1. Consider the following studies.

College Scorecard (Institution-Level Data)

Pulse Survey

Beginning Postsecondary Students Longitudinal Study (BPS)

International House Price Database

After inspecting the website's information about these datasets (e.g., dictionary/ codebooks, sample design description, technical documentation, etc.), answers the questions listed below for each of the four datasets:

(a) Say if the data collected in the study are cross-sectional, time series, longitudinal /panel data.

(4 points)

(b) Identify the unit of analysis of each dataset. (4 points)

(c) Identify the dates were the data were collected. (8 points)

(d) Identify the population of interest associated with each dataset (4 pts)

2. The National Survey of Children's Health (NSCH) is an "annual household survey that collect information of the physical and emotional health of children 0 - 17 years old in the United States". Read the codebook of this survey available here. Identify the following type of variables:

(a) One categorical and nominal variable (1 point)

(b) One categorical and ordinal variable (2 points)

(c) One quantitative and discrete variable (1 point)

(d) One quantitative and continuous variable (1 point)

3. A description of workers. Each year, the Census Bureau selects a different and random sample of more than 3 million of households to be interviewed in American Community Survey (ACS). The dataset that has been assigned to you contains information of a sample of workers of two states.

Here's the data set for the two states. (You have to download it first then open it using R studio)

('A worker has been defined as someone who had a positive salary in the last 12 months previous to the interview.)

interviewed in the ACS 2021. You must use that dictionary to know the label and the definition of the variables that you have in your dataset (person record). The dictionary can be found here:

ACS 2020 dictionary Please note that the salary variable (WAGP) in your dataset is in thousands of dollars.

Notes

In your answers use up to one decimal place when the number is not an integer. If the number is close to zero (i.e 0.0006) use up to four decimal places.

Show your work to earn full credit. When it corresponds, indicate what R function you used to compute the estimate (or upload your R script).

Use the dataset that was assigned. If you use a different dataset, your homework will not be graded.

Upload your R script that it can contribute to understanding how you did graphs or calculations.

(a) Describe the structure of the data set. In your answer include the population of interest, sample size, number of variables, and type of data (i.e., cross-sectional, time series, or longitudinal/panel data). In addition, identify each variable following the classification reviewed in class (i.e. categorical (nominal /ordinal) or quantitative (discrete/continuous)). You can ignore the ID variables and the person sampling weight. (15 points)

Describe the workers by computing the estimates of median and mean for these three variables: earnings (WAGP), the usual hours worked per week (WKHP), and the travel time to work (JWMNP). Compute the estimates conditional to the state of residence of the worker (i.e. compute the estimates for the first state and for the second state separately). Present your results in a table as it is suggested in the word document "TABLE HW1". Comment the results. Do not forget to mention the R functions you used to compute the statistics (or include the R code that you wrote.(15points)

Here's the "TABLE HW1".

	ANNUAL SALARY ($000's)	USUAL HOURS WORKED PER WEEK	TRAVEL TIME TO WORK (minutes)
	FEMALE	MALE	FEMALE	MALE	FEMALE	MALE
Sample mean
Sample median
Number of Observations

	MALE	FEMALE
	ANNUAL SALARY ($000's)	USUAL HOURS WORKED PER WEEK	TRAVEL TIME TO WORK (minutes)	ANNUAL SALARY ($000's)	USUAL HOURS WORKED PER WEEK	TRAVEL TIME TO WORK (minutes)
Sample Mean
Sample Median
Number of Observations

	GENDER	ANNUAL SALARY ($000's)	USUAL HOURS WORKED PER WEEK	TRAVEL TIME TO WORK (minutes)
Sample Mean	MALE
FEMALE
Sample Median	MALE
FEMALE
Number of Observations	MALE
FEMALE