Hypotheses

H0 (Null Hypotheses): The observed frequencies matches the expected frequencies. H1 (Alternate Hypotheses): The observed frequencies does not match the expected frequencies.

Result

A Chi-Square Goodness-of-Fit Test was conducted to determine whether dessert type preference (Cheesecake, ChocoCake, Tiramisu) was different from an equal distribution (33.33%, 33.33%, 33.33%) among 548 participants. There was a statistically significant difference in dessert type preferences, χ²(2, N = 548) = 9.67, p < .001.Participants preferred ChocoCake more than Cheesecake or tiramisu. The effect size was moderate (Cohen’s W = 0.31).

R Code

INSTALL REQUIRED PACKAGE The package only needs to be installed once. The code for this task is provided below. Remove the hashtag below to convert the note into code.

LOAD THE PACKAGE You must always reload the package you want to use. The code for this task is provided below. Remove the hashtag below to convert the note into code.

 library(readxl)

IMPORT THE EXCEL FILE INTO R STUDIO

 dataset <- read_excel("C:/Users/hites/Downloads/RQ1.xlsx")

VISUALLY DISPLAY THE DATA

CREATE A FREQUENCY TABE

 observed <- table(dataset$Dessert)

VIEW YOUR FREQUENCY TABLE

 print(observed)
## 
## Cheesecake  ChocoCake   Tiramisu 
##        171        258        119
names(observed)
## [1] "Cheesecake" "ChocoCake"  "Tiramisu"
 expected <- c(1/3, 1/3, 1/3)

CALCULATE CHI-SQUARED RESULTS

 chisq_gfit <- chisq.test(observed, p = expected)
 print(chisq_gfit)
## 
##  Chi-squared test for given probabilities
## 
## data:  observed
## X-squared = 54.004, df = 2, p-value = 1.876e-12
 W <- sqrt(chisq_gfit$statistic / sum(observed))
 W
## X-squared 
## 0.3139217