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GitHub topics: significance-testing

Repositories

statmlben/dnn-inference

[TNNLS 2022] Significance tests of feature relevance for a black-box learner

Language: Python - Size: 568 MB - Last synced: about 24 hours ago - Pushed: about 1 month ago - Stars: 15 - Forks: 4

Alcampopiano/hypothesize

Robust statistics in Python

Language: Python - Size: 5.2 MB - Last synced: 2 days ago - Pushed: 10 months ago - Stars: 62 - Forks: 3

shwetapardhi/Assignment-03-Q5--Hypothesis-Testing

Chi2 contengency independence test Q5. Fantaloons Sales managers commented that % of males versus females walking in to the store differ based on day of the week. Analyze the data and determine whether there is evidence at 5 % significance level to support this hypothesis. Assume Null Hypothesis as Ho: Independence of categorical variables (% of

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shwetapardhi/Assignment-03-Q4-Hypothesis-Testing

Chi2 contengency independence test Q4. TeleCall uses 4 centers around the globe to process customer order forms. They audit a certain % of the customer order forms. Any error in order form renders it defective and has to be reworked before processing. The manager wants to check whether the defective % varies by centre. Please analyze the data at 5

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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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arleyc/PCAtest

R package PCAtest for evaluating the statistical significance of PCA analysis, selecting number of significant PC axes, and testing the contributions of the variables to those PCs.

Language: R - Size: 3.64 MB - Last synced: 9 days ago - Pushed: 9 days ago - Stars: 18 - Forks: 3

automl-private/significance_analysis

This package is used to analyse datasets of different HPO-algorithms performing on multiple benchmarks.

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spatstat/spatstat.explore

Sub-package of spatstat providing functions for exploratory and nonparametric data analysis

Language: R - Size: 1.73 MB - Last synced: 20 days ago - Pushed: 20 days ago - Stars: 0 - Forks: 1

dgluesen/ab-testing-trials

Development of the theoretical basis for statistical hypothesis testing with calculation of sample data sets

Language: Jupyter Notebook - Size: 10.6 MB - Last synced: 22 days ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

Kaleidophon/deep-significance

Enabling easy statistical significance testing for deep neural networks.

Language: Python - Size: 5.54 MB - Last synced: 19 days ago - Pushed: 7 months ago - Stars: 315 - Forks: 20

andreekeberg/abby

Minimal A/B Testing Library in PHP

Language: PHP - Size: 47.9 KB - Last synced: 10 days ago - Pushed: almost 4 years ago - Stars: 30 - Forks: 0

jmersinger/EPI-vs-GDP-Data-Analysis-Visualization-Paper

Research, Analysis, and Final Paper for my Intro to Econometrics class taken in Fall 2023

Language: R - Size: 11.9 MB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 0 - Forks: 0

RSAKIB78/Statistical-Analysis-R

Implementing statistical analysis on data

Size: 5.98 MB - Last synced: 4 months ago - Pushed: over 1 year ago - Stars: 1 - Forks: 0

nidhimanthale/Statistical-Modelling

Statistical Modelling of Swine Flu Outbreak Data

Language: R - Size: 239 KB - Last synced: 5 months ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

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/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/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/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/P24.-Supervised-ML---Simple-Linear-Regression---Newspaper-data

Supervised-ML---Simple-Linear-Regression---Newspaper-data. EDA and Visualization, Correlation Analysis, Model Building, Model Testing, Model predictions.

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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/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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vaitybharati/Assignment-03-Q4-Hypothesis-Testing-

Chi2 contengency independence test. Q4. TeleCall uses 4 centers around the globe to process customer order forms. They audit a certain % of the customer order forms. Any error in order form renders it defective and has to be reworked before processing. The manager wants to check whether the defective % varies by centre. Please analyze the data at 5% significance level and help the manager draw appropriate inferences.

Language: Jupyter Notebook - Size: 3.91 KB - Last synced: 7 months ago - Pushed: about 3 years ago - Stars: 1 - Forks: 1

vaitybharati/Assignment-03-Q5-Hypothesis-Testing-

Chi2 contengency independence test. Fantaloons Sales managers commented that % of males versus females walking in to the store differ based on day of the week. Analyze the data and determine whether there is evidence at 5 % significance level to support this hypothesis.

Language: Jupyter Notebook - Size: 2.93 KB - Last synced: 7 months ago - Pushed: about 3 years ago - Stars: 1 - Forks: 0

vaitybharati/Assignment-03-Q1-Hypothesis-Testing-

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 validity of the assumptions. Cutlets.csv

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vaitybharati/Assignment-03-Q2-Hypothesis-Testing-

Anova ftest statistics. A hospital wants to determine whether there is any difference in the average Turn Around Time (TAT) of reports of the laboratories on their preferred list. They collected a random sample and recorded TAT for reports of 4 laboratories. TAT is defined as sample collected to report dispatch. Analyze the data and determine whether there is any difference in average TAT among the different laboratories at 5% significance level.

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cloudy-sfu/GC-significance-test

The significance test for Granger causality of financial risks in stock indices

Language: Python - Size: 659 KB - Last synced: 3 days ago - Pushed: 7 months ago - Stars: 0 - Forks: 1

Nero103/AB-Test-Comparing-Ride-Fare

This is an A/B test to compare the ride service fare payments to find which one generates the most revenue.

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T3kan0/bootstrap_resample_with_replacement

A combination of codes developed for the calculation of the cross-correlation confidence intervals, making use of a pair of light-curves. The code conducts a bootstrap random sampling with replacement method to generate artificial light-curves. The code determines the cross-correlation of the artificial light-curves, and uses them for significance.

Language: Fortran - Size: 210 KB - Last synced: 8 months ago - Pushed: 8 months ago - Stars: 1 - Forks: 0