Publications by Nischal Bondalapati
ANLY 502 Lab 3
Question 1: Describe the distribution of streak lengths. Distribution of Kobe's streak lengths is right skewed. Distribution of Independent shooter's streal lengths is also right skewed. Question 2: What is the typical streak length for this? Typical streak length of Kobe is 0. Typical streak length of Indipendent shooter is also 0. Question 3: S...
2419 sym
ANLY 502 Lab 7
Question 1 Calculate a 95% confidence interval for the average length of pregnancies (weeks) and interpret it in context. Note that since you're doing inference on a single population parameter, there is no explanatory variable, so you can omit the x variable from the function. inference(y = nc$weeks, est = "mean", type = "ci", null = 0, alternat...
2091 sym R (2116 sym/14 pcs) 4 img
ANLY 502 Lab 8
Question 1 Answer the following two questions using the inference function. As always, write out the hypotheses for any tests you conduct and outline the status of the conditions for inference. Is there convincing evidence that Spain has seen a change in its atheism index between 2005 and 2012? Hint: Create a new data set for respondents from Sp...
1544 sym R (1951 sym/16 pcs) 4 img
ANLY 506 Final Project
library(tidyverse) ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ── ## ✓ ggplot2 3.3.5 ✓ purrr 0.3.4 ## ✓ tibble 3.1.5 ✓ dplyr 1.0.7 ## ✓ tidyr 1.1.4 ✓ stringr 1.4.0 ## ✓ readr 2.0.2 ✓ f...
7314 sym R (22636 sym/99 pcs) 10 img
NischalBondalapati_ANLY505-2022-LateSummer.html
Chapter 2 - Large Worlds and Small Worlds The objectives of this problem set is to work with the conceptual mechanics of Bayesian data analysis. The target of inference in Bayesian inference is a posterior probability distribution. Posterior probabilities state the relative numbers of ways each conjectured cause of the data could have produced th...
3777 sym R (1320 sym/14 pcs)
Extra Credit Project
#loading libraries library(readr) library(Hmisc) ## Loading required package: lattice ## Loading required package: survival ## Loading required package: Formula ## Loading required package: ggplot2 ## ## Attaching package: 'Hmisc' ## The following objects are masked from 'package:base': ## ## format.pval, units #loading data df<-read_csv("d...
463 sym R (5996 sym/34 pcs) 1 img
ANLY 510 Exam Two: Answer 8
#loading libraries library(readr) library(Hmisc) ## Loading required package: lattice ## Loading required package: survival ## Loading required package: Formula ## Loading required package: ggplot2 ## ## Attaching package: 'Hmisc' ## The following objects are masked from 'package:base': ## ## format.pval, units #loading data df<-read_csv("A...
22 sym R (4100 sym/17 pcs)
ANLY 510 Exam Two: Answer 9
#loading libraries library(readr) library(Hmisc) ## Loading required package: lattice ## Loading required package: survival ## Loading required package: Formula ## Loading required package: ggplot2 ## ## Attaching package: 'Hmisc' ## The following objects are masked from 'package:base': ## ## format.pval, units #loading data df<-read_csv("A...
731 sym R (3233 sym/17 pcs)
NischalBondalapati_ANLY505-2022-LateSummer-Assignment8.html
Chapter 9 - Markov Chain Monte Carlo This chapter has been an informal introduction to Markov chain Monte Carlo (MCMC) estimation. The goal has been to introduce the purpose and approach MCMC algorithms. The major algorithms introduced were the Metropolis, Gibbs sampling, and Hamiltonian Monte Carlo algorithms. Each has its advantages and disadva...
2660 sym R (2688 sym/14 pcs) 3 img
NischalBondalapati_ANLY505-2022-LateSummer-Assignment6.html
Chapter 7 - Ulysses' Compass The chapter began with the problem of overfitting, a universal phenomenon by which models with more parameters fit a sample better, even when the additional parameters are meaningless. Two common tools were introduced to address overfitting: regularizing priors and estimates of out-of-sample accuracy (WAIC and PSIS). ...
3588 sym R (7664 sym/58 pcs) 1 tbl