degrees-of-freedom

There are 1 repository under degrees-of-freedom topic.

• lukem512 / anova

  Analysis of Variance (ANOVA)

  anovavarianceanalysisstatisticsf-valuesum-of-squaresdegrees-of-freedommean-squared
  Language:JavaScript 11

• Duke02 / PoseNet

  Pose estimator project from previous internship.

  pythonneural-networkjupyter-notebookconvolutional-neural-networkdegrees-of-freedomposenetsingularitypytorchdocker
  Language:Jupyter Notebook 1

• hdarjus / student-t-asis-paper

  Code for reproducing the results in arXiv:2109.01726

  student-tdegrees-of-freedombayesian-statisticsgibbs-samplingeffective-sample-size
  Language:R 1

• Montevani / Analise-Robo-SCARA-4dof

  Projeto para a aula de Robótica Industrial (UNESP, 2016).

  college-projectdegrees-of-freedominverse-kinematicsjacobianmatricesportuguese-brazilianrobotics
  Language:MATLAB 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

• cmu05391-gsilvera / 4DOFBakeoff

  Open design challenge for optimizing accuracy and speed of a user changing 4 degrees of freedom (size, rotation, x, y) to a target. Teammates: Matt Buchman, Vivian Nguyen, Gustavo Silvera

  teammatesdegrees-of-freedomhuman-computer-interactionprocessing
  Language:Processing 0

• kwfongab / casia-project-kwfongab

  The codes of the final project for the CASIA course about the paper "Effective Degrees of Freedom: a Flawed Metaphor" by Janson, Fithian and Hastie at https://hastie.su.domains/Papers/df_paper_LJrev6.pdf

  degrees-of-freedom
  Language:Python 0