312final/lab_problems.R at master · susantmtran/312final · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
library(tidyverse)
library(readxl)
library(janitor)
library(scales)

uni_data <- read_excel("uni_data.xlsx") %>% clean_names()

### LAB 4

# problem 1 -- difference in means

summary(uni_data$end_endow)

low_endow <- uni_data %>% filter(end_endow <= median(uni_data$end_endow))
hi_endow <- uni_data %>% filter(end_endow >= median(uni_data$end_endow))

summary(low_endow$end_endow)
summary(hi_endow$end_endow)

t.test(hi_endow$end_endow, low_endow$end_endow, var.equal = FALSE)

summary(uni_data$h_index)

t.test(uni_data$h_index, mu = 0.5)
hist(uni_data$h_index)

# problem 2 -- correlation between variables

ggplot(uni_data, aes(end_endow, h_index)) +
  geom_jitter() +
  geom_smooth(method = "lm", color = "pink") +
  theme_light() +
  labs(x = "endowment at the end of fy19 ($)",
       y = "theil's information index")

ggplot(uni_data, aes(log(end_endow), h_index)) +
  geom_jitter() +
  geom_smooth(method = "lm", color = "pink") +
  theme_light() +
  labs(x = "log of endowment at the end of fy19 ($)",
       y = "theil's information index")

### LAB 5

# problem 1 -- bivariate regression

lm_log <- lm(h_index ~ I(log(end_endow)), uni_data)

summary(lm_log)

plot(uni_data$h_index ~ I(log(uni_data$end_endow)),
     xlab = "log of market value of endowment ($)",
     ylab = "theil's information index")

abline(lm_log)

### LAB 6

# problem 1 -- multivariate regression

uni_data$ranking <- as.numeric(uni_data$ranking)

model <- lm(h_index ~ I(log(end_endow)) + factor(ranking) + year, uni_data)
summary(model)

model2 <- lm(h_index ~ I(log(end_endow)) + factor(ranking):year, uni_data)
summary(model2)

library(stargazer)
stargazer(lm_log, model, type="text", out="reg_table.html")

### LAB 7

# problem 1 -- regression

uni_data$type <- as.factor(uni_data$type)
uni_data$county <- as.factor(uni_data$county)
uni_data$admit_pct <- uni_data$admit_pct/100
uni_data$year <- as.character(uni_data$year)
uni_data$year <- as.Date(uni_data$year, "%Y")

final_model <- lm(h_index ~ I(log(end_endow)) + ranking:admit_pct + year, uni_data)
final_model2 <- lm(h_index ~ I(log(end_endow)) + ranking + admit_pct + year, uni_data)

stargazer(lm_log, model, final_model, final_model2, type = "text", out = "reg_table.html")

summary(lm_log)
summary(model)
summary(final_model)
summary(final_model2)

# problem 2 -- largest change

quantile(uni_data$end_endow, na.rm=TRUE)
quantile(log(uni_data$end_endow), na.rm=TRUE)
x_quantiles <- quantile(log(uni_data$end_endow), na.rm=TRUE)

percentile_25 <- x_quantiles[[2]]
percentile_75 <- x_quantiles[[4]]

coefficients <- coef(final_model2)
coefficient_x <- coefficients[[2]]
change_x <- percentile_75 - percentile_25
change_y <- change_x * coefficient_x
change_y

range_y <- range(uni_data$h_index, na.rm = TRUE)[2] -
  range(uni_data$h_index, na.rm = TRUE)[1]
range(uni_data$h_index, na.rm = TRUE)
change_y/range_y