proportion-test

There are 0 repository under proportion-test topic.

• 28101991SUNNY / Statistics_study

  about statistical techniques for Data Science

  anova-analysisbayes-theorembootstrapping-statisticscentral-limit-theoremchi-square-testconfidence-intervalgaussian-distributionhypothesis-testinginferencial-statisticskolmogorov-smirnov-testsmathematicsnonparametric-statisticsparametricpost-hoc-analysisprobabilityproportion-testqqplotst-test
  Language:Jupyter Notebook 5

• MoinDalvs / Learn_hypothesis_testing_for_Data_science

  Hypothesis for Data Science

  one-sample-t-testtwo-sample-t-testindependent-sample-t-testpaired-sample-t-testproportion-testanova-testchi2-contingencychi2goodness-of-fittestofindependence
  Language:Jupyter Notebook 1

• vaitybharati / Hypothesis-Test

  Hypothesis-Test in python

  python3hypothesis-testshypothesis-testingpandasnumpyscipystatst-statisticcdfone-tail-testtwo-tail-testproportion-testanova-test
  Language:Jupyter Notebook 1

• 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.

  pythonproportion-testhypothesis-testingnull-hypothesisalternate-hypothesis2-proportion-ttestbernoulli-binomial-rvstatsmodelspandasnumpysignificance-testingt-scorep-valueprobabilitydegrees-of-freedom
  Language:Jupyter Notebook 1

• mosama1994 / Wine-Quality-Analysis-using-R

  Wine dataset statistical analysis using Hypothesis testing (F-test, T-test, ANOVA, ANCOVA). Using machine learning to predict wine quality. Using regularization with 10 fold cross validation to overcome overfitting. Created different visualizations on the dataset.

  f-testmarkdownrt-testancovaanovabenferronicross-validationhypothesis-testingproportion-testregularizationtuckey-s-hsd-test
  Language:HTML 0

• reshma78611 / Hypothesis-Testing-using-R-

  Hypothesis Testing using R language

  hypothesis-testinganova-testr-studioproportion-testchi-square-test
  Language:R