Question 1

Statistical projects should document both the data and the methods used to arrive at the conclusion.

Accepted Answer

A) True 
 B)False  True

Question 2

Describe/list some of the information that generally goes into a codebook.

Accepted Answer

Type of data, source of data, variable information, and individual/organization that collected the data

Question 3

The standard deviation measures how widely dispersed the values of the observations are.

Accepted Answer

A) True 
 B)False  True

Question 4

Replication files are used by researches to verify another researcher's projects results.

Accepted Answer

A) True 
 B)False

Question 5

The statistical package R is easier to use than Stata.

Accepted Answer

A) True 
 B)False

Question 6

Explain the importance of keeping replication files and properly documenting the data/research.

Accepted Answer

The answer of Explain the importance of keeping replication files...

Question 7

If an analysis cannot be replicated, it cannot be trusted.

Accepted Answer

A) True 
 B)False

Question 8

Please list the descriptive statistics that are used to better understand the data.

Accepted Answer

The answer of Please list the descriptive statistics that are...

Question 9

Compare and contrasts the basic benefits/drawbacks of Stata and R.

Accepted Answer

The answer of Compare and contrasts the basic benefits/drawbacks of...

Question 10

What is the purpose of plotting the data?

Accepted Answer

The answer of What is the purpose of plotting the...

Statistical projects should document both the data and the methods used to arrive at the conclusion.

Describe/list some of the information that generally goes into a codebook.

The standard deviation measures how widely dispersed the values of the observations are.

Replication files are used by researches to verify another researcher's projects results.

The statistical package R is easier to use than Stata.

Explain the importance of keeping replication files and properly documenting the data/research.

If an analysis cannot be replicated, it cannot be trusted.

Please list the descriptive statistics that are used to better understand the data.

Compare and contrasts the basic benefits/drawbacks of Stata and R.

What is the purpose of plotting the data?

The Quest for Causality

Bivariate Ols: the Foundation of Econometric Analysis

Hypothesis Testing and Interval Estimation: Answering Research Questions

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 2: Stats in the Wild: Good Data Practices

Statistical projects should document both the data and the methods used to arrive at the conclusion.

Describe/list some of the information that generally goes into a codebook.

The standard deviation measures how widely dispersed the values of the observations are.

Replication files are used by researches to verify another researcher's projects results.

The statistical package R is easier to use than Stata.

Explain the importance of keeping replication files and properly documenting the data/research.

If an analysis cannot be replicated, it cannot be trusted.

Please list the descriptive statistics that are used to better understand the data.

Compare and contrasts the basic benefits/drawbacks of Stata and R.

What is the purpose of plotting the data?

The Quest for Causality

Bivariate Ols: the Foundation of Econometric Analysis

Hypothesis Testing and Interval Estimation: Answering Research Questions

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