Why can't I predict for new observations in my linear model in R : <p>Please read this before insisting it's already been answered. I've reviewed similar questions to no avail. I have the very simple goal of building a simple linear model and predicting new values. Here's my code:</p>

<pre><code>a &lt;- c(9024492, 8379054, 8962608, 9095940, 8468694, 9215560, 9082280)

b &lt;- c(3747494, 3258151, 3795750, 2976020, 3185280, 3955260, 3837480)

model_data &lt;- data.frame(A = a, B = b)

model &lt;- lm(formula = A ~ B, data = model_data)

new_points &lt;- c(3500000, 3600000, 3700000)
new_points &lt;- data.frame(B = new_points)

predict(model, new_data = new_points)
</code></pre>

<p>And here is the unexpected output:</p>

<pre><code>&gt; predict(model, new_data = new_points)
      1       2       3       4       5       6       7 
8988178 8760036 9010676 8628501 8726062 9085043 9030131 
</code></pre>
