Company X has recently introduced a new type of bidding, average bidding, as an alternative to the current type of bidding called maximum bidding. One of our clients, bombabomba.com, decided to test this 8000 new feature and wants to do an A/B test to see if average bidding converts more than maximum bidding.
Basic A/B Testing analysis with Python (Shapiro, Levene, T-Test)
Perform Levene's statistical test for equality of group variances.
Statistical analysis comparing metal accumulation levels in three macroinvertebrate groups
This project explores Yulu bike rental data to analyze user demand, seasonal trends, and environmental influences on ride volume. Additionally, hypothesis testing was performed to statistically validate key assumptions regarding rental patterns.
The data relates to several user actions or interests recorded on two variants of landing pages for an online news portal. The objective is to analyse these interests by performing statistical analyses to determine if one variant is more effective based on chosen metrics (A/B testing).
HHA507 / Data Science / Assignment 6 / ANOVA
Fundamental Concept for Hypothesis Testing, such as Parametric vs Non Parametric Statistical Tests , Various T-tests ,
Applied statistical inference project analyzing mileage differences between manual and automatic vehicles using data preprocessing, EDA, Shapiro–Wilk test, Levene’s test, independent t-test (Welch), Mann–Whitney U test, Cohen’s d, and 95% CIs in Python (Pandas, NumPy, SciPy, Matplotlib, Seaborn).
A collection of simple parameter estimation and significance tests for the comparison of multivariate means and variation, covered in Chapters 4 and 5 of the book Multivariate Statistical Methods. A Primer. 5th edition.
Statistically analyzing the results of an A-B test
Gain hands-on experience with ANOVA analysis, understanding its assumptions, and applying it to real-world datasets to understand differences among group means.
Exploratory Data Analysis is applied to analyse past data of video games that are sold during year 1980 to 2016. The purpose of the analysis it to find out which games, platforms, genres, and ESRB rating class that highly marketable in year 2017.
This project explores Yulu bike rental data to analyze user demand, seasonal trends, and environmental influences on ride volume. Additionally, hypothesis testing was performed to statistically validate key assumptions regarding rental patterns.
Analyze a loan default dataset to understand the factors that contribute to loan defaults.
Cab riding trips are analyzed to understand more on how trips are affected by weather condition, how certain spots attract more taxi passengers, and how a taxi company stands out in making most trips.
This repo creates a randomized data set for testing statistical methods with.
Identification of ineffective operators for the call centre "CallMeMaybe" by exploratory data analysis (EDA) and statistical hypothesis testing (Levene, T-test). Includes retention metrics, wait times and dashboard in Tableau.
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