हमारे मुफ्त ऑनलाइन टूल से ए/बी परीक्षण की सार्थकता की गणना करें। बेहतर समझ के लिए उपयोगी स्पष्टीकरण और सुझावों के साथ तत्काल परिणाम प्राप्त करें।

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ए/बी परीक्षण सार्थकता कैलकुलेटर

हमारे मुफ्त ऑनलाइन टूल से ए/बी परीक्षण की सार्थकता की गणना करें। बेहतर समझ के लिए उपयोगी स्पष्टीकरण और सुझावों के साथ तत्काल परिणाम प्राप्त करें।

इनपुट

गणना के लिए आवश्यक मान दर्ज करें

परिणाम

अपने गणना परिणाम देखें

गणना करने के लिए नीचे मान दर्ज करें

A/B Test Significance कैलकुलेटर क्या है?

एक A/B Test Significance कैलकुलेटर आपकी मदद करता है निर्धारित करें if the difference में रूपांतरण rates के बीच two variations की a webpage या app है statistically significant. It tells you whether the observed results are likely due को the changes you made या just random chance.

उपयोग कैसे करें

1. Enter की संख्या आगंतुक के लिए the Control (original) version. 2. Enter की संख्या रूपांतरण के लिए the Control version. 3. Enter की संख्या आगंतुक के लिए the Variant (new) version. 4. Enter की संख्या रूपांतरण के लिए the Variant version. 5. Select your desired confidence level (आमतौर पर 95% या 99%). 6. The कैलकुलेटर will show you the रूपांतरण rates, uplift, और whether the परिणाम है significant.

अक्सर पूछे जाने वाले प्रश्न

What is an A/B Test Significance Calculator?

This tool helps you determine if the difference in performance between two variations (Control and Variant) is statistically significant or just due to random chance.

What is statistical significance?

Statistical significance is a measure of probability that the observed difference between your control and variant is not caused by random chance. A common threshold is 95% confidence.

What is a P-value?

The P-value represents the probability of seeing results as extreme as yours if there was actually no difference between the two versions. A P-value less than 0.05 usually indicates statistical significance.

What is the difference between one-tailed and two-tailed tests?

A one-tailed test checks if the Variant is better than the Control (directional). A two-tailed test checks if the Variant is simply different from the Control (either better or worse). Two-tailed is more conservative and common.

Why does my result say 'Not Significant' even if Variant B looks better?

This usually means your sample size is too small. While Variant B has a higher conversion rate, the difference is not large enough or the traffic is not high enough to rule out luck.

What confidence level should I choose?

The industry standard is 95%. This means you accept a 5% risk of concluding there is a difference when there actually isn't (a false positive). Use 99% for stricter testing.

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