Title: A Comparative Statistical Analysis of Different Colours
Author: Madhura Gaokar -63
Introduction:
Colours play an important role in shaping human perception and preferences. This study focuses on four colours—White, Blue, Black, and Pink. White is associated with purity and simplicity, blue with calmness and trust. Black represents elegance and power, while pink reflects softness and warmth. The study aims to compare these colours to understand differences in ratings and preferences.
Objective:
To analyze the ratings of different colours using one-way ANOVA in order to determine whether significant differences exist among them.
Literature review:
1.Colour Psychology and Human Perception
Elliot (2015) reviews theoretical and empirical research on colour and psychological functioning, highlighting that colours influence human emotions, cognition, and behavior. The study explains that different hues (such as blue, red, and green) carry specific psychological associations and can affect attention, mood, and decision-making. It also emphasizes that while colour has strong effects, results may vary depending on context and experimental conditions.
2.Colour Preference and Statistical Analysis
Schloss and Palmer (2011) examine aesthetic responses to colour combinations and individual preferences using experimental data. Their study shows that people demonstrate consistent patterns in colour preference, influenced by factors such as harmony, similarity, and past experiences. Similarly, research on colour emotion and preference (2017) indicates that attributes like hue, lightness, and chroma significantly affect how individuals rate colours, making statistical techniques like ANOVA useful for comparing these preferences.
Data collection:
The data for this study was collected using primary research methods via a structured survey distributed through Google Forms. A total of 40 responses were recorded for each colour. Participants were asked to rate the colours—White, Blue, Black, and Pink—on a scale of 1 to 10 based on their visual appeal and personal preference. A One-Way ANOVA was calculated on the compiled data.
Data Analysis:
Anova: Single Factor
SUMMARY
|
Groups |
Count |
Sum |
Average |
Variance |
|
White |
40 |
334 |
8.35 |
4.233333 |
|
Blue |
40 |
314 |
7.85 |
3.925641 |
|
Black |
40 |
325 |
8.125 |
5.753205 |
|
Pink |
40 |
230 |
5.75 |
5.935897 |
ANOVA
|
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
|
Between Groups |
171.8688 |
3 |
57.28958 |
11.54562 |
7.07E-07 |
2.662569 |
|
Within Groups |
774.075 |
156 |
4.962019 |
|||
|
Total |
945.9438 |
159 |
|
|
|
|
H0: White=Blue=Black=Pink
H1: Any one of them is different.
Conclusion:
As calculated, F (11.54562) is greater than F crit (2.662569). Therefore, we reject H0 and accept H1, meaning any one of them is different.
References:
1.Elliot, A. J. (2015). Color and psychological functioning: A review of theoretical and empirical work. Frontiers in Psychology, 6, 368.
2.Schloss, K. B., Hawthorne-Madell, D., & Palmer, S. E. (2011). Ecological influences on individual differences in color preference. Attention, Perception, & Psychophysics, 77(8), 2803–2816.