🪴 Aster's notebook

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I. Notes

Here is a list of my study notes :)

85 items under this folder.

May 28, 2024
Automate the boring stuff with python
- #yarn
May 16, 2024
Prompt engineering
- #yarn
Feb 21, 2024
R
- #moc
Feb 09, 2024
Normal distribution
- #knit
Feb 08, 2024
SQL
- #knit
Feb 06, 2024
Data science
- #moc
Feb 06, 2024
Pandas
- #knit
Feb 06, 2024
R style guide
- #fo
Feb 06, 2024
R Utilities
- #fo
Feb 06, 2024
Tidyverse cheatsheet
- #fo
Dec 27, 2023
Bayes' theorem
- #2-ref
Dec 27, 2023
Python
- #moc
Nov 08, 2023
Binomial distribution
- #2-ref
Nov 03, 2023
Exponential distribution
- #2-ref
Nov 03, 2023
Maximum likelihood
- #2-ref
Nov 02, 2023
P-value
- #2-ref
Nov 02, 2023
Probability vs likelihood
- #2-ref
Nov 02, 2023
Quantiles and percentiles
- #2-ref
Nov 02, 2023
Quantile normalization
- #2-ref
Nov 02, 2023
Quantile-quantile plot (QQ plot)
- #2-ref
Oct 30, 2023
Analysis of Variance (ANOVA)
- #2-ref
Oct 30, 2023
Design matrix
- #2-ref
Oct 30, 2023
t-test
- #2-ref
Oct 29, 2023
Linear regression in R
- #2-ref
Oct 29, 2023
Linear regresssion
- #2-ref
Oct 29, 2023
Multiple regression
- #2-ref
Oct 29, 2023
Multiple regression in R
- #2-ref
Oct 25, 2023
Fitting a line to data in linear regression
- #2-ref
Oct 25, 2023
R-squared
- #2-ref
Oct 24, 2023
Fitting a curve to data
- #2-ref
Oct 24, 2023
Least squares
- #2-ref
Oct 24, 2023
Log (logarithm)
- #2-ref
Oct 24, 2023
Mathematics
- #moc
Oct 24, 2023
Weighted least squares
- #2-ref
Oct 23, 2023
Bootstrapping
- #2-ref
Oct 23, 2023
Boxplots
- #2-ref
Oct 23, 2023
Central limit theorem
- #2-ref
Oct 23, 2023
Data visualization
- #moc
Oct 23, 2023
Expected value
- #2-ref
Oct 23, 2023
Mean, variance and standard deviation
- #2-ref
Oct 23, 2023
Probability distribution
- #2-ref
Oct 23, 2023
Sample size and effective sample size
- #2-ref
Oct 23, 2023
Standard error
- #2-ref
Oct 23, 2023
Technical replicates vs Biological replicates
- #2-ref
Oct 20, 2023
Conditional probabilities
- #2-ref
Oct 18, 2023
Pearson Correlation
- #2-ref
Oct 18, 2023
Covariance
- #2-ref
Oct 17, 2023
Power analysis
- #2-ref
Oct 17, 2023
Statistical power
- #2-ref
Oct 16, 2023
Alternative hypotheses
- #2-ref
Oct 16, 2023
Calculate p-value
- #2-ref
Oct 16, 2023
False discovery rates FDR
- #2-ref
Oct 16, 2023
Hypothesis testing and the null hypothesis
- #2-ref
Oct 16, 2023
P-hacking and false positives
- #2-ref
Oct 15, 2023
Statistical test
- #2-ref
Oct 08, 2023
Confidence intervals
- #2-ref
Oct 08, 2023
Histogram
- #2-ref
Oct 08, 2023
Mathematical model
- #2-ref
Oct 08, 2023
Population and estimated parameters
- #2-ref
Oct 08, 2023
Random sampling
- #2-ref
Oct 08, 2023
Resampling
- #2-ref
Oct 08, 2023
Sampling a distribution
- #2-ref
Oct 08, 2023
Underestimate the variance
- #2-ref
Oct 07, 2023
Stats
- #moc
Oct 05, 2023
Probability
- #moc
Oct 04, 2023
Bayes classifier
- #2-ref
Oct 04, 2023
Classification
- #2-ref
Oct 04, 2023
Linear discriminant analysis (LDA)
- #2-ref
Oct 03, 2023
Logistic regression
- #2-ref
Oct 03, 2023
Prior probability and posterior probability
- #2-ref
Oct 02, 2023
Bayesian statistics
- #2-ref
Oct 02, 2023
Bias variance trade off
- #2-ref
Oct 02, 2023
Classification error metrics
- #2-ref
Oct 02, 2023
K nearest neighbours (KNN) with python
- #2-ref
Oct 02, 2023
K nearest neighbours (KNN) theory
- #2-ref
Oct 02, 2023
Linear regresssion in python
- #2-ref
Oct 02, 2023
Regression error metrics
- #2-ref
Oct 02, 2023
Machine learning
- #moc
Oct 01, 2023
Logistic regression coefficients
- #2-ref
Oct 01, 2023
Logistic regression in python
- #2-ref
Oct 01, 2023
Z-value
- #2-ref
Sep 16, 2023
Decision tree and random forest
- #2-ref
Sep 15, 2023
Supervised learning
- #2-ref
Aug 22, 2022
VBA
- #fo
Apr 18, 2022
Working with Excel from R
- #fo

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