Part II Question
Please use the functions and approaches we practiced in
class. If you choose a different method, you must clearly explain your
steps in your own words, or full credit may not be given. Please
complete this assignment without AI assistance.
The Taiwan Social Change Survey (TSCS) is a nationwide survey that
has been conducted every year since 1985. The TSCS conducts face-to-face
interviews with a nationally representative sample of adults in Taiwan.
The tscs162s.csv file is a subset of the TSCS survey
conducted in 2016 (https://www2.ios.sinica.edu.tw/sc/en/scDownload3a.php).
Table below displays the names and descriptions of variables in the
tscs162s.csv data file. (25 points)
| id |
Respondent’s ID |
| sex |
Respondent’s Sex |
| birthyr |
Birth Year |
| eduyear |
Years of Education |
| hincome |
Household Monthly Income |
| internew |
Paid How Much Attention to International Issues |
| intpol |
How Interested in Politics |
1. Please import tscs162s.csv into R and obtain a summary of the
data. Remember to copy and paste the data import line from the
Console panel below so that R Markdown can read the
dataset. (15 points)
tscs162s <- read.csv("C:/Users/DELL/Desktop/tscs162s.csv")
summary(tscs162s)
## id sex birthyr internew
## Min. :103101 Min. :1.000 Min. :1918 Min. :1.000
## 1st Qu.:244126 1st Qu.:1.000 1st Qu.:1956 1st Qu.:1.000
## Median :406202 Median :1.000 Median :1970 Median :2.000
## Mean :460977 Mean :1.475 Mean :1969 Mean :2.141
## 3rd Qu.:710102 3rd Qu.:2.000 3rd Qu.:1984 3rd Qu.:3.000
## Max. :973123 Max. :2.000 Max. :1997 Max. :4.000
## NAs :9 NAs :1
## hincome eduyear intpol
## Min. : 1.00 Min. : 1.00 Min. :1.000
## 1st Qu.: 5.00 1st Qu.: 9.00 1st Qu.:3.000
## Median : 8.00 Median :13.00 Median :4.000
## Mean : 9.37 Mean :12.66 Mean :3.991
## 3rd Qu.:12.00 3rd Qu.:16.00 3rd Qu.:5.000
## Max. :26.00 Max. :31.00 Max. :5.000
## NAs :477 NAs :81 NAs :11
2. How many observations are there in the dataset? (Please use the
code introduced in class to find N.) (5 points)
nrow(tscs162s)
## [1] 1966
3. Based on the summary output, what are the earliest and latest
birth years (birthyr) represented in the dataset? (5 points)
Answer: earliest birth year is 1918, latest birth year is 1997
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