def test_mse():
x = [1, 2, 2, 3]
y = [3, 4, 5, 6]
model = lsrl(x, y)
assert mse(x, y, model, rounding=3) == 0.25
x = [6, 7, 7, 8, 10, 10, 11, 12, 14, 15, 16]
y = [55, 40, 50, 41, 35, 28, 38, 32, 28, 18, 13]
model = lsrl(x, y)
assert round(math.sqrt(mse(x, y, model)), 2) == 5.01
def test_lsrl():
x = [1, 2, 2, 3]
y = [3, 4, 5, 6]
model = lsrl(x, y)
assert isinstance(model, LinearRegression)
assert round(model.intercept_, 2) == 1.5
assert round(model.coef_[0], 2) == 1.5
x = [6, 7, 7, 8, 10, 10, 11, 12, 14, 15, 16]
y = [55, 40, 50, 41, 35, 28, 38, 32, 28, 18, 13]
model = lsrl(x, y)
assert isinstance(model, LinearRegression)
assert round(model.intercept_, 2) == 70.16
assert round(model.coef_[0], 2) == -3.39
def test_lsrl_summarize():
x = [6, 7, 7, 8, 10, 10, 11, 12, 14, 15, 16]
y = [55, 40, 50, 41, 35, 28, 38, 32, 28, 18, 13]
assert lsrl(
x,
y,
summarize=True,
rounding=2) == {'intercept': 70.16, 'slope': -3.39}
def test_t_conf_y():
x = [6, 7, 7, 8, 10, 10, 11, 12, 14, 15, 16]
y = [55, 40, 50, 41, 35, 28, 38, 32, 28, 18, 13]
k = 1
model = lsrl(x, y)
s_2 = mse(x, y, model)
df = len(x) - (k + 1)
res = t_conf_y(x, 13, s_2, model, df, rounding=3)
assert res == (21.754, 30.311)
def test_t_pred_y():
x = [6, 7, 7, 8, 10, 10, 11, 12, 14, 15, 16]
y = [55, 40, 50, 41, 35, 28, 38, 32, 28, 18, 13]
k = 1
model = lsrl(x, y)
s_2 = mse(x, y, model)
df = len(x) - (k + 1)
res = t_pred_y(x, 13, s_2, model, df, rounding=3)
assert res == (13.919, 38.146)
def test_residuals():
x = [1, 2, 2, 3]
y = [3, 4, 5, 6]
model = lsrl(x, y)
assert residuals(x, y, model, 3) == [0.0, -0.5, 0.5, 0.0]