**Principal component analysis** (**PCA**) is a mathematical algorithm that reduces the dimensionality of the data while retaining most of the variation in the data set. It accomplishes this reduction by identifying directions, called **principal components**, along which the variation in the data is maximum.

Below are the list of steps we will be following throughout the tutorial.

- Normalize data
- Know how to select number of components
- Perform Principal component analysis (PCA)
- Compute the correlations between the original data and each principal component
- Explain the components observed
- Scatter plot all the data on PC0 vs PC1 or PC1 vs PC2
- Scatter…

Power curves are **line plots that show how the change in variables**, such as **effect size and sample size**, **impact the power of the statistical test**.

In this assignment, we will use the pwr package in R.

library(tidyverse)

## -- Attaching packages -------------------------------------------------------------------------------------------------------- tidyverse 1.3.0 --## v ggplot2 3.3.0 v purrr 0.3.3

## v tibble 2.1.3 v dplyr 0.8.4

## v tidyr 1.0.2 v stringr 1.4.0

## v readr 1.3.1 v forcats 0.5.0library(pwr)

Let’s understand, What is POWER ?

The power of a hypothesis test is the probability that the test correctly rejects the null hypothesis. The power…

Calculate and output for the confidence interval for the `Odds Ratio`

and `Relative Risk.`

Ref http://www.rdocumentation.org/packages/base/versions/3.6.2/topics/log

For simplicity, I have assigned exposure and outcome groups to `a`

,`b`

,`c`

and `d`

variables inside the function.

`with(acupuncture.data,table(group,migraine)) -> con.tab`

a <- con.tab[1,2]

b <- con.tab[1,1]

c <- con.tab[2,2]

d <- con.tab[2,1]

Steps to calculate Confidence Interval for Odds Ratio

- Calculate Odds Ratio
`(a*d)/(b*c)`

- Calculate Point Estimate (
`Log`

of`Odds Ratio`

so that the value looks normal) - Find Margin Error for
`95%`

confidence interval`1.96 * sqrt((1/a) + (1/b) + (1/c)+ (1/d))`

- Apply
`+-`

and`Exponentiate`

value `Round`

CI’s Upper and lower boundary

Steps to…

**Trader Account**: cash balance**Publicly traded companies**: Identified by ticker symbol (`IBM`

,`AAPL`

,`TSLA`

,`GE`

,`NKE`

,`ZM`

,`AMZN`

,`GM`

,`T`

). Use at least 10.**Stock position**: number of stock shares of a**Public Company**in a**Trader Account**.**Withdrawals and deposits**: money in and into**Trader Account**without changing stock positions.**Stop order**: Sell or Buy, ticker symbol, number of shares, price**Market order**: Sell or Buy, ticker symbol, number of share.**Transactions**: A transaction occurs when a market order is placed and there is stop order for the same company of the opposite buy/sell category.

- Define the
`place_order`

function…

Design a binary classifier that uses the cognitive task performance data to tell whether the person is in age category 1: 15–65 yo or category 2: all other ages.

https://github.com/cinnipatel/ml/blob/master/Proj1-Human%20Behaviour.ipynb

Data Scientist — Generalist | Big data Enthusiast | Student at St Thomas Uni