Conducting Analysis & Running Statistical Tests

How do varyious factors affect one’s feelings toward immigration policies?

In my analysis, I will look at seven variables and there relationships with feelings toward immigration.

Variables:

• Immigration_Should_Be: how a respondent feels about changing immigration policies
• Raised_In_US: was a respondent was raised in the United States
• Relig_Importance: independent of what religion, how important is religion to a respondent
• Occupation: a respondent’s occupation classification
• FT_Trump: how does a respondent feel about Trump and his policies
• Politics_OR_Current_Events: is the respondent interested in politics or current events
• ft_immig_2017: respondent’s feeling toward immigrants

MyVoterData <- FullVoterData %>% 
  mutate(Immigration_Should_Be = ifelse(immi_makedifficult_2018 == 1, "Much Easier",
                                 ifelse(immi_makedifficult_2018 == 2, "Slightly Easier",
                                 ifelse(immi_makedifficult_2018 == 3, "No Change",
                                 ifelse(immi_makedifficult_2018 == 4, "Slightly Harder",
                                 ifelse(immi_makedifficult_2018 == 5, "Much Harder",
                                 ifelse(immi_makedifficult_2018 == 8, "Don't Know", NA)))))),
         Raised_In_US = ifelse(childhood_2018 == 1, "Yes",
                        ifelse(childhood_2018 == 2, "No", NA)),
         Relig_Importance = ifelse(pew_religimp_2018 == 1, "Very Important",
                           ifelse(pew_religimp_2018 == 2, "Somewhat Important",
                           ifelse(pew_religimp_2018 == 3, "Not Too Important",
                           ifelse(pew_religimp_2018 == 4, "Not at All Important", NA)))),
         Occupation = ifelse(occupationcat_baseline == 1, "Professional/Technical",
                      ifelse(occupationcat_baseline == 2, "Management",
                      ifelse(occupationcat_baseline == 3, "Management",
                      ifelse(occupationcat_baseline == 4, "Sales",
                      ifelse(occupationcat_baseline == 5, "Business Owner/Self-Employed",
                      ifelse(occupationcat_baseline == 6, "Clerical/Administrative",
                      ifelse(occupationcat_baseline == 7, "Military/Civilian Uniform Services",
                      ifelse(occupationcat_baseline == 8, "Retired",
                      ifelse(occupationcat_baseline == 9, "Other",
                      ifelse(occupationcat_baseline == 10, "Student",
                      ifelse(occupationcat_baseline == 11, "Unemployed",
                      ifelse(occupationcat_baseline == 12, "Other", NA)))))))))))),
         FT_Trump = ifelse(trumpfeel_2018 == 1, "Like and Approve of his Policies",
                    ifelse(trumpfeel_2018 == 2, "Like but Disapprove of his Policies",
                    ifelse(trumpfeel_2018 == 3, "Dislike but Approve of his Policies",
                    ifelse(trumpfeel_2018 == 4, "Dislike and Disapprove of his Policies", NA)))),
         Politics_OR_Current_Events = ifelse(polinterest_baseline == 1, "Very Interested",
                                      ifelse(polinterest_baseline == 2, "Somewhat Interested",
                                      ifelse(polinterest_baseline == 3, "Not Very Interested",
                                      ifelse(polinterest_baseline == 4, "Nothing", NA))))) %>% 
  filter(!is.na(ft_immig_2017),ft_immig_2017<=100) %>% 
  select(Immigration_Should_Be, Raised_In_US, Relig_Importance, Occupation, FT_Trump, Politics_OR_Current_Events, ft_immig_2017)
 
head(MyVoterData)

 
MyVoterData <- MyVoterData %>% 
  mutate(Immigration_Should_Be = factor(Immigration_Should_Be, levels = c("Much Easier",
                                                                          "Slightly Easier",
                                                                          "No Change",
                                                                          "Slightly Harder",
                                                                          "Much Harder",
                                                                          "Don't Know"
                                                                          )),
         Raised_In_US = factor(Raised_In_US, levels = c("Yes",
                                                        "No")),
         Occupation = factor(Occupation, levels = c("Professional/Technical",
                                                    "Management",
                                                    "Sales",
                                                    "Business Owner/Self-Employed",
                                                    "Clerical/Administrative",
                                                    "Military/Civilian Uniform Services",
                                                    "Retired",
                                                    "Student",
                                                    "Unemployed",
                                                    "Other")),
         Politics_OR_Current_Events = factor(Politics_OR_Current_Events, levels = c("Very Interested",
                                                                                    "Somewhat Interested",
                                                                                    "Not Very Interested",
                                                                                    "Nothing")))

---

Analysis

Does being raised in the US affect one’s feelings toward immigration policies?

kable(round(prop.table(table(MyVoterData$Raised_In_US, MyVoterData$Immigration_Should_Be),1),2)) %>% 
  kable_styling(bootstrap_options = c("striped", "condensed"), full_width = T) %>% 
  column_spec(1, bold = T)

	Much Easier	Slightly Easier	No Change	Slightly Harder	Much Harder	Don't Know
Yes	0.09	0.17	0.26	0.19	0.24	0.05
No	0.09	0.20	0.29	0.18	0.20	0.04

# Observed Frequencies
chisq.test(MyVoterData$Raised_In_US, MyVoterData$Immigration_Should_Be)[6]

$observed
                        
MyVoterData$Raised_In_US Much Easier Slightly Easier No Change Slightly Harder Much Harder Don't Know
                     Yes         386             741      1096             823        1023        211
                     No           16              34        50              30          34          7

# Expected Frequencies
chisq.test(MyVoterData$Raised_In_US, MyVoterData$Immigration_Should_Be)[7]

$expected
                        
MyVoterData$Raised_In_US Much Easier Slightly Easier  No Change Slightly Harder Much Harder Don't Know
                     Yes   386.55583       745.22579 1101.97259       820.22916  1016.39182 209.624803
                     No     15.44417        29.77421   44.02741        32.77084    40.60818   8.375197

# Chi-Squared Test
chisq.test(MyVoterData$Raised_In_US, MyVoterData$Immigration_Should_Be)

    Pearson's Chi-squared test

data:  MyVoterData$Raised_In_US and MyVoterData$Immigration_Should_Be
X-squared = 3.0839, df = 5, p-value = 0.6871

There is no statistically significant relationship between being raised in the U.S. and one’s feelings toward changing immigration laws.

kable(MyVoterData %>% 
  group_by(Raised_In_US) %>% 
  filter(!is.na(Raised_In_US)) %>% 
  summarize(avg_ft_immig = mean(ft_immig_2017, na.rm = TRUE))
) %>% 
  kable_styling(bootstrap_options = c("striped", "condensed"), full_width = T) %>% 
  column_spec(1, bold = T)

Raised_In_US	avg_ft_immig
Yes	61.09127
No	72.05848

# T-Test
t.test(ft_immig_2017~Raised_In_US, data = MyVoterData)

    Welch Two Sample t-test

data:  ft_immig_2017 by Raised_In_US
t = -5.6801, df = 187.14, p-value = 0.00000005077
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -14.776177  -7.158242
sample estimates:
mean in group Yes  mean in group No 
         61.09127          72.05848 

The table shows that on average, people who were raised outside of the US have higher feelings toward immigrants than people raised within the US. The t-test shows that there is a statistically significant difference between people raised within and outside the US and their average feelings toward immigrants.

---

Does religiousness affect one’s feelings toward immigration policies?

kable(round(prop.table(table(MyVoterData$Relig_Importance, MyVoterData$Immigration_Should_Be),1),2)) %>% 
  kable_styling(bootstrap_options = c("striped", "condensed"), full_width = T) %>% 
  column_spec(1, bold = T)

	Much Easier	Slightly Easier	No Change	Slightly Harder	Much Harder	Don't Know
Not at All Important	0.16	0.26	0.26	0.14	0.14	0.05
Not Too Important	0.08	0.18	0.27	0.20	0.21	0.05
Somewhat Important	0.07	0.16	0.26	0.21	0.24	0.05
Very Important	0.07	0.13	0.25	0.21	0.30	0.04

 
# Observed Frequencies
chisq.test(MyVoterData$Relig_Importance, MyVoterData$Immigration_Should_Be)[6]

$observed
                            
MyVoterData$Relig_Importance Much Easier Slightly Easier No Change Slightly Harder Much Harder Don't Know
        Not at All Important         157             253       254             134         140         53
        Not Too Important             51             115       169             124         133         30
        Somewhat Important            75             175       284             224         264         59
        Very Important               119             232       440             371         525         77

# Expected Frequencies
chisq.test(MyVoterData$Relig_Importance, MyVoterData$Immigration_Should_Be)[7]

$expected
                            
MyVoterData$Relig_Importance Much Easier Slightly Easier No Change Slightly Harder Much Harder Don't Know
        Not at All Important    89.36339        172.2802  254.9747        189.6193    236.0794   48.68304
        Not Too Important       56.08883        108.1314  160.0345        119.0144    148.1750   30.55585
        Somewhat Important      97.47914        187.9262  278.1308        206.8401    257.5195   53.10431
        Very Important         159.06864        306.6622  453.8600        337.5262    420.2261   86.65680

# Ch-Squared Test
chisq.test(MyVoterData$Relig_Importance, MyVoterData$Immigration_Should_Be)

    Pearson's Chi-squared test

data:  MyVoterData$Relig_Importance and MyVoterData$Immigration_Should_Be
X-squared = 215.64, df = 15, p-value < 0.00000000000000022

There is a strong statistical association between religious importance and feelings toward changing immigration laws. 29% of respondents who believe religion is very important also believe that immigration should be much harder, while only 14% of respondents who believe religion is not at all important believe that immigration should be much harder.

kable(MyVoterData %>% 
  group_by(Relig_Importance) %>% 
  filter(!is.na(Relig_Importance)) %>% 
  summarize(avg_ft_immig = mean(ft_immig_2017, na.rm = TRUE))
) %>% 
  kable_styling(bootstrap_options = c("striped", "condensed"), full_width = T) %>% 
  column_spec(1, bold = T)

Relig_Importance	avg_ft_immig
Not at All Important	67.81635
Not Too Important	61.97428
Somewhat Important	58.97138
Very Important	59.35730

NA

The table shows that on average, people who believe religion is not so important have higher feelings toward immigrants than people who believe religion is important.

---

Does one’s occupation affect his/her feelings toward immigration policies?

kable(round(prop.table(table(MyVoterData$Occupation, MyVoterData$Immigration_Should_Be),1),2)) %>% 
  kable_styling(bootstrap_options = c("striped", "condensed"), full_width = T) %>% 
  column_spec(1, bold = T)

	Much Easier	Slightly Easier	No Change	Slightly Harder	Much Harder	Don't Know
Professional/Technical	0.12	0.21	0.26	0.17	0.20	0.04
Management	0.10	0.16	0.24	0.25	0.21	0.04
Sales	0.07	0.17	0.24	0.19	0.29	0.04
Business Owner/Self-Employed	0.05	0.22	0.30	0.18	0.22	0.03
Clerical/Administrative	0.08	0.16	0.26	0.18	0.25	0.06
Military/Civilian Uniform Services	0.08	0.13	0.23	0.27	0.25	0.04
Retired	0.10	0.16	0.25	0.21	0.25	0.03
Student	0.21	0.31	0.15	0.10	0.15	0.07
Unemployed	0.10	0.14	0.25	0.18	0.25	0.08
Other	0.06	0.15	0.26	0.18	0.28	0.07

# Observed Frequencies
chisq.test(MyVoterData$Occupation, MyVoterData$Immigration_Should_Be)[6]

$observed
                                    
MyVoterData$Occupation               Much Easier Slightly Easier No Change Slightly Harder Much Harder
  Professional/Technical                     110             196       247             158         184
  Management                                  56              89       128             133         112
  Sales                                       15              36        52              41          61
  Business Owner/Self-Employed                14              61        81              49          60
  Clerical/Administrative                     29              63       101              71          96
  Military/Civilian Uniform Services           4               7        12              14          13
  Retired                                     72             116       188             156         188
  Student                                     14              21        10               7          10
  Unemployed                                  29              42        75              52          74
  Other                                       58             135       241             161         257
                                    
MyVoterData$Occupation               Don't Know
  Professional/Technical                     40
  Management                                 22
  Sales                                       8
  Business Owner/Self-Employed                9
  Clerical/Administrative                    24
  Military/Civilian Uniform Services          2
  Retired                                    23
  Student                                     5
  Unemployed                                 24
  Other                                      61

# Expected Frequencies
chisq.test(MyVoterData$Occupation, MyVoterData$Immigration_Should_Be)[7]

$expected
                                    
MyVoterData$Occupation               Much Easier Slightly Easier No Change Slightly Harder Much Harder
  Professional/Technical               84.884537      162.148517 240.25923       178.23636   223.32465
  Management                           49.024225       93.647272 138.75934       102.93865   128.97894
  Sales                                19.337333       36.938646  54.73285        40.60358    50.87503
  Business Owner/Self-Employed         24.875255       47.517319  70.40752        52.23183    65.44487
  Clerical/Administrative              34.861671       66.593616  98.67331        73.20082    91.71836
  Military/Civilian Uniform Services    4.720851        9.017885  13.36201         9.91261    12.42019
  Retired                              67.453702      128.851709 190.92257       141.63595   177.46547
  Student                               6.082635       11.619199  17.21644        12.77202    16.00294
  Unemployed                           26.872538       51.332579  76.06067        56.42563    70.69957
  Other                                82.887254      158.333258 234.60607       174.04256   218.06996
                                    
MyVoterData$Occupation               Don't Know
  Professional/Technical              46.146706
  Management                          26.651573
  Sales                               10.512565
  Business Owner/Self-Employed        13.523206
  Clerical/Administrative             18.952230
  Military/Civilian Uniform Services   2.566448
  Retired                             36.670591
  Student                              3.306769
  Unemployed                          14.609011
  Other                               45.060901

# Chi-Squared Test
chisq.test(MyVoterData$Occupation, MyVoterData$Immigration_Should_Be)

    Pearson's Chi-squared test

data:  MyVoterData$Occupation and MyVoterData$Immigration_Should_Be
X-squared = 128.6, df = 45, p-value = 0.000000000558

There is a statically significant association between occupation and feelings toward changing immigration laws. The crosstab shows that students are the only occupation category in which the majority respondents believe immigration should be made easier.

kable(MyVoterData %>% 
  group_by(Occupation) %>% 
  filter(!is.na(Occupation)) %>% 
  summarize(avg_ft_immig = mean(ft_immig_2017, na.rm = TRUE))
) %>% 
  kable_styling(bootstrap_options = c("striped", "condensed"), full_width = T) %>% 
  column_spec(1, bold = T)

Occupation	avg_ft_immig
Professional/Technical	63.96885
Management	63.45352
Sales	59.72628
Business Owner/Self-Employed	62.69412
Clerical/Administrative	63.05165
Military/Civilian Uniform Services	55.06579
Retired	60.78330
Student	67.74074
Unemployed	57.83690
Other	59.89817

The table shows that on average, students have the highest feelings toward immigrants.

---

Are feelings toward Trump and his policies related to feelings toward immigration policies?

kable(round(prop.table(table(MyVoterData$FT_Trump, MyVoterData$Immigration_Should_Be),1),2)) %>% 
  kable_styling(bootstrap_options = c("striped", "condensed"), full_width = T) %>% 
  column_spec(1, bold = T)

	Much Easier	Slightly Easier	No Change	Slightly Harder	Much Harder	Don't Know
Dislike and Disapprove of his Policies	0.15	0.24	0.29	0.16	0.10	0.06
Dislike but Approve of his Policies	0.04	0.13	0.24	0.23	0.33	0.04
Like and Approve of his Policies	0.03	0.10	0.21	0.22	0.42	0.02
Like but Disapprove of his Policies	0.04	0.08	0.24	0.29	0.25	0.10

# Observed Frequencies
chisq.test(MyVoterData$FT_Trump, MyVoterData$Immigration_Should_Be)[6]

$observed
                                        
MyVoterData$FT_Trump                     Much Easier Slightly Easier No Change Slightly Harder Much Harder
  Dislike and Disapprove of his Policies         328             531       648             349         220
  Dislike but Approve of his Policies             30              97       184             177         253
  Like and Approve of his Policies                38             128       269             278         538
  Like but Disapprove of his Policies              3               6        17              21          18
                                        
MyVoterData$FT_Trump                     Don't Know
  Dislike and Disapprove of his Policies        135
  Dislike but Approve of his Policies            34
  Like and Approve of his Policies               25
  Like but Disapprove of his Policies             7

# Expected Frequencies
chisq.test(MyVoterData$FT_Trump, MyVoterData$Immigration_Should_Be)[7]

$expected
                                        
MyVoterData$FT_Trump                     Much Easier Slightly Easier No Change Slightly Harder Much Harder
  Dislike and Disapprove of his Policies  203.550761       388.73604 570.35025       420.87563    524.9467
  Dislike but Approve of his Policies      71.348639       136.25981 199.91924       147.52538    184.0044
  Like and Approve of his Policies        117.472081       224.34518 329.15736       242.89340    302.9543
  Like but Disapprove of his Policies       6.628519        12.65898  18.57314        13.70558     17.0946
                                        
MyVoterData$FT_Trump                     Don't Know
  Dislike and Disapprove of his Policies 102.540609
  Dislike but Approve of his Policies     35.942547
  Like and Approve of his Policies        59.177665
  Like but Disapprove of his Policies      3.339179

# Chi-Squared Test
chisq.test(MyVoterData$FT_Trump, MyVoterData$Immigration_Should_Be)

    Pearson's Chi-squared test

data:  MyVoterData$FT_Trump and MyVoterData$Immigration_Should_Be
X-squared = 733.7, df = 15, p-value < 0.00000000000000022

There is a statisticaly significant association between feelings toward Trump and his policies and feelings toward changing immigration laws. The crosstab shows that respondents who like Trump and approve of his polices are most likely to believe immigration should be harder, while much fewer of respondents who dislike Trump and disapprove of his policies believe immigration should be harder.

kable(MyVoterData %>% 
  group_by(FT_Trump) %>% 
  filter(!is.na(FT_Trump)) %>% 
  summarize(avg_ft_immig = mean(ft_immig_2017, na.rm = TRUE))
) %>% 
  kable_styling(bootstrap_options = c("striped", "condensed"), full_width = T) %>% 
  column_spec(1, bold = T)

FT_Trump	avg_ft_immig
Dislike and Disapprove of his Policies	72.72559
Dislike but Approve of his Policies	54.46392
Like and Approve of his Policies	47.49843
Like but Disapprove of his Policies	54.12329

The table shows that on average, people who dislike Trump and disapprove of his policies have much higher feelings toward immigrants than any other category.

---

Are people who follow politics or current events more or less likely to want immigration to be easier?

kable(round(prop.table(table(MyVoterData$Politics_OR_Current_Events, MyVoterData$Immigration_Should_Be),1),2)) %>% 
  kable_styling(bootstrap_options = c("striped", "condensed"), full_width = T) %>% 
  column_spec(1, bold = T)

	Much Easier	Slightly Easier	No Change	Slightly Harder	Much Harder	Don't Know
Very Interested	0.11	0.20	0.25	0.18	0.23	0.03
Somewhat Interested	0.06	0.14	0.27	0.22	0.25	0.07
Not Very Interested	0.05	0.10	0.24	0.22	0.28	0.11
Nothing	0.07	0.04	0.22	0.26	0.19	0.22

# Observed Frequencies
chisq.test(MyVoterData$Politics_OR_Current_Events, MyVoterData$Immigration_Should_Be)[6]

$observed
                     
                      Much Easier Slightly Easier No Change Slightly Harder Much Harder Don't Know
  Very Interested             306             563       715             501         655         92
  Somewhat Interested          81             181       358             284         325         90
  Not Very Interested          13              28        64              60          77         30
  Nothing                       2               1         6               7           5          6

# Expected Frequencies
chisq.test(MyVoterData$Politics_OR_Current_Events, MyVoterData$Immigration_Should_Be)[7]

$expected
                     
                      Much Easier Slightly Easier  No Change Slightly Harder Much Harder Don't Know
  Very Interested      255.834607      491.940674 727.410337      542.216629  675.861573 138.736180
  Somewhat Interested  119.154607      229.120674 338.790337      252.536629  314.781573  64.616180
  Not Very Interested   24.571685       47.248539  69.864270       52.077303   64.913258  13.324944
  Nothing                2.439101        4.690112   6.935056        5.169438    6.443596   1.322697

# Chi-Squared Test
chisq.test(MyVoterData$Politics_OR_Current_Events, MyVoterData$Immigration_Should_Be)

    Pearson's Chi-squared test

data:  MyVoterData$Politics_OR_Current_Events and MyVoterData$Immigration_Should_Be
X-squared = 136.2, df = 15, p-value < 0.00000000000000022

There is a statisticaly significant association between following politics or current events and feelings toward changing immigration laws. The crosstabs reveal that respondents who are more interested in politics or current events are more likely to believe that immigration should be easier, while respondents who have no interest have the highest proportion of respondents who do not know how they feel toward immigration policies.

kable(MyVoterData %>% 
  group_by(Politics_OR_Current_Events) %>% 
  filter(!is.na(Politics_OR_Current_Events)) %>% 
  summarize(avg_ft_immig = mean(ft_immig_2017, na.rm = TRUE))
) %>% 
  kable_styling(bootstrap_options = c("striped", "condensed"), full_width = T) %>% 
  column_spec(1, bold = T)

Politics_OR_Current_Events	avg_ft_immig
Very Interested	63.45345
Somewhat Interested	59.21726
Not Very Interested	55.12607
Nothing	60.68571

The table shows that on average, people who are very interested in politics or current events have the highest feelings toward immigrants; however, people who have no interest have the second highest feelings toward immigrants.