Posts

Showing posts from June, 2020

2_Applied_States

Measure of Central tendency  Find the average  Mean : Sum/N  Issue with outliers  Median  Order and take middle value, robust , resistance to outlier  Mode Assume most occurred values as means Measure of dispersion                                                  Spread of your data around central area Coefficient variation : Standard deviation as percentage of mean, like if mean is 10, then how much percentage of mean, the current value is , this cancel out any units from SD and gives , percentage like value  <Image3> ex : Wind turbulance, is measure of variability in wind.( 10% turbulence of avg wind speed of 30 kmp) Its like SD but represented in % Z state : How do I know, 6 feet tall is good height from the group of basketball player/ Measure from Mean ? or measure from standard deviation of group, which can be acceptable  Z = Tells how many standard deviation far this X/6 feet is ? Z =1 , means 1 SD above the average Z = -2, means 2 SD below the average   

3_1_EDA

Image
Structured data | Tidy data | Labeled data Mainly numbers  Unstructured data Mainly , text, audio video,image >>> Convert them to structured(numbers) Variables : Qualitative | Categorical :  1. Nominal (Texts like name,City,place) 2. Ordinal (Comparable, Like Size, rank) Quantitative | Continuous variables : Number, int, float, etc, age,empId

Probability

Image
Conditional probabilities