Regression with a Single Regressor (FRM Part 1 2023 - Book 2 - Chapter 7)

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After completing this reading you should be able to:
- Calculate and interpret confidence intervals for regression coefficients.
- Interpret the p-value.
- Interpret hypothesis tests about regression coefficients.
- Evaluate the implications of homoskedasticity and heteroskedasticity.
- Determine the conditions under which the OLS is the best linear conditionally unbiased estimator.
- Explain the Gauss-Markov Theorem and its limitations, and alternatives to the OLS.
- Apply and interpret the t-statistic when the sample size is small.

[@user-ni8pg8ki3z]

Thank you! Your videos are really helpful ❤️

[@analystprep]

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[@FCTORAU]

@ around 11:40, when finding the t value, why is the degree of freedom 28? the sample has 30 observations, and n-1 so i thought the degree of freedom is 29?

[@leonardoandaloro397]

Because we are estimating two parameters (B0 and B1) so the degrees of freedom are calculated as n - 2 so 28. It's written in the slide in minute 7:40 :)

[@christonenov]

@19:16 You mean it that it will no long be efficient. You said "It is no longer going to be inefficient" twice.

[@analystprep]

You are correct. Sorry about that. We meant "not efficient" as it is written on the slide.