Useful notes: The percentile 95 of a t-student distribution (with >100) is approximately 1.64 and the percentile 97.5 is

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answerhappygod
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Useful notes: The percentile 95 of a t-student distribution (with >100) is approximately 1.64 and the percentile 97.5 is

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Useful Notes The Percentile 95 Of A T Student Distribution With 100 Is Approximately 1 64 And The Percentile 97 5 Is 1
Useful Notes The Percentile 95 Of A T Student Distribution With 100 Is Approximately 1 64 And The Percentile 97 5 Is 1 (50.47 KiB) Viewed 95 times
Useful Notes The Percentile 95 Of A T Student Distribution With 100 Is Approximately 1 64 And The Percentile 97 5 Is 2
Useful Notes The Percentile 95 Of A T Student Distribution With 100 Is Approximately 1 64 And The Percentile 97 5 Is 2 (50.47 KiB) Viewed 95 times
Useful Notes The Percentile 95 Of A T Student Distribution With 100 Is Approximately 1 64 And The Percentile 97 5 Is 3
Useful Notes The Percentile 95 Of A T Student Distribution With 100 Is Approximately 1 64 And The Percentile 97 5 Is 3 (50.47 KiB) Viewed 95 times
Useful notes: The percentile 95 of a t-student distribution (with >100) is approximately 1.64 and the percentile 97.5 is approximately 1.96 QUESTION 1 (16 marks) Answer the following questions: a) Briefly explain the concept of Omitted Variable Bias. Provide an example of it. b) Briefly explain how OLS estimation of ß in the regression y = a +Bxi + ε is affected when the variable xis measured with some random error (i.e. we don't observe the true x; but a version of it that includes some measurement error). c) After running an OLS regression of y, on Xi you calculate the average & and you realize that it is zero. Does it mean that the OLS assumption E($) = 0 is true in the population? d) You estimate the model: Profits; = a + B, EducCEO; + & by OLS, where EducCEO, is the education of the CEO. Your estimation of B, is imprecise (i.e. it has a large variance). Explain if including the experience of the CEO as a second explanatory variable in the regression will increase or reduce the variance of the estimated Bi. =
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