CHART, GRAPHS, TABLES

To complete this assignment you will use data_codebook.pdf and data_gss7414.xlsx, both found on Canvas.
PART 1: READING THE DATA [Purpose: to build an understanding of how the data is structured in excel and to practice mathematical notation.]
For this part, use FILTER to limit the dataset to respondents interviewed in 2014
1. In the GSS 2014, how old is respondent #100?
2. In the GSS 2014, is respondent #61 male or female? How happy is he/she? How many
years of education did his/her father have? [Hint: Use the codebook to look up category
labels. If the value for a variable is missing, tell me so].
3. In the GSS 2014, how many respondents are 89 years old? [Hint: Filter the data by year
and age]
PART 2: TYPES OF VARIABLES [Purpose: to familiarize you with the variables you will choose from for your final paper and to practice identifying variable types.]
4. For each of the variables below, tell me whether it is numerical or categorical. If numerical, is it ratio or interval? Is it discrete or continuous?
If categorical, is it ordinal or nominal? Is it binomial?
Base your answers on the variables as described in the codebook.
a. degree
b. hhincome
c. wrkstat
d. sex
PART 3: MODEL BUILDING [Purpose: to think about how the variables in the dataset may be connected and practice drawing models.]
5. Pick three variables from the codebook that have an intervening relationship.
a. Draw the model. Label the variables as IV, DV, and Intervening. Include arrows
showing causal direction.
b. In 2-3 sentences, explain your model and how you think the variables are related.
Specifically, why is your third variable intervening?
6. Pick three variables from the codebook that have a moderating relationship.
a. Draw the model. Label the variables as IV, DV, and Moderating. Include arrows
showing causal direction.
b. In 2-3 sentences, explain your model and how you think the variables are related.
Specifically, why is your third variable moderating?

FALL 2015: CHARTS, GRAPHS, & TABLES
Take-Home Assignment
DUE: Friday Monday November 2, 2015
NOTE: A hard copy is due at the beginning of class. Since it includes drawn models, this
homework may be handwritten. If there are multiple sheets, they must be stapled. This
assignment will be worth the equivalent of two (2) in-class assignments.
To complete this assignment you will use data_codebook.pdf and data_gss7414.xlsx, both found
on Canvas.
PART 1: READING THE DATA [Purpose: to build an understanding of how the data is
structured in excel and to practice mathematical notation.]
For this part, use FILTER to limit the dataset to respondents interviewed in 2014
1. In the GSS 2014, how old is respondent #100?
2. In the GSS 2014, is respondent #61 male or female? How happy is he/she? How many
years of education did his/her father have? [Hint: Use the codebook to look up category
labels. If the value for a variable is missing, tell me so].
3. In the GSS 2014, how many respondents are 89 years old? [Hint: Filter the data by year
and age]
PART 2: TYPES OF VARIABLES [Purpose: to familiarize you with the variables you will
choose from for your final paper and to practice identifying variable types.]
4. For each of the variables below, tell me whether it is numerical or categorical.
If numerical, is it ratio or interval? Is it discrete or continuous?
If categorical, is it ordinal or nominal? Is it binomial?
Base your answers on the variables as described in the codebook.
a. degree
b. hhincome
c. wrkstat
d. sex
PART 3: MODEL BUILDING [Purpose: to think about how the variables in the dataset may be
connected and practice drawing models.]
5. Pick three variables from the codebook that have an intervening relationship.
a. Draw the model. Label the variables as IV, DV, and Intervening. Include arrows
showing causal direction.
b. In 2-3 sentences, explain your model and how you think the variables are related.
Specifically, why is your third variable intervening?
6. Pick three variables from the codebook that have a moderating relationship.
a. Draw the model. Label the variables as IV, DV, and Moderating. Include arrows
showing causal direction.
b. In 2-3 sentences, explain your model and how you think the variables are related.
Specifically, why is your third variable moderating?


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