ASSIGNMENT 1 607

Analysis of Americans’ concen regarding COVID 19 and President’s Trumps approval rate:

For the purpose of this analysis an article from FiveThrirtyEight named “How Americans View The Coronavirus Crisis And Trump’s Response” was chosen. This article quantifies that the AmericanS’ concern about getting infected with COVID 19. The article also illustrates their concern about economy.

link

setwd("C:/Users/malia/OneDrive/Desktop/MSDS DATA 607")
library(tidyverse)

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## v readr   1.3.1     v forcats 0.5.0

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library(magrittr)

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library(foreign)
library(descr)
library(lubridate)

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library(expss)

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library(readr)
library(dplyr)
library(ggplot2)
library(Hmisc)

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Loading data frame.

COVID_CONCERN <- read_csv("https://raw.githubusercontent.com/fivethirtyeight/covid-19-polls/master/covid_concern_polls_adjusted.csv")

## Parsed with column specification:
## cols(
##   .default = col_double(),
##   subject = col_character(),
##   modeldate = col_character(),
##   party = col_character(),
##   startdate = col_character(),
##   enddate = col_character(),
##   pollster = col_character(),
##   grade = col_character(),
##   population = col_character(),
##   multiversions = col_logical(),
##   tracking = col_logical(),
##   timestamp = col_character(),
##   url = col_character()
## )

## See spec(...) for full column specifications.

link

head(COVID_CONCERN)

## # A tibble: 6 x 23
##   subject modeldate party startdate enddate pollster grade samplesize population
##   <chr>   <chr>     <chr> <chr>     <chr>   <chr>    <chr>      <dbl> <chr>     
## 1 concer~ 1/20/2021 all   1/27/2020 1/29/2~ Morning~ B/C         2202 a         
## 2 concer~ 1/20/2021 all   1/31/2020 2/2/20~ Morning~ B/C         2202 a         
## 3 concer~ 1/20/2021 all   2/7/2020  2/9/20~ Morning~ B/C         2200 a         
## 4 concer~ 1/20/2021 all   2/13/2020 2/18/2~ Kaiser ~ <NA>        1207 a         
## 5 concer~ 1/20/2021 all   2/24/2020 2/26/2~ Morning~ B/C         2200 a         
## 6 concer~ 1/20/2021 all   2/27/2020 2/27/2~ SurveyM~ <NA>        1051 a         
## # ... with 14 more variables: weight <dbl>, influence <dbl>,
## #   multiversions <lgl>, tracking <lgl>, very <dbl>, somewhat <dbl>,
## #   not_very <dbl>, not_at_all <dbl>, very_adjusted <dbl>,
## #   somewhat_adjusted <dbl>, not_very_adjusted <dbl>,
## #   not_at_all_adjusted <dbl>, timestamp <chr>, url <chr>

covid_approval_polls_n<-read_csv("https://raw.githubusercontent.com/fivethirtyeight/covid-19-polls/master/covid_approval_polls.csv")

## Parsed with column specification:
## cols(
##   start_date = col_date(format = ""),
##   end_date = col_date(format = ""),
##   pollster = col_character(),
##   sponsor = col_character(),
##   sample_size = col_double(),
##   population = col_character(),
##   party = col_character(),
##   subject = col_character(),
##   tracking = col_logical(),
##   text = col_character(),
##   approve = col_double(),
##   disapprove = col_double(),
##   url = col_character()
## )

Subsetting the data frame for the convinience of analysis.

subset_COVID_CONCERN<-subset(COVID_CONCERN,select=c(subject,party,startdate,enddate,very,somewhat,not_very,not_at_all))
head(subset_COVID_CONCERN)

## # A tibble: 6 x 8
##   subject         party startdate enddate    very somewhat not_very not_at_all
##   <chr>           <chr> <chr>     <chr>     <dbl>    <dbl>    <dbl>      <dbl>
## 1 concern-economy all   1/27/2020 1/29/2020    19       33       23         11
## 2 concern-economy all   1/31/2020 2/2/2020     26       32       25          7
## 3 concern-economy all   2/7/2020  2/9/2020     23       32       24          9
## 4 concern-economy all   2/13/2020 2/18/2020    22       35       28         15
## 5 concern-economy all   2/24/2020 2/26/2020    32       37       18          6
## 6 concern-economy all   2/27/2020 2/27/2020    41       37       14          5

subset_COVID_APPROVAL<-subset(COVID_CONCERN,select=c(subject,party,startdate,enddate,very,somewhat,not_very,not_at_all))
head(subset_COVID_CONCERN)

## # A tibble: 6 x 8
##   subject         party startdate enddate    very somewhat not_very not_at_all
##   <chr>           <chr> <chr>     <chr>     <dbl>    <dbl>    <dbl>      <dbl>
## 1 concern-economy all   1/27/2020 1/29/2020    19       33       23         11
## 2 concern-economy all   1/31/2020 2/2/2020     26       32       25          7
## 3 concern-economy all   2/7/2020  2/9/2020     23       32       24          9
## 4 concern-economy all   2/13/2020 2/18/2020    22       35       28         15
## 5 concern-economy all   2/24/2020 2/26/2020    32       37       18          6
## 6 concern-economy all   2/27/2020 2/27/2020    41       37       14          5

head(covid_approval_polls_n)

## # A tibble: 6 x 13
##   start_date end_date   pollster sponsor sample_size population party subject
##   <date>     <date>     <chr>    <chr>         <dbl> <chr>      <chr> <chr>  
## 1 2020-02-02 2020-02-04 YouGov   Econom~        1500 a          all   Trump  
## 2 2020-02-02 2020-02-04 YouGov   Econom~         376 a          R     Trump  
## 3 2020-02-02 2020-02-04 YouGov   Econom~         523 a          D     Trump  
## 4 2020-02-02 2020-02-04 YouGov   Econom~         599 a          I     Trump  
## 5 2020-02-07 2020-02-09 Morning~ <NA>           2200 a          all   Trump  
## 6 2020-02-07 2020-02-09 Morning~ <NA>            684 a          R     Trump  
## # ... with 5 more variables: tracking <lgl>, text <chr>, approve <dbl>,
## #   disapprove <dbl>, url <chr>

subset_COVID_APPROVAL_POLLS<-subset(covid_approval_polls_n,select=c(pollster,sample_size,party,approve,disapprove))
head(subset_COVID_APPROVAL_POLLS)

## # A tibble: 6 x 5
##   pollster        sample_size party approve disapprove
##   <chr>                 <dbl> <chr>   <dbl>      <dbl>
## 1 YouGov                 1500 all        42         29
## 2 YouGov                  376 R          75          6
## 3 YouGov                  523 D          21         51
## 4 YouGov                  599 I          39         25
## 5 Morning Consult        2200 all        57         22
## 6 Morning Consult         684 R          88          4

Omitting na variables

na.omit(subset_COVID_CONCERN)

## # A tibble: 552 x 8
##    subject         party startdate enddate    very somewhat not_very not_at_all
##    <chr>           <chr> <chr>     <chr>     <dbl>    <dbl>    <dbl>      <dbl>
##  1 concern-economy all   1/27/2020 1/29/2020    19       33       23         11
##  2 concern-economy all   1/31/2020 2/2/2020     26       32       25          7
##  3 concern-economy all   2/7/2020  2/9/2020     23       32       24          9
##  4 concern-economy all   2/13/2020 2/18/2020    22       35       28         15
##  5 concern-economy all   2/24/2020 2/26/2020    32       37       18          6
##  6 concern-economy all   2/27/2020 2/27/2020    41       37       14          5
##  7 concern-economy all   2/28/2020 3/1/2020     38       33       13          5
##  8 concern-economy all   3/2/2020  3/3/2020     36       36       21          6
##  9 concern-economy all   3/3/2020  3/5/2020     38       37       12          5
## 10 concern-economy all   3/2/2020  3/5/2020     34       40       19          6
## # ... with 542 more rows

The cross tabulatation refers that people are concerned about COVID 19.

 crosstab(subset_COVID_CONCERN$subject, subset_COVID_CONCERN$very, prop.r = T, chisq = T, dnn=c("COVID-CONCERN", "Very Concerned about COVID"))

## Warning in chisq.test(tab, correct = FALSE, ...): Chi-squared approximation may
## be incorrect

##    Cell Contents 
## |-------------------------|
## |                   Count | 
## |             Row Percent | 
## |-------------------------|
## 
## ==============================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================
##          Very Concerned about COVID
## COVID        8       9      10      11      12      13      14      15      16      18      19      20      21      22    22.8      23    23.1    23.5    23.7    23.9      24    24.6   24.83      25    25.5      26    26.5    26.8      27    27.4    27.5    27.6    27.8      28    28.4    28.5    28.6   28.75    28.9      29    29.5    29.7    29.8   29.98      30    30.5   30.63      31    31.4    31.5    31.6      32    32.2    32.4    32.5   32.55   32.71      33   33.09   33.67      34   34.45    34.5   34.67   34.82   34.86   34.92      35    35.5   35.51   35.75      36   36.21   36.47    36.5      37    37.5      38    38.5      39   39.47    39.5      40    40.5      41    41.5      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   Total
## ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
## cncr-       0       0       0       0       0       0       0       0       0       0       1       0       0       1       0       1       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       2       0       0       0       0       0       1       0       0       1       0       0       0       0       0       0       1       0       0       0       4       0       0       0       0       0       2       0       0       0       0       2       0       2       0       3       2       9      12       3      14       9       8       7       6       9       4       7       5       6       8       7       8       6      15       5       3       4       3       4       4       1       3       1       2       1       1     199 
##           0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.5%    0.0%    0.0%    0.5%    0.0%    0.5%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.5%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    1.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.5%    0.0%    0.0%    0.5%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.5%    0.0%    0.0%    0.0%    2.0%    0.0%    0.0%    0.0%    0.0%    0.0%    1.0%    0.0%    0.0%    0.0%    0.0%    1.0%    0.0%    1.0%    0.0%    1.5%    1.0%    4.5%    6.0%    1.5%    7.0%    4.5%    4.0%    3.5%    3.0%    4.5%    2.0%    3.5%    2.5%    3.0%    4.0%    3.5%    4.0%    3.0%    7.5%    2.5%    1.5%    2.0%    1.5%    2.0%    2.0%    0.5%    1.5%    0.5%    1.0%    0.5%    0.5%   35.9%
## ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
## cncr-       1       4       3       5       7       2       4       3       5       2       3       8       6      16       1       7       1       1       1       1      14       1       1       9       1      17       2       1       6       1       2       1       1       9       1       2       1       1       1       8       1       2       1       1      12       1       1       8       1       1       1       6       1       1       2       1       1       7       1       1       8       1       4       1       2       1       1       9       2       1       1      10       1       1       6      16       4      13       4       3       1       2       4       1       6       2       7       4       1       3       5       6       2       5       4       1       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0       0       0       0       0       0       0       0     356 
##           0.3%    1.1%    0.8%    1.4%    2.0%    0.6%    1.1%    0.8%    1.4%    0.6%    0.8%    2.2%    1.7%    4.5%    0.3%    2.0%    0.3%    0.3%    0.3%    0.3%    3.9%    0.3%    0.3%    2.5%    0.3%    4.8%    0.6%    0.3%    1.7%    0.3%    0.6%    0.3%    0.3%    2.5%    0.3%    0.6%    0.3%    0.3%    0.3%    2.2%    0.3%    0.6%    0.3%    0.3%    3.4%    0.3%    0.3%    2.2%    0.3%    0.3%    0.3%    1.7%    0.3%    0.3%    0.6%    0.3%    0.3%    2.0%    0.3%    0.3%    2.2%    0.3%    1.1%    0.3%    0.6%    0.3%    0.3%    2.5%    0.6%    0.3%    0.3%    2.8%    0.3%    0.3%    1.7%    4.5%    1.1%    3.7%    1.1%    0.8%    0.3%    0.6%    1.1%    0.3%    1.7%    0.6%    2.0%    1.1%    0.3%    0.8%    1.4%    1.7%    0.6%    1.4%    1.1%    0.3%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.3%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%    0.0%   64.1%
## ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
## Total       1       4       3       5       7       2       4       3       5       2       4       8       6      17       1       8       1       1       1       1      14       1       1       9       1      18       2       1       6       1       2       1       1       9       1       2       1       1       1       8       1       2       1       1      12       1       1       8       1       1       1       8       1       1       2       1       1       8       1       1       9       1       4       1       2       1       1      10       2       1       1      14       1       1       6      16       4      15       4       3       1       2       6       1       8       2      10       6      10      15       8      20      11      13      11       7       9       4       7       5       6       8       7       8       7      15       5       3       4       3       4       4       1       3       1       2       1       1     555 
## ==============================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================
## 
## Statistics for All Table Factors
## 
## Pearson's Chi-squared test 
## ------------------------------------------------------------
## Chi^2 = 394.6496      d.f. = 117      p <2e-16 
## 
##         Minimum expected frequency: 0.3585586 
## Cells with Expected Frequency < 5: 197 of 236 (83.47458%)

Filtering data on the basis of concern level:

subset_COVID_CONCERN %>%
  select(subject,startdate,very)%>%
  filter(startdate %in% c("7/3/2020","7/5/2020,9/25/2020","10/16/2020"),subject%in%c("concern-infected"))

## # A tibble: 5 x 3
##   subject          startdate   very
##   <chr>            <chr>      <dbl>
## 1 concern-infected 7/3/2020      24
## 2 concern-infected 7/3/2020      35
## 3 concern-infected 10/16/2020    24
## 4 concern-infected 10/16/2020    26
## 5 concern-infected 10/16/2020    49

subset_COVID_CONCERN %>%
  select(subject,startdate,not_at_all)%>%
  filter(startdate %in% c("7/3/2020","7/5/2020","9/25/2020","10/16/2020"),subject%in%c("concern-infected"))

## # A tibble: 7 x 3
##   subject          startdate  not_at_all
##   <chr>            <chr>           <dbl>
## 1 concern-infected 7/3/2020           15
## 2 concern-infected 7/3/2020           10
## 3 concern-infected 7/5/2020           13
## 4 concern-infected 9/25/2020          16
## 5 concern-infected 10/16/2020         15
## 6 concern-infected 10/16/2020         14
## 7 concern-infected 10/16/2020         NA

subset_COVID_CONCERN %>%
  select(subject,startdate,very)%>%
  filter(startdate %in% c("9/7/2020","9/28/2020"),subject%in%c("concern-economy"))

## # A tibble: 2 x 3
##   subject         startdate  very
##   <chr>           <chr>     <dbl>
## 1 concern-economy 9/7/2020     62
## 2 concern-economy 9/28/2020    61

subset_COVID_CONCERN %>%
  select(subject,startdate,not_at_all)%>%
  filter(startdate %in% c("9/25/2020","10/16/2020"),subject%in%c("concern-economy"))

## # A tibble: 1 x 3
##   subject         startdate not_at_all
##   <chr>           <chr>          <dbl>
## 1 concern-economy 9/25/2020          2

Filtering data on the basis of approval and disapproval of response of the President Trump regarding the COVID 19.A certain pollster named Morning-Consult whish has bigger sample size, and party variable has alsoo been filtered to have a microsopic understanding regarding the approval/disapproval data.

subset_COVID_APPROVAL_POLLS %>%
  select(pollster,party,approve,disapprove)%>%
  filter(pollster %in% c("Morning Consult"))

## # A tibble: 331 x 4
##    pollster        party approve disapprove
##    <chr>           <chr>   <dbl>      <dbl>
##  1 Morning Consult all        57         22
##  2 Morning Consult R          88          4
##  3 Morning Consult D          37         37
##  4 Morning Consult I          50         22
##  5 Morning Consult all        39         35
##  6 Morning Consult R          71          8
##  7 Morning Consult D          15         60
##  8 Morning Consult I          34         33
##  9 Morning Consult all        54         27
## 10 Morning Consult R          84          7
## # ... with 321 more rows

histogram(subset_COVID_APPROVAL_POLLS$approve,main = "Histogram 1",xlab = "Trends for approval for the President Trump",col = "blue")

histogram(subset_COVID_APPROVAL_POLLS$disapprove,main = "Histogram 2",xlab = "Trends for disapproval for the President Trump",col = "red")

ggplot()+
  geom_line(data=subset_COVID_CONCERN$very.graph,aes(x=subset_COVID_CONCERN$subject,y=subset_COVID_CONCERN$very))+labs(title="Trends in support for anti-miscgeny laws from 1970 to 2010, GSS", x="subject",y="Proportions")

## Warning: Unknown or uninitialised column: `very.graph`.

Conclusion:

After conducting analysis through subsetting and filtering it appears that Americans are definitely concerned about COVID-19. However, people from the United States are likely to be more concerned about economy than getting infected. Moreover, people are likely to disprove President Trump’s response rather than approving. The concerned attitude and disapproval towards President Trump’s response to the crisis might have affected the election outcome against President Trump.