Opposite Season Preference Analysis

Process the data

Category Proportion (%) Type
SummerGroup 53.1 Birth Group
WinterGroup 46.9 Birth Group
Summer 28.7 Birth Season
Autumn 24.4 Birth Season
Winter 23.8 Birth Season
Spring 23.1 Birth Season
WinterGroup 75.0 Preferred Group
SummerGroup 25.0 Preferred Group
Winter 54.4 Preferred Season
Spring 20.6 Preferred Season
Autumn 13.8 Preferred Season
Summer 11.2 Preferred Season

Binomial test for preference of opposite group


    Exact binomial test

data:  successes_2 and n_2
number of successes = 83, number of trials = 160, p-value = 0.3464
alternative hypothesis: true probability of success is greater than 0.5
95 percent confidence interval:
 0.450805 1.000000
sample estimates:
probability of success 
               0.51875

Out of 160 people, 83 (about 51.9%) preferred a season opposite to the one they were born in. Although this is slightly more than half, the result is not statistically significant (p = 0.346), meaning it could easily be due to random chance. The 95% confidence interval ranges from about 45.1% to 100%, so we cannot confidently say that people generally prefer opposite seasons.

Association Tests


    Pearson's Chi-squared test

data:  chi_table_4
X-squared = 5.6844, df = 9, p-value = 0.771
[1] "Cramer's V: 0.11"

The chi-square test showed no significant association between birth season and preferred season (p = 0.771), meaning the pattern of preferences could be due to chance. The Cramer’s V value of 0.11 indicates a very weak relationship, suggesting that birth season has little to no meaningful influence on preferred season in this dataset.

Correlation / Rank Agreement


    Spearman's rank correlation rho

data:  processed_data$birth_season_num and processed_data$preferred_season_num
S = 657770, p-value = 0.6474
alternative hypothesis: true rho is not equal to 0
sample estimates:
       rho 
0.03643167 

    Kendall's rank correlation tau

data:  processed_data$birth_season_num and processed_data$preferred_season_num
z = 0.45019, p-value = 0.6526
alternative hypothesis: true tau is not equal to 0
sample estimates:
       tau 
0.03049365 
 Cohen's Kappa for 2 Raters (Weights: unweighted)

 Subjects = 160 
   Raters = 2 
    Kappa = 0.0344 

        z = 0.839 
  p-value = 0.401

The results from Spearman’s rho (ρ = 0.036, p = 0.647), Kendall’s tau (τ = 0.030, p = 0.653), and Cohen’s kappa (κ = 0.034, p = 0.401) all show that there is no meaningful correlation or agreement between a person’s birth season and their preferred season. The correlations are very close to zero, meaning there’s essentially no trend, and the p-values are far above 0.05, so these small differences are likely due to random chance rather than a real relationship.

Done By Ahmed ElSaeed