Take these two vectors:

```
points <- c(44, 36, 33, 33, 29, 28, 28, 22, 21, 20, 18, 15, 15, 15, 12, 12, 12, 11, 10, 10,  8,  8,  8,  8,  7,  7,  7,  6,  6,  6,  6,  6,  5,  5,  4,  3, 3, 2,  2,  2,  2,  1,  1,  1,  1,  1,  1,  1)

hours <- c(137.000000,  58.450000,  92.250000,  94.750000,  80.000000, 100.000000,  33.750000,  48.500000,  70.500000,  76.500000, 43.250000,  90.750000,  33.000000,  13.750000,  16.250000,  27.250000,  30.830000,  12.000000,  68.000000,  34.000000, 13.250000,  32.250000,   9.750000,   4.083333,  18.000000,  23.750000,   4.666667,  31.750000,  11.750000,   4.850000, 10.866667,   4.166667,  14.000000,   6.166667,   2.000000,   7.750000,  11.100000,   4.750000,   1.750000,   0.250000, 1.000000,  12.000000,  13.000000,   1.000000,   0.250000,   5.250000,   5.333333,   2.166667)

```

I made this model:

```
lm(points ~ hours)

# Call:
# lm(formula = points ~ hours)

# Coefficients:
# (Intercept)        hours  
#     2.9530       0.2823

```

The model suggests that if I do 1 hour, I get 3.2353 points.

I have also calculated mean points per hour:

```
mean(points/hours)

# 0.839875

```

The ratio suggests that if I do 1 hour, I get 0.839875 points.

Why is there such a big difference in the number of points per hour predicted by each method? Or am I interpreting something wrong?