p-value | Topic | Ecosyste.ms: Repos

Topic: "p-value"

aangelopoulos/ppi_py

A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.

Language: Python - Size: 5.89 MB - Last synced at: about 20 hours ago - Pushed at: 4 months ago - Stars: 231 - Forks: 19

Pegah-Ardehkhani/Statistics-and-Probability-in-Python

A comprehensive exploration of Statistics and Probability Theory concepts, with practical implementations in Python

Language: Jupyter Notebook - Size: 6.66 MB - Last synced at: 18 days ago - Pushed at: about 1 month ago - Stars: 139 - Forks: 37

puolival/multipy

Multiple hypothesis testing in Python

Language: Python - Size: 1.1 MB - Last synced at: 19 days ago - Pushed at: 9 months ago - Stars: 105 - Forks: 24

mateuszbuda/ml-stat-util

Statistical functions based on bootstrapping for computing confidence intervals and p-values comparing machine learning models and human readers

Language: Jupyter Notebook - Size: 28.3 KB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 45 - Forks: 15

andreekeberg/abby

Minimal A/B Testing Library in PHP

Language: PHP - Size: 47.9 KB - Last synced at: 10 days ago - Pushed at: over 4 years ago - Stars: 32 - Forks: 0

kusterlab/curve_curator

Analysis platform for large-scale dose-dependent data

Language: Python - Size: 42.5 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 25 - Forks: 3

nirupamaprv/Analyze-AB-test-Results

E-Commerce Website A/B testing: Recommend which of two landing pages to keep based on A/B testing

Language: HTML - Size: 10.5 MB - Last synced at: over 1 year ago - Pushed at: over 7 years ago - Stars: 23 - Forks: 28

pMoSS (p-value Model using the Sample Size) is a Python code to model the p-value as an n-dependent function using Monte Carlo cross-validation. Exploits the dependence on the sample size to characterize the differences among groups of large datasets

Language: Python - Size: 21.1 MB - Last synced at: 28 days ago - Pushed at: about 1 year ago - Stars: 16 - Forks: 5

VaibhavAbhimanyooHiwase/Risk_Calculation_using_Backward_Elimination_Algorithm_in_Life_Insurance

Implementation of backward elimination algorithm used for dimensionality reduction for improving the performance of risk calculation in life insurance industry.

Language: Python - Size: 8.22 MB - Last synced at: 5 months ago - Pushed at: over 6 years ago - Stars: 12 - Forks: 6

nunofachada/pval_adjust

Adjust p-values for multiple comparisons

Language: MATLAB - Size: 6.84 KB - Last synced at: 20 days ago - Pushed at: over 5 years ago - Stars: 9 - Forks: 2

vaitybharati/Assignment-04-Simple-Linear-Regression-2

Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

Language: Jupyter Notebook - Size: 45.9 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 8 - Forks: 9

kmedian/korr

collection of utility functions for correlation analysis

Language: Python - Size: 1.77 MB - Last synced at: 11 days ago - Pushed at: almost 3 years ago - Stars: 7 - Forks: 3

nanxstats/signify

Shiny Web Application for Making Your p-value Sound Significant

Language: R - Size: 71.3 KB - Last synced at: about 11 hours ago - Pushed at: about 4 years ago - Stars: 6 - Forks: 2

samirsaci/lss-kruskal-wallis

Lean Six Sigma with Python — Kruskal Wallis Test

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LastAncientOne/GDP_Project

GDP Forcasting

Size: 1.49 MB - Last synced at: 2 months ago - Pushed at: over 3 years ago - Stars: 5 - Forks: 1

mthulin/boot.pval

Bootstrap p-values, including convenience functions for regression models.

Language: R - Size: 1.5 MB - Last synced at: 14 days ago - Pushed at: about 2 months ago - Stars: 4 - Forks: 1

NourKamaly/AirlineTicketPricePrediction

First rank winner in the Machine Learning Course Competition for class 2021-2022. Airline ticket price prediction from end to end (analysis - preprocessing - modeling - testing - deployment - documentation) between Indian cities

Language: Jupyter Notebook - Size: 231 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 4

ksatola/Analyze-A-B-Test-Results

Understand the results of an A/B test run by the website and provide statistical and practical interpretation on the test results

Language: Jupyter Notebook - Size: 4.93 MB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 4 - Forks: 9

fsalhani/coin_tossing

Simple coin tossing simulation to show the issues with peeking at data during frequentist A/B tests

Language: Jupyter Notebook - Size: 248 KB - Last synced at: almost 2 years ago - Pushed at: almost 6 years ago - Stars: 4 - Forks: 2

jmlcode/p2-ab-testing

Analysis of mock A/B Test Results by an e-commerce company. Application of probability, hypothesis testing, sampling distribution, two-sample z-test, and logistic regression to determining whether the company should implement the new web page it developed to increase users' conversion rate

Language: HTML - Size: 5.04 MB - Last synced at: about 2 years ago - Pushed at: about 6 years ago - Stars: 4 - Forks: 4

RachelPengmkt/Analyzing-a-Simple-A-B-Test-with-a-T-Test

I will include two ways of t tests that compare conversion rate and click through rate of two groups

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AlexiaNomena/Correspondence_Analysis_User_Friendly

Correspondence Analysis with python

Language: Python - Size: 1.25 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0

jvirico/normality-tests-pvalues-boxcoxtransformations

Strategies for analyzing the distribution of datasets, switching the data towards a normal distribution testing different manual transformations and Box-Cox transformation.

Language: Python - Size: 1.91 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 3 - Forks: 0

vaitybharati/Assignment-04-Simple-Linear-Regression-1

Assignment-04-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regression.

Language: Jupyter Notebook - Size: 43 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 3 - Forks: 6

Abhishek20182/Analyze-AB-Test-Results

Udacity Data Analyst Nanodegree - Project III

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rebeccak1/pricing-test

Language: Jupyter Notebook - Size: 9.43 MB - Last synced at: 7 months ago - Pushed at: over 7 years ago - Stars: 3 - Forks: 2

debbiemarkslab/GELMMnet

Generalized linear mixed model elastic net

Language: Jupyter Notebook - Size: 341 KB - Last synced at: about 1 year ago - Pushed at: over 7 years ago - Stars: 3 - Forks: 1

m-damien/Statslator.js

🔢 Conversion between statistical reporting styles

Language: TypeScript - Size: 2.27 MB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

lingfeiwang/lassopv

Nonparametric P-Value Estimation for Predictors in Lasso

Language: R - Size: 21.5 KB - Last synced at: 26 days ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 1

kchu25/MotifPvalue.jl

Threshold and p-value computations for Position Weight Matrices

Language: Julia - Size: 111 KB - Last synced at: 6 days ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 0

tantawy997/Analyze_ab_test_results_notebook

Analyze ab test results udacity project

Language: Jupyter Notebook - Size: 35.2 KB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 0

vaitybharati/Assignment-05-Multiple-Linear-Regression-2

Assignment-05-Multiple-Linear-Regression-2. Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in the past few years State -- states from which data is collected Profit -- profit of each state in the past few years.

Language: Jupyter Notebook - Size: 669 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 9

christophersingh/Car-CNN-Capstone

A Convolutional Neural Network Implementation To Classify The Vacancy Of A Parking Spot Using Transfer Learning Methodologies

Language: Jupyter Notebook - Size: 70.2 MB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 1

odeibarredo/Statistics_Group-Comparisons

Statistical analysis comparing metal accumulation levels in three macroinvertebrate groups

Language: R - Size: 687 KB - Last synced at: over 1 year ago - Pushed at: over 7 years ago - Stars: 2 - Forks: 1

steviecurran/Z-value

Code for calculating Z-score from the p-value

Language: C - Size: 37.1 KB - Last synced at: about 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

OliverHennhoefer/online-fdr

Online Multiple Hypothesis Testing.

Language: Python - Size: 131 KB - Last synced at: about 2 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

Jayita11/AtliQo-Bank-Credit-Card-Launch-EDA

This project involves exploratory data analysis and statistical testing for AtliQo Bank's new credit card launch. Key insights include targeting high-income occupations and the 18-25 age group. Recommendations focus on tailored marketing campaigns, education, and incentives to enhance credit card adoption and usage among young adults.

Language: Jupyter Notebook - Size: 1.07 MB - Last synced at: about 2 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

pierogio/Hipotesis_Testing

Hypothesis testing on UEFA European leagues dataframe.

Language: Jupyter Notebook - Size: 985 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

AlaaNabil98/Analyze-A-B-Test-Results

working to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product.

Language: Jupyter Notebook - Size: 5.25 MB - Last synced at: almost 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

Wb-az/Transformers-Emotion-Analysis

Emotion Analysis with Transformers

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Shahequa/Statistics-Assignments

This repository contains problems on hypothesis testing, confidence intervals, P-value, percentiles, skewness, histogram and more.

Size: 1.71 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

KWASSI09/hollywood_vc

Hollywood movie analysis to identify the main driver of growth . We used a CSV file with over 45,000 films on which we performed data cleaning, data visualization, and statistical analysis.

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Usama-Tariq/-Udacity_Analyze-A-B-Test-Results_Project-3_DAND

A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these.

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vaitybharati/P25.-Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data

Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data. EDA and data visualization, Correlation Analysis, Model Building, Model Testing, Model Prediction.

Language: Jupyter Notebook - Size: 178 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0

vaitybharati/P22.-Hypothesis-Testing-Chi2-Test-Human-Gender-and-Choice-of-Pets-

Hypothesis-Testing-Chi2-Test-Human-Gender-and-Choice-of-Pets. Assume Null Hypothesis as Ho: Human Gender and choice of pets is independent and not related. Thus Alternate Hypothesis as Ha : Human Gender and choice of pets is dependent and related. As (p_valu=0.1031) > (α = 0.05); Accept Null Hypothesis i.e Independence among categorical variables. Thus, there is no relation between Human Gender and Choice of Pets.

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vaitybharati/P21.-Hypothesis-Testing-Chi2-Test-Athletes-and-Smokers-

Hypothesis-Testing-Chi2-Test-Athletes-and-Smokers. Assume Null Hypothesis as Ho: Independence of categorical variables (Athlete and Smoking not related). Thus Alternate Hypothesis as Ha: Dependence of categorical variables (Athlete and Smoking is somewhat/significantly related). As (p_value = 0.00038) < (α = 0.05); Reject Null Hypothesis i.e. Dependence among categorical variables Thus Athlete and Smoking is somewhat/significantly related.

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vaitybharati/P20.-Hypothesis-Testing-Anova-Test---Iris-Flower-dataset

Hypothesis Testing Anova Test - Iris Flower dataset. Anova ftest statistics: Analysis of varaince between more than 2 samples or columns. Assume Null Hypothesis Ho as No Varaince: All samples population means are same. Thus Alternate Hypothesis Ha as It has Variance: Atleast one population mean is different. As (p_value = 0) < (α = 0.05); Reject Null Hypothesis i.e. Atleast one population mean is different Thus there is variance in more than 2 samples.

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vaitybharati/P19.-Hypothesis-Testing-2-Proportion-T-test-Students-Jobs-in-2-States-

Hypothesis-Testing-2-Proportion-T-test-Students-Jobs-in-2-States. Assume Null Hypothesis as Ho is p1-p2 = 0 i.e. p1 ≠ p2. Thus Alternate Hypthesis as Ha is p1 = p2. Explanation of bernoulli Binomial RV: np.random.binomial(n=1,p,size) Suppose you perform an experiment with two possible outcomes: either success or failure. Success happens with probability p, while failure happens with probability 1-p. A random variable that takes value 1 in case of success and 0 in case of failure is called a Bernoulli random variable. Here, n = 1, Because you need to check whether it is success or failure one time (Placement or not-placement) (1 trial) p = probability of success size = number of times you will check this (Ex: for 247 students each one time = 247) Explanation of Binomial RV: np.random.binomial(n=1,p,size) (Incase of not a Bernoulli RV, n = number of trials) For egs: check how many times you will get six if you roll a dice 10 times n=10, P=1/6 and size = repetition of experiment 'dice rolled 10 times', say repeated 18 times, then size=18. As (p_value=0.7255) > (α = 0.05); Accept Null Hypothesis i.e. p1 ≠ p2 There is significant differnce in population proportions of state1 and state2 who report that they have been placed immediately after education.

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vaitybharati/P18.-Hypothesis-Testing-2-Sample-2-Tail-Test-Drugs-and-Placebos-

Hypothesis-Testing-2-Sample-2-Tail-Test-Drugs-and-Placebos. Note: This python code states both 2-sample 1-tail and 2-sample 2-tail codes. Treatment group mean is Mu1 Contrl group mean is Mu2 2-sample 2-tail ttest Assume Null Hypothesis Ho as Mu1 = Mu2 Thus Alternate Hypothesis Ha as Mu1 ≠ Mu2.

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vaitybharati/P17.-Hypothesis-Testing-1-Sample-1-Tail-Test-Salmonella-Outbreak-

Hypothesis-Testing-1-Sample-1-Tail-Test-Salmonella-Outbreak. 1-sample 1-tail ttest. Assume Null Hypothesis Ho as Mean Salmonella <= 0.3. Thus Alternate Hypothesis Ha as Mean Salmonella > 0.3. As No direct code for 1-sample 1-tail ttest available with unknown SD and arrays of means. Hence we find probability using 1-sample 2-tail ttest and divide it by 2 to get 1-tail ttest.

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vaitybharati/P16.-Hypothesis-Testing-1S2T---Call-Center-Process

Hypothesis Testing 1S2T - Call Center Process. Sample Parameters: n=50, df=50-1=49, Mean1=4, SD1=3 1-sample 2-tail ttest Assume Null Hypothesis Ho as Mean1 = 4 Thus, Alternate Hypothesis Ha as Mean1 ≠ 4

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vaitybharati/P15.-Hypothesis-Testing-1S1T---Super-Market-Loyality-Program

Hypothesis-Testing 1S1T-Super-Market-Loyality-Program. Population Parameters: Mean=120 Sample Parameters: n=80, Mean=130, SD=40, df=80-1=79

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DeboraOliver/Chi-square

Pearson's Chi-Square Test of Independence for NYHA and KCCQ

Language: R - Size: 10.7 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

deepdhungel/Charite-Projects-2017

MyWork

Language: Python - Size: 19.5 KB - Last synced at: 3 months ago - Pushed at: almost 5 years ago - Stars: 1 - Forks: 0

shakibyzn/Statistical-Methods

Use a wide variaty of statistical tests in python, R, SPSS

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akshatbhargava123/bluegenes-GO-term-visualizer Fork of intermine/bluegenes-go-term-visualizer

GO Term Visualizations

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admorris/StandardHypoTestInverter

A more sensible implementation of a RooStats demo

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NikhilaThota/Stats_analysis_hospital_readmissions

Used statistical measures to determine if the rate of re admissions for hospitals are high, if yes, what steps can be taken to bring the rate down.

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RRafiee/Association

Finding association between clinical, pathological and molecular features

Language: R - Size: 436 KB - Last synced at: over 1 year ago - Pushed at: over 7 years ago - Stars: 1 - Forks: 0

kkdey/WEAVER

Word Enrichment Analysis using VEctor Representations

Language: C - Size: 97.3 MB - Last synced at: about 2 years ago - Pushed at: almost 8 years ago - Stars: 1 - Forks: 0

YujiSODE/draw2Sample 📦

the interface for graphical sampling in order to generate values following an empirical distribution, with img/canvas tag on Firefox.

Language: JavaScript - Size: 173 KB - Last synced at: over 1 year ago - Pushed at: about 8 years ago - Stars: 1 - Forks: 0

zuzannna/AB-Testing-Bayes

A/B testing using frequentist and Bayesian approaches

Language: Jupyter Notebook - Size: 20 MB - Last synced at: over 1 year ago - Pushed at: about 8 years ago - Stars: 1 - Forks: 0

steviecurran/bin-data

Bin data and plot

Language: Python - Size: 161 KB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 0 - Forks: 0

josericodata/StatisticsApp

Interactive statistics analysis app using Python and Streamlit. Perform key statistical tests, visualise distributions, and explore data with ease.

Language: Python - Size: 6.79 MB - Last synced at: about 5 hours ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

Torusaynim/Mirea-Data-Analysis

📋 List of practical works from Technologies and Tools for Big Data Analysis subject from university

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Arjun-08/Effects-of-smoking

This project analyzes the effects of smoking on gene expression, focusing on the interaction between **Smoking Status** and **Gender** using a 2-way ANOVA framework. The results, visualized through a p-value histogram, highlight genes with potential differential responses.

Language: Python - Size: 9.98 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

lmizner/codecademy_farmburg_AB_testing

Language: Python - Size: 34.2 KB - Last synced at: 20 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

lmizner/codecademy_fetchmaker

Language: Python - Size: 3.91 KB - Last synced at: 20 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

lmizner/codecademy_heart_disease

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Loveleen-DS/AB_test

a straightforward approach to assess whether introducing a new landing page leads to an increase in user conversions using Conversion Analysis, One-Tailed T-Test (A/B Test) and Regression Analysis

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Senich17/educational-impact-analysis

A series of analyses to investigate the impact of parental education level on students' math scores.

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al1sant0s/Hypothesis-Tests

Python package to perform statistical hypothesis tests.

Language: Python - Size: 713 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

spacebakery/Statistical-Concepts

Statistics for Data Analysis | Sample Mean vs. Population Mean and P-Values

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jeaend/Inferential_Statistic Fork of ta-data-remote/lab-t-tests-p-values

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shwetapardhi/Assignment-05-Multiple-Linear-Regression-2

Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in t

Language: Jupyter Notebook - Size: 670 KB - Last synced at: about 2 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

shwetapardhi/Assignment-05-Multiple-Linear-Regression-1

Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.p

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shwetapardhi/Assignment-04-Simple-Linear-Regression-2

Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

Language: Jupyter Notebook - Size: 46.9 KB - Last synced at: about 2 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

shwetapardhi/Assignment-04-Simple-Linear-Regression-1

Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regressi

Language: Jupyter Notebook - Size: 43 KB - Last synced at: about 2 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

shwetapardhi/Assignment-03-Q1--Hypothesis-Testing

Q1.A F&B manager wants to determine whether there is any significant difference in the diameter of the cutlet between two units. A randomly selected sample of cutlets was collected from both units and measured? Analyze the data and draw inferences at 5% significance level. Please state the assumptions and tests that you carried out to check validit

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Hermann-web/some-common-statistical-methods

python module, showcasing computation (as part of a learning process) of some common statistical methods including mininum sample size, confidence interval estimation methods for mean or proportion, hypothesis testing mehods and regression models witth metrics and test suites

Language: Python - Size: 582 KB - Last synced at: 28 days ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Scrayil/GlobClus_prop-Analysis

This aim of this project is to analyze globular star clusters in the Milky Way, in order to understand their dynamics. The conducted study examined the properties that affect the central velocity dispersion, their impact and the correlations between them.

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Mukul-kush/Sun-Pharma-Case-Study

Pharmaceutical company Sun Pharma

Size: 618 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Aichatolba/Graduate-Admission-Logistic-Regression

Logistic regression in R

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ZofiaQlt/customer_behaviour

🎯 Customer behaviour and sales analysis for a national bookstore library willing to adapt its digital vs. instore strategy - use of Python and JupyterLab (Business insights, Data collection, Cleaning, EDA, Market Segmentation, Time Series analysis, Statistical tests and Data Visualization)

Language: Jupyter Notebook - Size: 35 MB - Last synced at: about 2 months ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

seandhan/Insurance-Business-Statistics

Statistical Analysis of Insurance premium data

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nourhenehanana/Advertising-Means-impact-on-Sales

The advertising dataset captures the sales revenue generated with respect ot advertisement costs across multiple channels loike radio, tv and newspapers. In this little project, we use the linear and multiple regression to understand how spending on advertisements impact sales.

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olesyamba/ICvsML

Usual linear regression or XGBoost? Combo! Or how I was investigating the impact of intellectual capital on NASDAQ-100 capitalization during 2 years.

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DerekEgenti/Stats_Comparison_Project

A basic comparison of different statistical methods for data understanding and exploration.

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S-CHAN11/Salary-Variance-Analysis

In this project I analyze if the salary of employees is dependent on their education or occupation using Advanced Statistical concepts like Hypothesis Testing and Anova

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RichmondDjwerter/Mobile-Games-A-B-Testing-with-Cookie-Cats

Cookie Cats is a hugely popular mobile puzzle game, it's a classic "connect three"-style puzzle game. in this notebook we're going to analyze an AB-test where we moved the first gate in Cookie Cats from level 30 to level 40. In particular, we will look at the impact on player retention.

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