Our null hypothesis is that the true coefficient is zero. In which case would we choose to use a one-sided alternative hypothesis over a two-sided alternative hypothesis? We choose a one sided alternative hypothesis when we have a large sample size. We choose a one sided alternative hypothesis when we specify a low (0.01) significance level. It does not matter what type of alternative hypothesis we specify. Choose a one sided alternative hypothesis when the theory and literature suggests either that the true coefficient should be greater than zero or that the true coefficient should be less than zero.

you are given the following model, where u and v are error terms meeting all standard assumptions of the linear regression: y= B1+B2 In(X2)+u y=B1+B2 Ln(X2)+ B3 X3+v One of the selection criteria between the 2 models is to choose the one with the highest R-Square Select one: O True O False

You are trying to determine whether or not variables x2 and x3 jointly affect y. You set up a null and alternative hypothesis appropriate to this question. Before forming your test statistic, what are the two models you need to estimate? None of these is the correct pair of models to estimate. y = Bo + B1x1 + B2x2 + B3x3 + B4x4 + u and y = Bo + v y = Bo + B1x1 + B2x2 + B4x4 + w and y = Bo + B1x1 + B3X3 + B4X4 + e y = Bo + B1x1 + B2x2 + B3x3 + B4x4 + u and y = Bo + B1x1 + B4x4 + v

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In the p-value approach to hypothesis testing, we reject the null hypothesis if O p-value > 0.05 O p-value 0.05 O p-value 0.05 O p-value < 0.05

7 Which of the following statements about Type I and Type II errors is correct:   a Type I:  Do not reject a false null hypothesis.  Type II: Reject a true null hypothesis. b Type I:  Reject a false null hypothesis.  Type II: Reject a true null hypothesis.   c Type I:  Reject a true null hypothesis.  Type II: Do not reject a false null hypothesis.  d Type I:  Reject a true alternative hypothesis.  Type II: Do not reject a false alternative.

When conducting a hypothesis test, you obtain a large p-value. This implies ... a- that the observed value is consistent with the null hypothesis b- a rejection of the null hypothesis c- the observed value is larger than cut-off value specified by the test d- that the t-satistic is large What is the answer?

Suppose we have sample data on (y,x) of size n. Consider regressing y on x and a constant using the least square method (OLS estimation). The estimated equation is y = 2.59 +5.19 x + e where e is the residual. The standard errors for the constant and the coefficient were 0.51 and 1.58 respectively. To test the null hypothesis of zero coefficient (for x) at a given significance level, we may use t-statistic. Compute the t-statistic for the coefficient. Make sure the answer is round up to the nearest hundredth. e.g. 3.015 --> 3.02

Spatial Resolution: Regionally specific fine-scale features and changes are difficult to capture in global climate models since they usually operate at coarse spatial resolutions. The inability to produce precise and comprehensive forecasts for localised consequences is a result of this restriction. Generate a hypothesis related to this problem

Question 4 Question 4. Microsort is a genetics company that advertises a product that supposedly increases the chance of a female birth for couples planning to have children. In their experimentation process, they set up the null hypothesis and alternative hypotheses as follows: Ho: the product does not work H: the product works The alpha error is "saying that the product works when in fact it does not" Which statement below is correct regarding this experiment? a) a. They should set the alpha level to 1 (or 100%). O b) b. They should set the alpha level to 0. O c) c. From the point of view of Microsoft, they will likely desire to set the alpha lower laconnorad to hiahorl on a orohahilitu.ceale