{"id":23714,"date":"2026-01-07T12:12:37","date_gmt":"2026-01-07T06:42:37","guid":{"rendered":"https:\/\/www.sachdevajk.in\/?p=23714"},"modified":"2026-01-07T12:12:37","modified_gmt":"2026-01-07T06:42:37","slug":"anova-based-comparison-of-bikers-ratings-for-selected-bikes","status":"publish","type":"post","link":"http:\/\/www.sachdevajk.in\/?p=23714","title":{"rendered":"ANOVA-Based Comparison of Bikers\u2019 Ratings for Selected Bikes"},"content":{"rendered":"

Introduction <\/span><\/b><\/p>\n

Customer ratings play a crucial role in evaluating two-wheelers in today\u2019s competitive automobile market. Bikers often rate bikes based on performance, comfort, design, and overall riding experience. These ratings help manufacturers and potential buyers compare different models.<\/span><\/p>\n

This study applies Analysis of Variance (ANOVA) to examine whether there is a significant difference in bikers\u2019 average ratings for selected bikes rated on a scale of 1 to 10.<\/span><\/p>\n

Objectives of the Study<\/span><\/b><\/p>\n

\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><\/span><\/span>To analyze bikers\u2019 ratings for selected bike models.<\/span><\/p>\n

\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><\/span><\/span>To compare the mean ratings of different bikes using ANOVA.<\/span><\/p>\n

\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><\/span><\/span>To determine whether bikers\u2019 ratings differ significantly among the bikes.<\/span><\/p>\n

\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><\/span><\/span>To draw conclusions based on statistical evidence.<\/span><\/p>\n

Literature Review <\/span><\/b><\/p>\n

Previous studies suggest that customer ratings significantly influence automobile purchase decisions. According to Kotler & Keller (2016), consumer perception and satisfaction are key determinants of product success.<\/span><\/p>\n

Research by Malhotra (2019) highlights the usefulness of ANOVA in comparing customer opinions across multiple products, making it a reliable tool for market and consumer research.<\/span><\/p>\n

Data Collection <\/span><\/b><\/p>\n

\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><\/span><\/span>Type of Data: Primary data<\/span><\/p>\n

\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><\/span><\/span>Method: Structured questionnaire<\/span><\/p>\n

\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><\/span><\/span>Scale Used: Rating scale from 1 (Very Poor) to 10 (Excellent)<\/span><\/p>\n

\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><\/span><\/span>Sample Size: 39 respondents<\/span><\/p>\n

\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><\/span><\/span>Bike Models Considered:<\/span><\/p>\n

o\u00a0\u00a0 <\/span><\/span><\/span>Classic 350<\/span><\/p>\n

o\u00a0\u00a0 <\/span><\/span><\/span>GT 650<\/span><\/p>\n

o\u00a0\u00a0 <\/span><\/span><\/span>RTR 310<\/span><\/p>\n

o\u00a0\u00a0 <\/span><\/span><\/span>Triumph Speed 400<\/span><\/p>\n

o\u00a0\u00a0 <\/span><\/span><\/span>Hunter 350<\/b><\/span><\/p>\n

Data analysis<\/span><\/b><\/p>\n\n\n\n\n\n\n\n
\n

Source of Variation<\/span><\/b><\/p>\n<\/td>\n

\n

Sum of Squares (SS)<\/span><\/b><\/p>\n<\/td>\n

\n

Degrees of Freedom (df)<\/span><\/b><\/p>\n<\/td>\n

\n

Mean Square (MS)<\/span><\/b><\/p>\n<\/td>\n

\n

F-value<\/span><\/b><\/p>\n<\/td>\n

\n

p-value<\/span><\/b><\/p>\n<\/td>\n<\/tr>\n<\/thead>\n

\n

Between Groups<\/span><\/b><\/p>\n<\/td>\n

\n

38.67<\/span><\/p>\n<\/td>\n

\n

4<\/span><\/p>\n<\/td>\n

\n

9.67<\/span><\/p>\n<\/td>\n

\n

2.22<\/span><\/p>\n<\/td>\n

\n

0.069<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

Within Groups<\/span><\/b><\/p>\n<\/td>\n

\n

830.26<\/span><\/p>\n<\/td>\n

\n

190<\/span><\/p>\n<\/td>\n

\n

4.37<\/span><\/p>\n<\/td>\n

\n

\u2014<\/span><\/p>\n<\/td>\n

\n

\u2014<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

Total<\/span><\/b><\/p>\n<\/td>\n

\n

868.93<\/span><\/p>\n<\/td>\n

\n

194<\/span><\/p>\n<\/td>\n

\n

\u2014<\/span><\/p>\n<\/td>\n

\n

\u2014<\/span><\/p>\n<\/td>\n

\n

\u2014<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u00a0<\/span><\/p>\n

GT 650 received the highest average rating, while RTR 310 had the lowest.<\/span><\/p>\n

Hypothesis Testing<\/span><\/b><\/p>\n

Null Hypothesis (H\u2080):<\/span><\/b><\/p>\n

There is no significant difference in mean ratings of the selected bikes.<\/span><\/p>\n

Alternative Hypothesis (H\u2081):<\/span><\/b><\/p>\n

There is a significant difference in mean ratings of the selected bikes.<\/span><\/p>\n

Decision Rule<\/span><\/b><\/p>\n

Level of significance (\u03b1) = 0.05<\/span><\/p>\n

If p-value \u2264 0.05, reject H\u2080<\/span><\/p>\n

If p-value > 0.05, fail to reject H\u2080<\/span><\/p>\n

Result (ANOVA Test)<\/span><\/b><\/p>\n