For reference, I use a 0 to 100 rating system.
Below is the summary and tabulation of the difference between my score and the given PSI (absolute value). Look at the tabulation, because that is were it tells you what percent of the time it gets within 1 point, 2 point, 5 point, etc.
I had 2,021 ratings at the time, only 1,947 of which had PSI's, so that's how many observations there are.
Summary:
Code: Select all
Variable | Obs Mean Std. Dev. Min Max
-------------+---------------------------------------------------------
diff | 1,947 9.667694 10.76866 0 78
Code: Select all
diff | Freq. Percent Cum.
------------+-----------------------------------
0 | 103 5.29 5.29
1 | 165 8.47 13.76
2 | 163 8.37 22.14
3 | 170 8.73 30.87
4 | 150 7.70 38.57
5 | 147 7.55 46.12
6 | 122 6.27 52.39
7 | 108 5.55 57.94
8 | 101 5.19 63.12
9 | 74 3.80 66.92
10 | 65 3.34 70.26
11 | 56 2.88 73.14
12 | 57 2.93 76.07
13 | 42 2.16 78.22
14 | 43 2.21 80.43
15 | 36 1.85 82.28
16 | 26 1.34 83.62
17 | 24 1.23 84.85
18 | 24 1.23 86.08
19 | 23 1.18 87.26
20 | 17 0.87 88.14
21 | 16 0.82 88.96
22 | 11 0.56 89.52
23 | 13 0.67 90.19
24 | 8 0.41 90.60
25 | 12 0.62 91.22
26 | 11 0.56 91.78
27 | 15 0.77 92.55
28 | 7 0.36 92.91
29 | 15 0.77 93.68
30 | 4 0.21 93.89
31 | 4 0.21 94.09
32 | 7 0.36 94.45
33 | 5 0.26 94.71
34 | 15 0.77 95.48
35 | 3 0.15 95.63
36 | 5 0.26 95.89
37 | 8 0.41 96.30
38 | 4 0.21 96.51
39 | 9 0.46 96.97
40 | 2 0.10 97.07
41 | 1 0.05 97.12
42 | 8 0.41 97.53
43 | 3 0.15 97.69
44 | 5 0.26 97.95
45 | 1 0.05 98.00
46 | 7 0.36 98.36
48 | 3 0.15 98.51
49 | 4 0.21 98.72
50 | 4 0.21 98.92
51 | 3 0.15 99.08
52 | 1 0.05 99.13
53 | 1 0.05 99.18
54 | 3 0.15 99.33
55 | 2 0.10 99.44
56 | 1 0.05 99.49
57 | 1 0.05 99.54
60 | 1 0.05 99.59
61 | 1 0.05 99.64
62 | 2 0.10 99.74
63 | 2 0.10 99.85
64 | 1 0.05 99.90
67 | 1 0.05 99.95
78 | 1 0.05 100.00
------------+-----------------------------------
Total | 1,947 100.00
The median difference is 6, and without outliers is still 6 (no surprise there).
The largest miss was Detroit (2017) at 78 over, which is also my lowest rated film.
The largest low miss was Piranha II, at 29 below, which is understandable because I rated it well as so-bad-it's-good experience.
Additionally, my PSI and eventual score have a correlation coefficient of 0.7, which is exactly the lower bound for "strong correlation." Interestingly, my PSI has a correlation coefficient of 0.86 with average IMDB ratings, which is quite strong.
In a regression where my score is the dependent variable and PSI is the only explanatory variable, this is the outcome:
Code: Select all
-------------+---------------------------------- F(1, 1945) = 1845.19
Model | 329784.882 1 329784.882 Prob > F = 0.0000
Residual | 347624.229 1,945 178.72711 R-squared = 0.4868
-------------+---------------------------------- Adj R-squared = 0.4866
Total | 677409.11 1,946 348.103346 Root MSE = 13.369
------------------------------------------------------------------------------
score | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
psi | 1.229146 .0286143 42.96 0.000 1.173028 1.285264
_cons | -22.50157 2.207148 -10.19 0.000 -26.8302 -18.17295
Almost 49% of the variance in my scores is explained by PSI. This compares very well to other variables.
- PSI: 49%
IMDB Ratings: 35%
Rotten Tomatoes scores: 35%
Metacritic scores: 32%
Budget: 27%
Date Rated: 10% (I rated harder over time)
Oscar Nominations: 9%
Oscar Wins: 5%
Year: 3%
Runtime: 1%
Box Office: 0%
So, how does PSI do? It passes, and with flying colors. It astounds me that 50% of the time it is able to get within 6 points.