| 1. Basics of subsetting.mp4 | 17 MB | ||
| 1. Binary random variables, sample space.mp4 | 54.1 MB | ||
| 1. Binomial random variables.mp4 | 89.8 MB | ||
| 1. Booleans.mp4 | 23.1 MB | ||
| 1. Common functions in R.mp4 | 23.8 MB | ||
| 1. Creating matrices with cbind and rbind.mp4 | 12.7 MB | ||
| 1. Data frames.mp4 | 15.6 MB | ||
| 1. Expected value of a sum.mp4 | 28.5 MB | ||
| 1. Exponential random variables.mp4 | 29.4 MB | ||
| 1. Gamma distribution and rgamma().mp4 | 33 MB | ||
| 1. Geometric random variables.mp4 | 30 MB | ||
| 1. Hypergeometric random variables.mp4 | 110.3 MB | ||
| 1. Introduction to vectorized operations.mp4 | 9.9 MB | ||
| 1. Introduction.mp4 | 18.1 MB | ||
| 1. Lists.mp4 | 21 MB | ||
| 1. Matrix subsetting.mp4 | 8.9 MB | ||
| 1. Negative binomial random variables.mp4 | 38.2 MB | ||
| 1. Normal random variables and the empirical rule.mp4 | 75.7 MB | ||
| 1. Poisson distribution and rpois().mp4 | 64.8 MB | ||
| 1. Uniform distribution, runif() and dunif().mp4 | 35.8 MB | ||
| 1. Variables and assignment.mp4 | 6.3 MB | ||
| 1. apply().mp4 | 28.6 MB | ||
| 1. binom.test.mp4 | 22.4 MB | ||
| 1. sample().mp4 | 12.5 MB | ||
| 10. Dealing with different time periods.mp4 | 29.8 MB | ||
| 10. Normal approximation to the binomial distribution.html | 102.4 B | ||
| 10. cdf and pbinom().mp4 | 83 MB | ||
| 10. chisq.test.html | 102.4 B | ||
| 10. colon .html | 102.4 B | ||
| 11. Normal approximation to the Poisson distribution.mp4 | 31.6 MB | ||
| 11. aov().html | 102.4 B | ||
| 11. colon coding solution.mp4 | 2.1 MB | ||
| 11. pbinom().html | 102.4 B | ||
| 11. prop.test() one sample.html | 102.4 B | ||
| 12. Other types of inequalities and intervals.mp4 | 55.8 MB | ||
| 12. Poisson Normal Approximation coding exercise.html | 102.4 B | ||
| 12. filter().html | 102.4 B | ||
| 12. prop.test two sample.html | 102.4 B | ||
| 12. seq().mp4 | 11.8 MB | ||
| 13. Visualizing the cdf.mp4 | 26.3 MB | ||
| 13. prop.test two sample example.html | 102.4 B | ||
| 13. select().html | 102.4 B | ||
| 13. seq() quiz.html | 102.4 B | ||
| 14. The median.mp4 | 50.7 MB | ||
| 14. glm().html | 102.4 B | ||
| 14. seq() exercise 1.html | 102.4 B | ||
| 15. accuracy.html | 102.4 B | ||
| 15. qbinom().mp4 | 75.3 MB | ||
| 15. seq() exercise 1 solution.mp4 | 3.3 MB | ||
| 16. precision and recall.html | 102.4 B | ||
| 16. qbinom().html | 102.4 B | ||
| 16. seq() exercise 2.html | 102.4 B | ||
| 17. 1 sample t test by hand.html | 102.4 B | ||
| 17. Problem-solving with qbinom().mp4 | 44.8 MB | ||
| 17. seq() exercise 2 solution.mp4 | 3.3 MB | ||
| 18. rep().mp4 | 9.5 MB | ||
| 18. t.test() one sample.html | 102.4 B | ||
| 19. 1 mean t interval.html | 102.4 B | ||
| 19. rep() quiz.html | 102.4 B | ||
| 2. Boolean Quiz 1.html | 102.4 B | ||
| 2. Empirical rule with rnorm().mp4 | 41.8 MB | ||
| 2. Expected value and standard deviation of gamma distribution.mp4 | 18.8 MB | ||
| 2. Install R and RStudio.html | 409.6 B | ||
| 2. Matrix subsetting quiz 1.html | 102.4 B | ||
| 2. Mean and standard deviation of the uniform distribution.mp4 | 7.8 MB | ||
| 2. Simulating Bernoulli random variables with rbinom().mp4 | 83.8 MB | ||
| 2. Standard deviation of a sum.mp4 | 23.2 MB | ||
| 2. Subsetting quiz 1.html | 102.4 B | ||
| 2. Variables and assignment.html | 102.4 B | ||
| 2. Vectorized operations quiz.html | 102.4 B | ||
| 2. apply() quiz 1.html | 102.4 B | ||
| 2. binom.test.html | 102.4 B | ||
| 2. cbind() and rbind().html | 102.4 B | ||
| 2. creating data frames.html | 102.4 B | ||
| 2. list quiz.html | 102.4 B | ||
| 2. mean(), median(), sum(), length().html | 102.4 B | ||
| 2. mean(rbinom()), Law of Large Numbers.mp4 | 34.8 MB | ||
| 2. rexp().mp4 | 20.2 MB | ||
| 2. rgeom().mp4 | 13.3 MB | ||
| 2. rnbinom().mp4 | 20.8 MB | ||
| 2. rpois() coding exercise.html | 102.4 B | ||
| 2. sample().html | 102.4 B | ||
| 20. 1 proportion interval, binom.test, prop.test.html | 102.4 B | ||
| 20. rep() exercise 1.html | 102.4 B | ||
| 21. lm().html | 102.4 B | ||
| 21. rep() exercise 1 solution.mp4 | 4.1 MB | ||
| 22. predict.html | 102.4 B | ||
| 22. rep() exercise 2.html | 102.4 B | ||
| 23. MSE.html | 102.4 B | ||
| 23. rep() exercise 2 solution.mp4 | 4.3 MB | ||
| 3. ==, , , =, =.html | 102.4 B | ||
| 3. Adding a number to all elements of a vector.html | 102.4 B | ||
| 3. Bernoulli trials - counting successes and failures.html | 102.4 B | ||
| 3. Sums of normal random variable is normal.mp4 | 8.1 MB | ||
| 3. Variables and assignment coding assignment.mp4 | 5.7 MB | ||
| 3. cbind and rbind quiz.html | 102.4 B | ||
| 3. data frame quiz.html | 102.4 B | ||
| 3. dgamma() and pgamma().mp4 | 17.2 MB | ||
| 3. dgeom().mp4 | 42.9 MB | ||
| 3. dnbinom().mp4 | 49.2 MB | ||
| 3. dnorm() and continuous distributions.mp4 | 93.9 MB | ||
| 3. dpois().mp4 | 15.4 MB | ||
| 3. matrix subsetting rows and columns.html | 102.4 B | ||
| 3. mean() median() sum() length() solution.mp4 | 9.9 MB | ||
| 3. punif().mp4 | 10.3 MB | ||
| 3. rbinom() exercise.html | 102.4 B | ||
| 3. rexp() coding exercise.html | 102.4 B | ||
| 3. rowSums() and rowMeans().html | 102.4 B | ||
| 3. sample() quiz.html | 102.4 B | ||
| 3. subsetting.html | 102.4 B | ||
| 4. Adding a number to all elements of a vector solution.mp4 | 5.3 MB | ||
| 4. Creating matrices with matrix().mp4 | 16.9 MB | ||
| 4. Generating Binomial random variables with rbinom().html | 102.4 B | ||
| 4. Mean and sd of binomial distribution, Normal approximation to the binomial.mp4 | 29.9 MB | ||
| 4. Parameters - The population proportion.mp4 | 46.1 MB | ||
| 4. Subsetting a vector with a boolean.mp4 | 7.4 MB | ||
| 4. Subsetting data randomly with sample().mp4 | 27.4 MB | ||
| 4. Variables and assignment.html | 102.4 B | ||
| 4. apply().html | 102.4 B | ||
| 4. dexp().mp4 | 9.3 MB | ||
| 4. dgeom().html | 102.4 B | ||
| 4. dnbinom(), pnbinom(), qnbinom() coding exercise.html | 102.4 B | ||
| 4. dpois() coding exercise.html | 102.4 B | ||
| 4. matrix subsetting, only certain columns.html | 102.4 B | ||
| 4. pnorm() and the empirical rule.mp4 | 11.5 MB | ||
| 4. qgamma().mp4 | 10.8 MB | ||
| 4. qunif() and the inverse transform method.mp4 | 38.1 MB | ||
| 4. sd() and var().html | 102.4 B | ||
| 4. subsetting with c().html | 102.4 B | ||
| 5. Converting Celsius to Fahrenheit.html | 102.4 B | ||
| 5. Estimating probabilities with mean() and rbinom().mp4 | 29.1 MB | ||
| 5. Expected value and sd of exponential distribution.mp4 | 32 MB | ||
| 5. Expected value and standard deviation of geometric distribution.mp4 | 39.9 MB | ||
| 5. Expected value and standard deviation.mp4 | 16.3 MB | ||
| 5. Mean and standard deviation of negative binomial distribution.mp4 | 16.5 MB | ||
| 5. Sample statistics - mean() for calculating sample proportions.mp4 | 41.8 MB | ||
| 5. Vectors with c().mp4 | 9.7 MB | ||
| 5. matrix subsetting, only certain rows.html | 102.4 B | ||
| 5. matrix() quiz.html | 102.4 B | ||
| 5. pgamma() and qgamma() coding exercise.html | 102.4 B | ||
| 5. punif() and qunif() coding exercise.html | 102.4 B | ||
| 5. qnorm().mp4 | 60.6 MB | ||
| 5. sd() and var() solution.mp4 | 7.4 MB | ||
| 5. subsetting with .html | 102.4 B | ||
| 5. test and train data.html | 102.4 B | ||
| 6. Converting Celsius to Fahrenheit solution.mp4 | 8.6 MB | ||
| 6. Inverse transform coding exercise.html | 102.4 B | ||
| 6. Matrix subsetting with booleans.mp4 | 11.3 MB | ||
| 6. Normal approximation to gamma distribution.mp4 | 37.3 MB | ||
| 6. dbinom() intro.mp4 | 19 MB | ||
| 6. dbinom().mp4 | 35.2 MB | ||
| 6. matrix() 1.html | 102.4 B | ||
| 6. pexp() and memorylessness.mp4 | 41.4 MB | ||
| 6. pgeom(), the cdf.mp4 | 27.7 MB | ||
| 6. pnbinom().mp4 | 26.7 MB | ||
| 6. ppois().mp4 | 11.9 MB | ||
| 6. removing elements with -.html | 102.4 B | ||
| 6. rnorm(), mean, and sd.html | 102.4 B | ||
| 6. summary().html | 102.4 B | ||
| 6. testtrain quiz.html | 102.4 B | ||
| 6. vectors with c().html | 102.4 B | ||
| 7. Adding two vectors - weights of twins.html | 102.4 B | ||
| 7. Normal approximation to gamma distribution coding exercise.html | 102.4 B | ||
| 7. Vectors with c() solution.mp4 | 2.4 MB | ||
| 7. dbinom() exercise.html | 102.4 B | ||
| 7. dbinom().html | 102.4 B | ||
| 7. dim(), nrow(), ncol() quiz.html | 102.4 B | ||
| 7. matrix subsetting, rows that meet a boolean criterion.html | 102.4 B | ||
| 7. pexp() coding exercise.html | 102.4 B | ||
| 7. pgeom().html | 102.4 B | ||
| 7. pnorm().html | 102.4 B | ||
| 7. ppois() coding exercise.html | 102.4 B | ||
| 7. qnbinom().mp4 | 57 MB | ||
| 7. rchisq(), pchisq(), qchisq().html | 102.4 B | ||
| 7. summary() solution.mp4 | 12.2 MB | ||
| 8. Adding two vectors - weights of twins solution.mp4 | 8.5 MB | ||
| 8. Expected Value.mp4 | 78.5 MB | ||
| 8. Missing data and na.rm.mp4 | 5.9 MB | ||
| 8. Normal approximation to the negative binomial coding exercise.html | 102.4 B | ||
| 8. The colon .mp4 | 4.7 MB | ||
| 8. dnorm() and plotting, continuous distributions.html | 102.4 B | ||
| 8. qexp().mp4 | 7.7 MB | ||
| 8. qgeom().mp4 | 29 MB | ||
| 8. qpois().mp4 | 9.6 MB | ||
| 8. table().html | 102.4 B | ||
| 9. Variance and Standard Deviation.mp4 | 85.6 MB | ||
| 9. Vector and colon quiz.html | 102.4 B | ||
| 9. chi-square goodness of fit test by hand.html | 102.4 B | ||
| 9. qexp() coding exercise.html | 102.4 B | ||
| 9. qgeom() coding exercise.html | 102.4 B | ||
| 9. qnorm().html | 102.4 B | ||
| 9. qpois() coding exercise.html | 102.4 B | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 194 total files | |||
Master R for Statistics and Data Science
https://FreeCourseWeb.com
Published 3/2024
Created by Brian Greco
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 97 Lectures ( 5h 53m ) | Size: 2.67 GB
A former Google data scientist teaches you R starting with the basics, and learning common tools for data science.
What you'll learn:
Master the basic parts of R like vectors and matrices
Learn more complex data structures like data frames and lists
Learn R's probability functions for simulating data and calculating probabilities
Practice these skills using Udemy's built-in coding exercises
Requirements:
Some experience in programming or statistics is helpful, but no prior knowledge is assumed.
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 2.1 GB | freecoursewb | 3 weeks | 4 | 23 | |
| 5.7 GB | JackieALF | 3 weeks | 3 | 26 | |
| 5.92 GB | adapteryl | 1 month | 4 | 2 | |
|
Udemy - Master Hyperparameter Tuning - Bayesian Optimization and TPE Posted by
freecoursewb in Other
|
810.4 MB | freecoursewb | 1 month | 2 | 5 |
| 1.2 GB | freecoursewb | 1 month | 17 | 2 |
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