User talk:Akerge: Difference between revisions
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Review first 10 minutes of 22.03.16 lecture. | Review first 10 minutes of 22.03.16 lecture. | ||
Starting from page 203 from "Introduction to Statistics", including Binomial, Poisson, multinomial distributions until 7th chapter regarding normal distributions. What is a normal deviation? What is a percentile? Finish exercises. | Starting from page 203 from "Introduction to Statistics", including Binomial, Poisson, multinomial distributions until 7th chapter regarding normal distributions. What is a normal deviation? What is a percentile? Finish the exercises. | ||
'''From the book''' | |||
* Probability density function | |||
* Bernoulli trials (Binomial Probability Formula) | |||
* Cumulative distribution | |||
<code> | |||
pnorm | |||
qnorm | |||
dnorm | |||
etc. | |||
runif(n,a,b) | |||
dunif(x,a,b) | |||
punif(x,a,b) | |||
</code> | |||
* Central Limit Theorem | |||
All of the above can be found from pages 203–211 and 249–272. | |||
Also: | |||
* Advanced Graphics from pages 273–299: | |||
** qq-plots – to compare distributions | |||
** Cumulative distribution function (CDF) | |||
** Contour plots | |||
** 3D plots (rgl lib) | |||
'''Midterm exam retake is on 29th of April from 8 'til 10.''' | |||
* Review the practice video of 19th of April, last 30 min. | |||
'''Go through (watch) these courses:''' | |||
* [https://www.khanacademy.org/math/probability/statistics-inferential Inferential Statistics] | |||
* [https://www.khanacademy.org/math/probability/descriptive-statistics Descriptive Statistics] | |||
* Read the corresponding chapters in Online Stat Book & finish the exercises | |||
'''TO READ from lectures''' | |||
*12.04 Sampling Distribution | |||
*19.04 Sampling Distributions, p. 300-328 | |||
*26.04 Estimation, p. 329-369 | |||
*[https://en.wikipedia.org/wiki/Shapiro%E2%80%93Wilk_test Shapiro-Wilk test] | |||
==OS's== | ==OS's== | ||
| Line 21: | Line 69: | ||
Review 17.03 lectures | Review 17.03 lectures | ||
REVIEW YaLP with bpython | |||
==Web | ==Web Dev== | ||
* Finish SQLite track on Codecademy | * Finish SQLite track on Codecademy | ||
* Get on track with the Lauri's git | * Get on track with the Lauri's git | ||
* Standalone temperature monitor that can be used without external power and the curve output to a web page. | * Standalone temperature monitor that can be used without external power and the curve output to a web page. | ||
'''Exam:''' | |||
* Up to 3 tables | |||
* Up to 5 views | |||
* Able to write PHP | |||
* Able to write SQL: select, join, insert, update | |||
** Has to avoid SQL injections! | |||
* Has to use cookies | |||
* Validate W3C validator | |||
* Basic CSS (Desktop + Mobile) | |||
* Basic JS (ajax?) | |||
* DEPLOYMENT | |||
Twiddle with this https://beta.hacksaw.academy/ | |||
==InfoSys Analysis== | ==InfoSys Analysis== | ||
| Line 32: | Line 94: | ||
==Intro to Cybersec== | ==Intro to Cybersec== | ||
* ''' Review first 20 min of 06.04.2016 lecture''' | |||
** EIK 2016 | |||
* Keep an eye on what's happening in Cybersec industry. Enforce the habit | * Keep an eye on what's happening in Cybersec industry. Enforce the habit | ||
* What will be the presentation topic(/demo) ? | * What will be the presentation topic(/demo) ? | ||
Latest revision as of 10:16, 17 May 2016
Homeworks
Statisticks
Finish Udemy R basics course.
Review first 10 minutes of 22.03.16 lecture. Starting from page 203 from "Introduction to Statistics", including Binomial, Poisson, multinomial distributions until 7th chapter regarding normal distributions. What is a normal deviation? What is a percentile? Finish the exercises.
From the book
- Probability density function
- Bernoulli trials (Binomial Probability Formula)
- Cumulative distribution
pnorm
qnorm
dnorm
etc.
runif(n,a,b)
dunif(x,a,b)
punif(x,a,b)
- Central Limit Theorem
All of the above can be found from pages 203–211 and 249–272.
Also:
- Advanced Graphics from pages 273–299:
- qq-plots – to compare distributions
- Cumulative distribution function (CDF)
- Contour plots
- 3D plots (rgl lib)
Midterm exam retake is on 29th of April from 8 'til 10.
- Review the practice video of 19th of April, last 30 min.
Go through (watch) these courses:
- Inferential Statistics
- Descriptive Statistics
- Read the corresponding chapters in Online Stat Book & finish the exercises
TO READ from lectures
- 12.04 Sampling Distribution
- 19.04 Sampling Distributions, p. 300-328
- 26.04 Estimation, p. 329-369
- Shapiro-Wilk test
OS's
Review homework
Python
Finish CodeCademy course!
Do CodingBat exercises daily!
Start programming with Raspberry!
Review 17.03 lectures
REVIEW YaLP with bpython
Web Dev
- Finish SQLite track on Codecademy
- Get on track with the Lauri's git
- Standalone temperature monitor that can be used without external power and the curve output to a web page.
Exam:
- Up to 3 tables
- Up to 5 views
- Able to write PHP
- Able to write SQL: select, join, insert, update
- Has to avoid SQL injections!
- Has to use cookies
- Validate W3C validator
- Basic CSS (Desktop + Mobile)
- Basic JS (ajax?)
- DEPLOYMENT
Twiddle with this https://beta.hacksaw.academy/
InfoSys Analysis
Keep an eye on workshops and quizzes.
Intro to Cybersec
- Review first 20 min of 06.04.2016 lecture
- EIK 2016
- Keep an eye on what's happening in Cybersec industry. Enforce the habit
- What will be the presentation topic(/demo) ?
Networking
Finish networking labs and exam ASAP!
