A null hypothesis of H0: \beta = 0 can be rejected at the 95% confidence interval if and only if:

A) The 95% confidence interval contains zero B) The 95% confidence interval does not contain zero C) The null hypothesis is in the middle of the 95% confidence interval D) The sample size is sufficiently large (n>=30) A) The 95% confidence interval contains zero B) The 95% confidence interval does not contain zero C) The null hypothesis is in the middle of the 95% confidence interval D) The sample size is sufficiently large (n>=30)

Exam 4: Hypothesis Testing and Interval Estimation: Answering Research Questions

Describe what a power curve is, and provide a rough sketch of a power curve, and accurately label the x-axis and the y-axis.

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Question 1

Correct Answer:

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A power curve characterizes the probability of rejecting the null hypothesis for each possible value of the parameter. The y-axis is the probability of rejecting the null for some alpha, while the x-axis is all the possible values of the parameter.

In hypothesis testing, what we really care about is the size of the ₁ coefficient.

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Question 2

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Describe the relationship between sample size and statistical significance.

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Question 3

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A larger sampler size can yield a statistically significant result even when the effect (coefficient) is small. This is because a larger sample increases the power of the test (and can decrease the standard error of the coefficient).

Explain the difference between statistical significance and substantive significance.

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Question 4

Reducing the significance level (alpha) will:

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Question 5

Show the full equation to calculate the t-statistic.

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Question 6

In which case would we choose to a one-sided alternative hypothesis over a two-sided alternative hypothesis?

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Question 7

If we decrease the significance level (alpha) all else being equal, the power of the test will:

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Question 8

Which of the following will tend to reduce the size of a confidence interval?

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Question 9

Explain what the distribution of B̂₁ is under the null hypothesis H₀: \beta = 0 and why.

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Question 10

We fail to reject the null hypothesis if the test statistic is greater than the critical value.

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Question 11

Assume that the two-sided 95% confidence interval for the effect of a price on amount of beef purchased is between 0.30 and 0.38. Which of the following statements is incorrect?

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Question 12

A null hypothesis of H₀: \beta = 0 can be rejected at the 95% confidence interval if and only if:

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Question 13

A large sample will tend to produce high-power statistical tests while small samples will tend to produce low power statistical tests.

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Question 14

Type I errors occur when we fail to reject a null hypothesis even when it is false.

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Question 15

Type II errors occur when we fail to reject a null hypothesis even when it is false.

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Question 16

Explain the t distribution and explain what its tails are like and why?

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Question 17

A null and alternative hypothesis are statements pertaining to:

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Question 18

Statistical tools allow us to prove the null hypothesis is wrong.

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Question 19

A statistical significance test that is based on a small sample may not produce a result that is statistically significant even if the true value of the coefficient is different from the value in the null hypothesis. Such a situation is:

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Question 20

Showing 1 - 20 of 20

Describe what a power curve is, and provide a rough sketch of a power curve, and accurately label the x-axis and the y-axis.

In hypothesis testing, what we really care about is the size of the ₁ coefficient.

Describe the relationship between sample size and statistical significance.

Explain the difference between statistical significance and substantive significance.

Reducing the significance level (alpha) will:

Show the full equation to calculate the t-statistic.

In which case would we choose to a one-sided alternative hypothesis over a two-sided alternative hypothesis?

If we decrease the significance level (alpha) all else being equal, the power of the test will:

Which of the following will tend to reduce the size of a confidence interval?

Explain what the distribution of B̂₁ is under the null hypothesis H₀: \beta = 0 and why.

We fail to reject the null hypothesis if the test statistic is greater than the critical value.

Assume that the two-sided 95% confidence interval for the effect of a price on amount of beef purchased is between 0.30 and 0.38. Which of the following statements is incorrect?

A null hypothesis of H₀: \beta = 0 can be rejected at the 95% confidence interval if and only if:

A large sample will tend to produce high-power statistical tests while small samples will tend to produce low power statistical tests.

Type I errors occur when we fail to reject a null hypothesis even when it is false.

Type II errors occur when we fail to reject a null hypothesis even when it is false.

Explain the t distribution and explain what its tails are like and why?

A null and alternative hypothesis are statements pertaining to:

Statistical tools allow us to prove the null hypothesis is wrong.

A statistical significance test that is based on a small sample may not produce a result that is statistically significant even if the true value of the coefficient is different from the value in the null hypothesis. Such a situation is:

The Quest for Causality

Stats in the Wild: Good Data Practices

Bivariate Ols: the Foundation of Econometric Analysis

Multivariate Ols: Where the Action Is

Dummy Variables: Smarter Than You Think

Specifying Models

Using Fixed Effects to Fight Endogeneity in Panel Data and Difference-In-Difference Models

Instrumental Variables: Using Exogenous Variation to Fight Endogeneity

Experiments: Dealing With Real-World Challenges

Regression Discontinuity: Looking for Jumps in Data

Dummy Dependent Variables

Time Series: Dealing With Stickiness Over Time

Advanced Ols

Advanced Panel Data

Filters

Exam 4: Hypothesis Testing and Interval Estimation: Answering Research Questions

Describe what a power curve is, and provide a rough sketch of a power curve, and accurately label the x-axis and the y-axis.

In hypothesis testing, what we really care about is the size of the 1 coefficient.

Describe the relationship between sample size and statistical significance.

Explain the difference between statistical significance and substantive significance.

Reducing the significance level (alpha) will:

Show the full equation to calculate the t-statistic.

In which case would we choose to a one-sided alternative hypothesis over a two-sided alternative hypothesis?

If we decrease the significance level (alpha) all else being equal, the power of the test will:

Which of the following will tend to reduce the size of a confidence interval?

Explain what the distribution of B̂1 is under the null hypothesis H0: \beta = 0 and why.

We fail to reject the null hypothesis if the test statistic is greater than the critical value.

Assume that the two-sided 95% confidence interval for the effect of a price on amount of beef purchased is between 0.30 and 0.38. Which of the following statements is incorrect?

A null hypothesis of H0: \beta = 0 can be rejected at the 95% confidence interval if and only if:

A large sample will tend to produce high-power statistical tests while small samples will tend to produce low power statistical tests.

Type I errors occur when we fail to reject a null hypothesis even when it is false.

Type II errors occur when we fail to reject a null hypothesis even when it is false.

Explain the t distribution and explain what its tails are like and why?

A null and alternative hypothesis are statements pertaining to:

Statistical tools allow us to prove the null hypothesis is wrong.

A statistical significance test that is based on a small sample may not produce a result that is statistically significant even if the true value of the coefficient is different from the value in the null hypothesis. Such a situation is:

The Quest for Causality

Stats in the Wild: Good Data Practices

Bivariate Ols: the Foundation of Econometric Analysis

Multivariate Ols: Where the Action Is

Dummy Variables: Smarter Than You Think

Specifying Models

Using Fixed Effects to Fight Endogeneity in Panel Data and Difference-In-Difference Models

Instrumental Variables: Using Exogenous Variation to Fight Endogeneity

Experiments: Dealing With Real-World Challenges

Regression Discontinuity: Looking for Jumps in Data

Dummy Dependent Variables

Time Series: Dealing With Stickiness Over Time

Advanced Ols

Advanced Panel Data

Filters

In hypothesis testing, what we really care about is the size of the ₁ coefficient.

Explain what the distribution of B̂₁ is under the null hypothesis H₀: \beta = 0 and why.

A null hypothesis of H₀: \beta = 0 can be rejected at the 95% confidence interval if and only if: