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}