I am trying to use a for-loop over a range of positive and negative values and then plot the results. However, I'm having trouble getting R not to plot the correct values, since the negative values seem to screw up the index.

More precisely, the code I am running is:

```
# Setup objects
R = (1:20)
rejection = rep(NA, 20)
t = seq(from = -10, to = 10, by = 1)
avg_rej_freq = rep(NA, 21)

# Test a hypothesis for each possible value of x and each replication
for (x in t) {
  for (r in R) {
    # Generate 1 observation from N(x,1)
    y =  rnorm(1, x, 1)
    # Take the average of this observation
    avg_y = mean(y)
    # Test this observation using the test we found in part a
    if (avg_y >= 1 + pnorm(.95))
    {rejection[r] = 1}
    if (y < 1 + pnorm(.95))
    {rejection[r] = 0}
  }
  # Calculate the average rejection frequency across the 20 samples
  avg_rej_freq[x] = mean(rejection)
}

# Plot the different values of x against the average rejection frequency
plot(t, avg_rej_freq)

```

The resulting graph should look something like this

```
# Define the rejection probability for n=1
rej_prob = function(x)(1-pnorm(1-x+qnorm(0.95)))

# Plot it
curve(rej_prob,from = -10, to = 10, xlab = expression(theta), 
      ylab = "Rejection probability")

```

...but there's clearly something wrong with my code that is shifting the positive values on the graph over to the left.

Any help on how to fix this would be much appreciated!