, c=1.96, Chấp nhận
  print("===================================================")
  test_goodness_of_fit(
    expected = c(100, 100, 100, 100, 100, 100),
    actual = c(106, 92, 97, 105, 88, 112),
    alpha = 0.05
  )
  # Đáp số: T=4.22, c=11.070, Chấp nhận
  print("===================================================")
  test_2_mean_norm(
    n1 = 40, n2 = 50, mean1 = 130, mean2 = 140,
    sigma1 = sqrt(80), sigma2 = sqrt(100),
    alpha = 0.01, alternative = "neq"
  )
  # Đáp số: T=5, c=2.58, Bác bỏ
  print("===================================================")
  test_2_mean_t(
    alternative = "neq", alpha = 0.01, mean1 = 4.8, n1 = 10,
    s1 = 1.1, mean2 = 4.3, n2 = 12, s2 = 0.9
  )
  # Đáp số: T=1.174, c=2.845, Chấp nhận
  print("===================================================")
  test_2_prop(
    f1 = 0.42, f2 = 0.46, n1 = 100, n2 = 200,
    alpha = 0.05, alternative = "neq"
  )
  # Đáp số: T=-0.66, c=1.96, Chấp nhận
  print("===================================================")
  test_k_prop(
    m_i = c(79, 82, 77, 83, 76, 81),
    n_i = c(100, 100, 100, 100, 100, 100),
    alpha = 0.05
  )
  # Đáp số: T=2.42. c=11.07. Chấp nhận
  print("===================================================")
  test_independent(
    matrix = matrix(data = c(328, 122, 77, 33), ncol = 2, nrow = 2),
    alpha = 0.05
  )
  # Đáp số: T=0.368, c=3.841, Chấp nhận
  print("===================================================")
  correlation(
    x = c(80, 85, 88, 90, 95, 92, 82, 75, 78, 85),
    y = c(2.4, 2.8, 3.3, 3.1, 3.7, 3, 2.5, 2.3, 2.8, 3.1)
  )
  # Đáp số: 0.858
  print("===================================================")
  linear_regression(
    x = c(400, 600, 500, 600, 400, 500),
    y = c(44, 47, 48, 48, 43, 46)
  )
  # Đáp số: y=0.02x + 36
  calculate_sum(
    x = c(400, 600, 500, 600, 400, 500),
    y = c(44, 47, 48, 48, 43, 46)
  )
  expect_equal(1, 1)
})