def significance():
"Check the significance of a correlation"
#TODO: test probability with student t
# p = student_t(n-1, t)
# if 1-p<=0.05 data is considered good [HUMPHREY95] p.70
actual_loc, hours = get_projects_metrics()
t, r2, n = calc_significance(actual_loc, hours)
p = calc_student_t_probability(t, n - 1)
s = 1 - p
if s < 0.005:
significance = "very high"
elif s < 0.01:
significance = "high"
elif s < 0.05:
significance = "good"
elif s < 0.2:
significance = "adequate"
else:
significance = "poor"
return {
'loc': actual_loc,
'hours': hours,
'n': n,
'r2': r2,
't': t,
'p': p,
's': s,
"significance": significance
}
def significance():
"Check the significance of a correlation"
# TODO: test probability with student t
# p = student_t(n-1, t)
# if 1-p<=0.05 data is considered good [HUMPHREY95] p.70
actual_loc, hours = get_projects_metrics()
t, r2, n = calc_significance(actual_loc, hours)
p = calc_student_t_probability(t, n - 1)
s = 1 - p
if s < 0.005:
significance = "very high"
elif s < 0.01:
significance = "high"
elif s < 0.05:
significance = "good"
elif s < 0.2:
significance = "adequate"
else:
significance = "poor"
return {"loc": actual_loc, "hours": hours, "n": n, "r2": r2, "t": t, "p": p, "s": s, "significance": significance}
def significance():
# [HUMPHREY95] p.515
t, r2, n = calc_significance(x_values, y_values)
p = calc_student_t_probability(t, n-1)
return {'loc': x_values, 'hours': y_values, 'n': n, 'r2': r2, 't': t, 'ok': round(t, 4)==9.0335, 'p': p}
