Null hypothesis (H₀): μ = 1800
Alternative hypothesis (H₁): μ ≠ 1800

Test statistic (t) = 3.149
p-value = 0.0108

Since the p-value (0.0108) is less than the significance level (α = 0.1), we reject the null hypothesis. This suggests that the average calorie intake for women at your college is significantly different from 1800 calories per day.

Would you like more details or have any questions?

Here are 5 related questions:

1. How is the test statistic for a t-test calculated?
2. What assumptions are required for conducting a t-test?
3. What does rejecting the null hypothesis imply in this context?
4. How is the p-value interpreted in hypothesis testing?
5. What happens if the significance level (alpha) is changed?

Tip: The p-value tells you the probability of observing the test results under the null hypothesis.