r cards at TU München

Arrow

100% for free

Arrow

Efficient learning

Arrow

100% for free

Arrow

Efficient learning

Arrow

Synchronization on all devices

Arrow Arrow

It’s completely free

studysmarter schule studium
d

4.5 /5

studysmarter schule studium
d

4.8 /5

studysmarter schule studium
d

4.5 /5

studysmarter schule studium
d

4.8 /5

Study with flashcards and summaries for the course r cards at the TU München

Exemplary flashcards for r cards at the TU München on StudySmarter:

False discovery rate:

Exemplary flashcards for r cards at the TU München on StudySmarter:

Family-wise error rate: Bonferroni correction

Exemplary flashcards for r cards at the TU München on StudySmarter:

Layers:

Exemplary flashcards for r cards at the TU München on StudySmarter:

Aesthetics:


Exemplary flashcards for r cards at the TU München on StudySmarter:

Family-wise error rate:

Exemplary flashcards for r cards at the TU München on StudySmarter:

Tidy data conclusions

Exemplary flashcards for r cards at the TU München on StudySmarter:

Separating and uniting (1 <-> more variables)


Exemplary flashcards for r cards at the TU München on StudySmarter:

Transform data form long to wide?

Exemplary flashcards for r cards at the TU München on StudySmarter:

Transform data from wide to long?

Exemplary flashcards for r cards at the TU München on StudySmarter:

Perform the conditional analysis by testing it with a full model that depends on the genotype (marker 5091) and a reduced model that does not depend on the genotype. full <- lm(growth_rate ~ genotype + condition_on_mk_geno, data=dt) reduced <- lm(growth_rate ~ condition_on_mk_geno, data=dt) anova(reduced, full) ## Analysis of Variance Table ## ## Model 1: growth_rate ~ condition_on_mk_geno ## Model 2: growth_rate ~ genotype + condition_on_mk_geno ## Res.Df RSS Df Sum of Sq F Pr(>F) ## 1 152 208.28 ## 2 151 207.23 1 1.0414 0.7588 0.3851

Exemplary flashcards for r cards at the TU München on StudySmarter:

Grammar of Graphics

Exemplary flashcards for r cards at the TU München on StudySmarter:

m <- lm(y ~ x1 * x2)

Your peers in the course r cards at the TU München create and share summaries, flashcards, study plans and other learning materials with the intelligent StudySmarter learning app.

Get started now!

Flashcard Flashcard

Exemplary flashcards for r cards at the TU München on StudySmarter:

r cards

False discovery rate:

E[V/ max(R, 1) ] , the expected fraction of false positives among all discoveries.

r cards

Family-wise error rate: Bonferroni correction

Family-wise error rate: P(V > 0) , the probability of one or more false positives. For large m0 , this is
di cult to keep small.
Bonferroni adjusted p-values:
m
· Suppose we conduct hypothesis tests for each g = 1, . . . , m , producing each a p-value pg
p = min{m , 1}
˜g
pg
Selecting all tests with p ≤ α˜g
Proof: Boole’s inequality implies:

i=1
pi
controls the FWER at level , ie.,α Pr(V > 0) ≤ α .
FWER = P{ ( ≤ ) } ≤ {P( ≤ ) } = m0
m0
α
m
m0

i=1
pi
α
m
α
m
≤ m = α.
α
m
This control does not require any assumptions about dependence among the p-values or about how
many of the null hypotheses are true.
In R: p.adjust(p_values, method = “bonferroni”)

r cards

Layers:

made up of geometric objects that represent data (geom_)

points, lines, boxplots, …

r cards

Aesthetics:


describes visual characteristics that represent data (aes)
· position (x,y), color, size, shape, transparency

r cards

Family-wise error rate:

P(V > 0) , the probability of one or more false positives. For large m0 , this is
di cult to keep small.

r cards

Tidy data conclusions

For data to be considered tidy, it has to pass certain criteria

Each column must represent one and only one variable indicated in its name.
Columns musn’t be values (eg. 1999, $10-20k).
Must be aggregated in the right amount of tables – avoid lists.

r cards

Separating and uniting (1 <-> more variables)


1 variable -> multiple variables
multiple variables -> 1 variable
other useful functions:
– tidyr::separate()
– tidyr::unite()
– data.table::tstrsplit, strsplit, paste, substr

r cards

Transform data form long to wide?

data.table::dcast()
tidyr::spread()

r cards

Transform data from wide to long?

data.table::melt()
tidyr::gather()

r cards

Perform the conditional analysis by testing it with a full model that depends on the genotype (marker 5091) and a reduced model that does not depend on the genotype. full <- lm(growth_rate ~ genotype + condition_on_mk_geno, data=dt) reduced <- lm(growth_rate ~ condition_on_mk_geno, data=dt) anova(reduced, full) ## Analysis of Variance Table ## ## Model 1: growth_rate ~ condition_on_mk_geno ## Model 2: growth_rate ~ genotype + condition_on_mk_geno ## Res.Df RSS Df Sum of Sq F Pr(>F) ## 1 152 208.28 ## 2 151 207.23 1 1.0414 0.7588 0.3851
## note: observe the probability under the null hypothesis of an F statistic as
## extreme as the one observed here is rather high (> 0.05) so we would not
## reject the null hypothesis

r cards

Grammar of Graphics

The Grammar of Graphics is a visualization theory developed by Leland Wilkinson in 1999.

Separation of data from aesthetics (e.g. x and y axis, color-coding)
Denition of common plot/chart elements (e.g. dot plots, boxplots, etc.)
Composition of these common elements (one can combine elements as layers)

r cards

m <- lm(y ~ x1 * x2)
lm(response ~ terms):
where response is the (numeric) response vector and terms is a series of terms which specifies a linear predictor for response.

Sign up for free to see all flashcards and summaries for r cards at the TU München

Singup Image Singup Image
Wave

Other courses from your degree program

For your degree program at the TU München there are already many courses on StudySmarter, waiting for you to join them. Get access to flashcards, summaries, and much more.

Back to TU München overview page

What is StudySmarter?

What is StudySmarter?

StudySmarter is an intelligent learning tool for students. With StudySmarter you can easily and efficiently create flashcards, summaries, mind maps, study plans and more. Create your own flashcards e.g. for r cards at the TU München or access thousands of learning materials created by your fellow students. Whether at your own university or at other universities. Hundreds of thousands of students use StudySmarter to efficiently prepare for their exams. Available on the Web, Android & iOS. It’s completely free.

Awards

Best EdTech Startup in Europe

Awards
Awards

EUROPEAN YOUTH AWARD IN SMART LEARNING

Awards
Awards

BEST EDTECH STARTUP IN GERMANY

Awards
Awards

Best EdTech Startup in Europe

Awards
Awards

EUROPEAN YOUTH AWARD IN SMART LEARNING

Awards
Awards

BEST EDTECH STARTUP IN GERMANY

Awards

How it works

Top-Image

Get a learning plan

Prepare for all of your exams in time. StudySmarter creates your individual learning plan, tailored to your study type and preferences.

Top-Image

Create flashcards

Create flashcards within seconds with the help of efficient screenshot and marking features. Maximize your comprehension with our intelligent StudySmarter Trainer.

Top-Image

Create summaries

Highlight the most important passages in your learning materials and StudySmarter will create a summary for you. No additional effort required.

Top-Image

Study alone or in a group

StudySmarter automatically finds you a study group. Share flashcards and summaries with your fellow students and get answers to your questions.

Top-Image

Statistics and feedback

Always keep track of your study progress. StudySmarter shows you exactly what you have achieved and what you need to review to achieve your dream grades.

1

Learning Plan

2

Flashcards

3

Summaries

4

Teamwork

5

Feedback