Akhileshkumarkc / Statistics-Projects

Statistics-Projects done in R involving basic R Function, analyzing US Election, boxplot and confidence interval for HeartBeat using finger-arm method, analysis of voicedata to classify instrument v/s Singer data, Linear Regression, Anova Analysis and AIC For cancer data and BootStrap Analysis on CPU Time. These are projects done by Akhilesh Kumar Kagalvadi Chinnaswamy and Vidya Sri Mani for Learning Statistics and Machine Learning using R.

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Statistics-Projects

These are projects done by Akhilesh Kumar Kagalvadi Chinnaswamy and Vidya Sri Mani for Learning Statistics and Machine Learning using R.

This Include below projects:

Project1- Basic R Function

Running Basic R fucntion for finding mean, simulating draws, computing Expected value, Variance.

Project2 - US Election Votes Anlaysis.

Analysing US Election data by ploting using ggplot calculating the weak and strong areas of Trump and Clinton using raster,ggplot2,ggmap,plyr,scales,maps.

Project3 - Boxplot and Confidence Interval - HeartBeat [finger,arm]

Analysing Heartbeat through Finger method and Arm Method and analysis the confidence Interval for measuring the heartbeat.

Project4 - Analysis of Voicedata to classify instrument v/s Singer data

Exploratory analysis of voice data.

Project5 - Linear Regression Anova AIC For cancer data

Analysis of Cancer Data to predict reasonable good model by taking PSA Response as response Variable by using Linear Regression with ANOVA Analysis and Verifying, comparing the results with AIC.

Project6 - BootStrap Analysis on CPU Time.

Bootstraping CPU Time for calculating boot values.

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Statistics-Projects done in R involving basic R Function, analyzing US Election, boxplot and confidence interval for HeartBeat using finger-arm method, analysis of voicedata to classify instrument v/s Singer data, Linear Regression, Anova Analysis and AIC For cancer data and BootStrap Analysis on CPU Time. These are projects done by Akhilesh Kumar Kagalvadi Chinnaswamy and Vidya Sri Mani for Learning Statistics and Machine Learning using R.


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Language:R 100.0%