Chi-square test for Independence

#Data

library(readxl)
DataSittie <- read_excel("D:/stat 50/DataSittie.xlsx")

## New names:
## * `` -> ...63
## * `` -> ...64

View(DataSittie)

library(DescTools)

## Warning: package 'DescTools' was built under R version 4.1.3

Is there any significant relationship between the demographic and adherence towards their perceived effectiveness of health countermeasures?

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

LC<- DataSittie %>%
      mutate(Agegroup = ifelse(Age <= 2,"at most 35 years old","More than 35 years old"))%>%
    mutate(EducationCode = ifelse(Education <= 3,"at most High School Level","at least High School Graduate"))%>%
    mutate(Incomecode =ifelse(Income<=2, "at most Php10,000", "More than Php10,000"))

##Over-all and Perceived Effectiveness

table(LC$OverallLevel)

## 
##      High       Low    Medium Very High 
##        59         6        19        12

prop.table(table(LC$OverallLevel))

## 
##      High       Low    Medium Very High 
## 0.6145833 0.0625000 0.1979167 0.1250000

Significant Relationship

##Overall and Effectiveness

library(gmodels)

## Warning: package 'gmodels' was built under R version 4.1.3

## Registered S3 method overwritten by 'gdata':
##   method         from     
##   reorder.factor DescTools

Crosstabdata<-CrossTable(LC$OverallLevel, LC$III)

## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## | Chi-square contribution |
## |           N / Row Total |
## |           N / Col Total |
## |         N / Table Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  96 
## 
##  
##                 | LC$III 
## LC$OverallLevel |         1 |         2 | Row Total | 
## ----------------|-----------|-----------|-----------|
##            High |        46 |        13 |        59 | 
##                 |     0.729 |     1.604 |           | 
##                 |     0.780 |     0.220 |     0.615 | 
##                 |     0.697 |     0.433 |           | 
##                 |     0.479 |     0.135 |           | 
## ----------------|-----------|-----------|-----------|
##             Low |         2 |         4 |         6 | 
##                 |     1.095 |     2.408 |           | 
##                 |     0.333 |     0.667 |     0.062 | 
##                 |     0.030 |     0.133 |           | 
##                 |     0.021 |     0.042 |           | 
## ----------------|-----------|-----------|-----------|
##          Medium |         6 |        13 |        19 | 
##                 |     3.818 |     8.401 |           | 
##                 |     0.316 |     0.684 |     0.198 | 
##                 |     0.091 |     0.433 |           | 
##                 |     0.062 |     0.135 |           | 
## ----------------|-----------|-----------|-----------|
##       Very High |        12 |         0 |        12 | 
##                 |     1.705 |     3.750 |           | 
##                 |     1.000 |     0.000 |     0.125 | 
##                 |     0.182 |     0.000 |           | 
##                 |     0.125 |     0.000 |           | 
## ----------------|-----------|-----------|-----------|
##    Column Total |        66 |        30 |        96 | 
##                 |     0.688 |     0.312 |           | 
## ----------------|-----------|-----------|-----------|
## 
##

Crosstabdata

## $t
##            y
## x            1  2
##   High      46 13
##   Low        2  4
##   Medium     6 13
##   Very High 12  0
## 
## $prop.row
##            y
## x                   1         2
##   High      0.7796610 0.2203390
##   Low       0.3333333 0.6666667
##   Medium    0.3157895 0.6842105
##   Very High 1.0000000 0.0000000
## 
## $prop.col
##            y
## x                    1          2
##   High      0.69696970 0.43333333
##   Low       0.03030303 0.13333333
##   Medium    0.09090909 0.43333333
##   Very High 0.18181818 0.00000000
## 
## $prop.tbl
##            y
## x                    1          2
##   High      0.47916667 0.13541667
##   Low       0.02083333 0.04166667
##   Medium    0.06250000 0.13541667
##   Very High 0.12500000 0.00000000

table2=matrix(c(8,17,58,15) ,ncol=2) 
colnames(table2)=c("Yes", "No") 
rownames(table2)=c("Low and Medium", "High and Very High")
table2

##                    Yes No
## Low and Medium       8 58
## High and Very High  17 15

chisq.test(table2)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  table2
## X-squared = 16.971, df = 1, p-value = 3.795e-05

CramerV(table2)

## [1] 0.4411025

##Public Market

library(gmodels)
Crosstabdata<-CrossTable(LC$PubLevel, LC$III)

## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## | Chi-square contribution |
## |           N / Row Total |
## |           N / Col Total |
## |         N / Table Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  96 
## 
##  
##              | LC$III 
##  LC$PubLevel |         1 |         2 | Row Total | 
## -------------|-----------|-----------|-----------|
##         High |        26 |         7 |        33 | 
##              |     0.484 |     1.064 |           | 
##              |     0.788 |     0.212 |     0.344 | 
##              |     0.394 |     0.233 |           | 
##              |     0.271 |     0.073 |           | 
## -------------|-----------|-----------|-----------|
##          Low |        14 |        11 |        25 | 
##              |     0.591 |     1.300 |           | 
##              |     0.560 |     0.440 |     0.260 | 
##              |     0.212 |     0.367 |           | 
##              |     0.146 |     0.115 |           | 
## -------------|-----------|-----------|-----------|
##       Medium |        19 |        12 |        31 | 
##              |     0.251 |     0.552 |           | 
##              |     0.613 |     0.387 |     0.323 | 
##              |     0.288 |     0.400 |           | 
##              |     0.198 |     0.125 |           | 
## -------------|-----------|-----------|-----------|
##    Very High |         7 |         0 |         7 | 
##              |     0.994 |     2.188 |           | 
##              |     1.000 |     0.000 |     0.073 | 
##              |     0.106 |     0.000 |           | 
##              |     0.073 |     0.000 |           | 
## -------------|-----------|-----------|-----------|
## Column Total |        66 |        30 |        96 | 
##              |     0.688 |     0.312 |           | 
## -------------|-----------|-----------|-----------|
## 
##

Crosstabdata

## $t
##            y
## x            1  2
##   High      26  7
##   Low       14 11
##   Medium    19 12
##   Very High  7  0
## 
## $prop.row
##            y
## x                   1         2
##   High      0.7878788 0.2121212
##   Low       0.5600000 0.4400000
##   Medium    0.6129032 0.3870968
##   Very High 1.0000000 0.0000000
## 
## $prop.col
##            y
## x                   1         2
##   High      0.3939394 0.2333333
##   Low       0.2121212 0.3666667
##   Medium    0.2878788 0.4000000
##   Very High 0.1060606 0.0000000
## 
## $prop.tbl
##            y
## x                    1          2
##   High      0.27083333 0.07291667
##   Low       0.14583333 0.11458333
##   Medium    0.19791667 0.12500000
##   Very High 0.07291667 0.00000000

table2=matrix(c(33,23,33,7) ,ncol=2) 
colnames(table2)=c("Yes", "No") 
rownames(table2)=c("Low and Medium", "High and Very High")
table2

##                    Yes No
## Low and Medium      33 33
## High and Very High  23  7

chisq.test(table2)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  table2
## X-squared = 4.987, df = 1, p-value = 0.02554

CramerV(table2)

## [1] 0.2507133

Bus Terminal

library(gmodels)
Crosstabdata<-CrossTable(LC$BusLevel, LC$III)

## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## | Chi-square contribution |
## |           N / Row Total |
## |           N / Col Total |
## |         N / Table Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  96 
## 
##  
##              | LC$III 
##  LC$BusLevel |         1 |         2 | Row Total | 
## -------------|-----------|-----------|-----------|
##         High |        28 |        11 |        39 | 
##              |     0.053 |     0.116 |           | 
##              |     0.718 |     0.282 |     0.406 | 
##              |     0.424 |     0.367 |           | 
##              |     0.292 |     0.115 |           | 
## -------------|-----------|-----------|-----------|
##          Low |         7 |         6 |        13 | 
##              |     0.420 |     0.924 |           | 
##              |     0.538 |     0.462 |     0.135 | 
##              |     0.106 |     0.200 |           | 
##              |     0.073 |     0.062 |           | 
## -------------|-----------|-----------|-----------|
##       Medium |        16 |        12 |        28 | 
##              |     0.549 |     1.207 |           | 
##              |     0.571 |     0.429 |     0.292 | 
##              |     0.242 |     0.400 |           | 
##              |     0.167 |     0.125 |           | 
## -------------|-----------|-----------|-----------|
##    Very High |        15 |         1 |        16 | 
##              |     1.455 |     3.200 |           | 
##              |     0.938 |     0.062 |     0.167 | 
##              |     0.227 |     0.033 |           | 
##              |     0.156 |     0.010 |           | 
## -------------|-----------|-----------|-----------|
## Column Total |        66 |        30 |        96 | 
##              |     0.688 |     0.312 |           | 
## -------------|-----------|-----------|-----------|
## 
##

Crosstabdata

## $t
##            y
## x            1  2
##   High      28 11
##   Low        7  6
##   Medium    16 12
##   Very High 15  1
## 
## $prop.row
##            y
## x                   1         2
##   High      0.7179487 0.2820513
##   Low       0.5384615 0.4615385
##   Medium    0.5714286 0.4285714
##   Very High 0.9375000 0.0625000
## 
## $prop.col
##            y
## x                    1          2
##   High      0.42424242 0.36666667
##   Low       0.10606061 0.20000000
##   Medium    0.24242424 0.40000000
##   Very High 0.22727273 0.03333333
## 
## $prop.tbl
##            y
## x                    1          2
##   High      0.29166667 0.11458333
##   Low       0.07291667 0.06250000
##   Medium    0.16666667 0.12500000
##   Very High 0.15625000 0.01041667

table2=matrix(c(23,18,58,13) ,ncol=2) 
colnames(table2)=c("Yes", "No") 
rownames(table2)=c("Low and Medium", "High and Very High")
table2

##                    Yes No
## Low and Medium      23 58
## High and Very High  18 13

chisq.test(table2)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  table2
## X-squared = 7.2739, df = 1, p-value = 0.006996

CramerV(table2)

## [1] 0.2755572

Bus Terminal

library(gmodels)
Crosstabdata<-CrossTable(LC$BusLevel, LC$III)

## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## | Chi-square contribution |
## |           N / Row Total |
## |           N / Col Total |
## |         N / Table Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  96 
## 
##  
##              | LC$III 
##  LC$BusLevel |         1 |         2 | Row Total | 
## -------------|-----------|-----------|-----------|
##         High |        28 |        11 |        39 | 
##              |     0.053 |     0.116 |           | 
##              |     0.718 |     0.282 |     0.406 | 
##              |     0.424 |     0.367 |           | 
##              |     0.292 |     0.115 |           | 
## -------------|-----------|-----------|-----------|
##          Low |         7 |         6 |        13 | 
##              |     0.420 |     0.924 |           | 
##              |     0.538 |     0.462 |     0.135 | 
##              |     0.106 |     0.200 |           | 
##              |     0.073 |     0.062 |           | 
## -------------|-----------|-----------|-----------|
##       Medium |        16 |        12 |        28 | 
##              |     0.549 |     1.207 |           | 
##              |     0.571 |     0.429 |     0.292 | 
##              |     0.242 |     0.400 |           | 
##              |     0.167 |     0.125 |           | 
## -------------|-----------|-----------|-----------|
##    Very High |        15 |         1 |        16 | 
##              |     1.455 |     3.200 |           | 
##              |     0.938 |     0.062 |     0.167 | 
##              |     0.227 |     0.033 |           | 
##              |     0.156 |     0.010 |           | 
## -------------|-----------|-----------|-----------|
## Column Total |        66 |        30 |        96 | 
##              |     0.688 |     0.312 |           | 
## -------------|-----------|-----------|-----------|
## 
##

Crosstabdata

## $t
##            y
## x            1  2
##   High      28 11
##   Low        7  6
##   Medium    16 12
##   Very High 15  1
## 
## $prop.row
##            y
## x                   1         2
##   High      0.7179487 0.2820513
##   Low       0.5384615 0.4615385
##   Medium    0.5714286 0.4285714
##   Very High 0.9375000 0.0625000
## 
## $prop.col
##            y
## x                    1          2
##   High      0.42424242 0.36666667
##   Low       0.10606061 0.20000000
##   Medium    0.24242424 0.40000000
##   Very High 0.22727273 0.03333333
## 
## $prop.tbl
##            y
## x                    1          2
##   High      0.29166667 0.11458333
##   Low       0.07291667 0.06250000
##   Medium    0.16666667 0.12500000
##   Very High 0.15625000 0.01041667

table2=matrix(c(23,18,43,12) ,ncol=2) 
colnames(table2)=c("Yes", "No") 
rownames(table2)=c("Low and Medium", "High and Very High")
table2

##                    Yes No
## Low and Medium      23 43
## High and Very High  18 12

chisq.test(table2)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  table2
## X-squared = 4.354, df = 1, p-value = 0.03692

CramerV(table2)

## [1] 0.2356804

Eatery

library(gmodels)
Crosstabdata<-CrossTable(LC$EatLevel, LC$III)

## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## | Chi-square contribution |
## |           N / Row Total |
## |           N / Col Total |
## |         N / Table Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  96 
## 
##  
##              | LC$III 
##  LC$EatLevel |         1 |         2 | Row Total | 
## -------------|-----------|-----------|-----------|
##         High |        34 |        18 |        52 | 
##              |     0.086 |     0.188 |           | 
##              |     0.654 |     0.346 |     0.542 | 
##              |     0.515 |     0.600 |           | 
##              |     0.354 |     0.188 |           | 
## -------------|-----------|-----------|-----------|
##          Low |         3 |         3 |         6 | 
##              |     0.307 |     0.675 |           | 
##              |     0.500 |     0.500 |     0.062 | 
##              |     0.045 |     0.100 |           | 
##              |     0.031 |     0.031 |           | 
## -------------|-----------|-----------|-----------|
##       Medium |         8 |         8 |        16 | 
##              |     0.818 |     1.800 |           | 
##              |     0.500 |     0.500 |     0.167 | 
##              |     0.121 |     0.267 |           | 
##              |     0.083 |     0.083 |           | 
## -------------|-----------|-----------|-----------|
##    Very High |        21 |         1 |        22 | 
##              |     2.282 |     5.020 |           | 
##              |     0.955 |     0.045 |     0.229 | 
##              |     0.318 |     0.033 |           | 
##              |     0.219 |     0.010 |           | 
## -------------|-----------|-----------|-----------|
## Column Total |        66 |        30 |        96 | 
##              |     0.688 |     0.312 |           | 
## -------------|-----------|-----------|-----------|
## 
##

Crosstabdata

## $t
##            y
## x            1  2
##   High      34 18
##   Low        3  3
##   Medium     8  8
##   Very High 21  1
## 
## $prop.row
##            y
## x                    1          2
##   High      0.65384615 0.34615385
##   Low       0.50000000 0.50000000
##   Medium    0.50000000 0.50000000
##   Very High 0.95454545 0.04545455
## 
## $prop.col
##            y
## x                    1          2
##   High      0.51515152 0.60000000
##   Low       0.04545455 0.10000000
##   Medium    0.12121212 0.26666667
##   Very High 0.31818182 0.03333333
## 
## $prop.tbl
##            y
## x                    1          2
##   High      0.35416667 0.18750000
##   Low       0.03125000 0.03125000
##   Medium    0.08333333 0.08333333
##   Very High 0.21875000 0.01041667

table2=matrix(c(11,11,55,19) ,ncol=2) 
colnames(table2)=c("Yes", "No") 
rownames(table2)=c("Low and Medium", "High and Very High")
table2

##                    Yes No
## Low and Medium      11 55
## High and Very High  11 19

chisq.test(table2)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  table2
## X-squared = 3.6067, df = 1, p-value = 0.05755

CramerV(table2)

## [1] 0.2205644

Mall and Grocery Stores

library(gmodels)
Crosstabdata<-CrossTable(LC$MallLevel, LC$III)

## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## | Chi-square contribution |
## |           N / Row Total |
## |           N / Col Total |
## |         N / Table Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  96 
## 
##  
##              | LC$III 
## LC$MallLevel |         1 |         2 | Row Total | 
## -------------|-----------|-----------|-----------|
##         High |        33 |        14 |        47 | 
##              |     0.015 |     0.032 |           | 
##              |     0.702 |     0.298 |     0.490 | 
##              |     0.500 |     0.467 |           | 
##              |     0.344 |     0.146 |           | 
## -------------|-----------|-----------|-----------|
##          Low |         4 |         4 |         8 | 
##              |     0.409 |     0.900 |           | 
##              |     0.500 |     0.500 |     0.083 | 
##              |     0.061 |     0.133 |           | 
##              |     0.042 |     0.042 |           | 
## -------------|-----------|-----------|-----------|
##       Medium |        13 |        10 |        23 | 
##              |     0.500 |     1.101 |           | 
##              |     0.565 |     0.435 |     0.240 | 
##              |     0.197 |     0.333 |           | 
##              |     0.135 |     0.104 |           | 
## -------------|-----------|-----------|-----------|
##    Very High |        16 |         2 |        18 | 
##              |     1.062 |     2.336 |           | 
##              |     0.889 |     0.111 |     0.188 | 
##              |     0.242 |     0.067 |           | 
##              |     0.167 |     0.021 |           | 
## -------------|-----------|-----------|-----------|
## Column Total |        66 |        30 |        96 | 
##              |     0.688 |     0.312 |           | 
## -------------|-----------|-----------|-----------|
## 
##

Crosstabdata

## $t
##            y
## x            1  2
##   High      33 14
##   Low        4  4
##   Medium    13 10
##   Very High 16  2
## 
## $prop.row
##            y
## x                   1         2
##   High      0.7021277 0.2978723
##   Low       0.5000000 0.5000000
##   Medium    0.5652174 0.4347826
##   Very High 0.8888889 0.1111111
## 
## $prop.col
##            y
## x                    1          2
##   High      0.50000000 0.46666667
##   Low       0.06060606 0.13333333
##   Medium    0.19696970 0.33333333
##   Very High 0.24242424 0.06666667
## 
## $prop.tbl
##            y
## x                    1          2
##   High      0.34375000 0.14583333
##   Low       0.04166667 0.04166667
##   Medium    0.13541667 0.10416667
##   Very High 0.16666667 0.02083333

table2=matrix(c(17,14,49,16) ,ncol=2) 
colnames(table2)=c("Yes", "No") 
rownames(table2)=c("Low and Medium", "High and Very High")
table2

##                    Yes No
## Low and Medium      17 49
## High and Very High  14 16

chisq.test(table2)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  table2
## X-squared = 3.2232, df = 1, p-value = 0.0726

CramerV(table2)

## [1] 0.207267

Church

library(gmodels)
Crosstabdata<-CrossTable(LC$ChurchLevel, LC$III)

## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## | Chi-square contribution |
## |           N / Row Total |
## |           N / Col Total |
## |         N / Table Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  96 
## 
##  
##                | LC$III 
## LC$ChurchLevel |         1 |         2 | Row Total | 
## ---------------|-----------|-----------|-----------|
##           High |        20 |        12 |        32 | 
##                |     0.182 |     0.400 |           | 
##                |     0.625 |     0.375 |     0.333 | 
##                |     0.303 |     0.400 |           | 
##                |     0.208 |     0.125 |           | 
## ---------------|-----------|-----------|-----------|
##            Low |         1 |         2 |         3 | 
##                |     0.547 |     1.204 |           | 
##                |     0.333 |     0.667 |     0.031 | 
##                |     0.015 |     0.067 |           | 
##                |     0.010 |     0.021 |           | 
## ---------------|-----------|-----------|-----------|
##         Medium |         2 |         4 |         6 | 
##                |     1.095 |     2.408 |           | 
##                |     0.333 |     0.667 |     0.062 | 
##                |     0.030 |     0.133 |           | 
##                |     0.021 |     0.042 |           | 
## ---------------|-----------|-----------|-----------|
##      Very High |        43 |        12 |        55 | 
##                |     0.712 |     1.566 |           | 
##                |     0.782 |     0.218 |     0.573 | 
##                |     0.652 |     0.400 |           | 
##                |     0.448 |     0.125 |           | 
## ---------------|-----------|-----------|-----------|
##   Column Total |        66 |        30 |        96 | 
##                |     0.688 |     0.312 |           | 
## ---------------|-----------|-----------|-----------|
## 
##

Crosstabdata

## $t
##            y
## x            1  2
##   High      20 12
##   Low        1  2
##   Medium     2  4
##   Very High 43 12
## 
## $prop.row
##            y
## x                   1         2
##   High      0.6250000 0.3750000
##   Low       0.3333333 0.6666667
##   Medium    0.3333333 0.6666667
##   Very High 0.7818182 0.2181818
## 
## $prop.col
##            y
## x                    1          2
##   High      0.30303030 0.40000000
##   Low       0.01515152 0.06666667
##   Medium    0.03030303 0.13333333
##   Very High 0.65151515 0.40000000
## 
## $prop.tbl
##            y
## x                    1          2
##   High      0.20833333 0.12500000
##   Low       0.01041667 0.02083333
##   Medium    0.02083333 0.04166667
##   Very High 0.44791667 0.12500000

table2=matrix(c(3,6,63,24) ,ncol=2) 
colnames(table2)=c("Yes", "No") 
rownames(table2)=c("Low and Medium", "High and Very High")
table2

##                    Yes No
## Low and Medium       3 63
## High and Very High   6 24

chisq.test(table2)

## Warning in chisq.test(table2): Chi-squared approximation may be incorrect

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  table2
## X-squared = 4.1218, df = 1, p-value = 0.04233

CramerV(table2)

## [1] 0.2457582

Plaza/Recreational ground

library(gmodels)
Crosstabdata<-CrossTable(LC$`PlazaLevel`, LC$III)

## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## | Chi-square contribution |
## |           N / Row Total |
## |           N / Col Total |
## |         N / Table Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  96 
## 
##  
##               | LC$III 
## LC$PlazaLevel |         1 |         2 | Row Total | 
## --------------|-----------|-----------|-----------|
##          High |        14 |         3 |        17 | 
##               |     0.458 |     1.007 |           | 
##               |     0.824 |     0.176 |     0.177 | 
##               |     0.212 |     0.100 |           | 
##               |     0.146 |     0.031 |           | 
## --------------|-----------|-----------|-----------|
##           Low |        25 |        16 |        41 | 
##               |     0.360 |     0.793 |           | 
##               |     0.610 |     0.390 |     0.427 | 
##               |     0.379 |     0.533 |           | 
##               |     0.260 |     0.167 |           | 
## --------------|-----------|-----------|-----------|
##        Medium |        15 |        11 |        26 | 
##               |     0.462 |     1.017 |           | 
##               |     0.577 |     0.423 |     0.271 | 
##               |     0.227 |     0.367 |           | 
##               |     0.156 |     0.115 |           | 
## --------------|-----------|-----------|-----------|
##     Very High |        12 |         0 |        12 | 
##               |     1.705 |     3.750 |           | 
##               |     1.000 |     0.000 |     0.125 | 
##               |     0.182 |     0.000 |           | 
##               |     0.125 |     0.000 |           | 
## --------------|-----------|-----------|-----------|
##  Column Total |        66 |        30 |        96 | 
##               |     0.688 |     0.312 |           | 
## --------------|-----------|-----------|-----------|
## 
##

Crosstabdata

## $t
##            y
## x            1  2
##   High      14  3
##   Low       25 16
##   Medium    15 11
##   Very High 12  0
## 
## $prop.row
##            y
## x                   1         2
##   High      0.8235294 0.1764706
##   Low       0.6097561 0.3902439
##   Medium    0.5769231 0.4230769
##   Very High 1.0000000 0.0000000
## 
## $prop.col
##            y
## x                   1         2
##   High      0.2121212 0.1000000
##   Low       0.3787879 0.5333333
##   Medium    0.2272727 0.3666667
##   Very High 0.1818182 0.0000000
## 
## $prop.tbl
##            y
## x                   1         2
##   High      0.1458333 0.0312500
##   Low       0.2604167 0.1666667
##   Medium    0.1562500 0.1145833
##   Very High 0.1250000 0.0000000

table2=matrix(c(40,27,26,3) ,ncol=2) 
colnames(table2)=c("Yes", "No") 
rownames(table2)=c("Low and Medium", "High and Very High")
table2

##                    Yes No
## Low and Medium      40 26
## High and Very High  27  3

chisq.test(table2)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  table2
## X-squared = 7.1157, df = 1, p-value = 0.007641

CramerV(table2)

## [1] 0.2967249

Chi-square test for Independence

Marvanessa Dinorog

5/20/2022

Is there any significant relationship between the demographic and adherence towards their perceived effectiveness of health countermeasures?

Significant Relationship

Bus Terminal

Bus Terminal

Eatery

Mall and Grocery Stores

Church

Plaza/Recreational ground