Skip to content

Fixed issues causing intermittent knitr errors #147

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 3 commits into
base: master
Choose a base branch
from
Open
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
424 changes: 213 additions & 211 deletions 07_RegressionModels/01_01_introduction/index.Rmd

Large diffs are not rendered by default.

682 changes: 313 additions & 369 deletions 07_RegressionModels/01_01_introduction/index.html

Large diffs are not rendered by default.

12 changes: 6 additions & 6 deletions 07_RegressionModels/01_02_notation/index.Rmd
Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@ mode : selfcontained # {standalone, draft}
* We will try to minimize the amount of mathematics required for this class.
* No caclculus is required.

---


## Notation for data

Expand All @@ -35,7 +35,7 @@ mode : selfcontained # {standalone, draft}
* $X_i$ is a conceptual random variable.
* $x$ is a number that we plug into.

---

## The empirical mean

* Define the empirical mean as
Expand All @@ -55,7 +55,7 @@ The the mean of the $\tilde X_i$ is 0.
\sum_{i=1}^n (X_i - \mu)^2
$$

---


## The emprical standard deviation and variance

Expand All @@ -71,7 +71,7 @@ $S = \sqrt{S^2}$. Notice that the standard deviation has the same units as the d
* Sometimes people divide by $n$ rather than $n-1$ (the latter
produces an unbiased estimate.)

---

## Normalization

* The the data defined by
Expand All @@ -84,7 +84,7 @@ have empirical mean zero and empirical standard deviation 1.
* Example, a value of 2 form normalized data means that data point
was two standard deviations larger than the mean.

---

## The empirical covariance
* Consider now when we have pairs of data, $(X_i, Y_i)$.
* Their empirical covariance is
Expand All @@ -102,7 +102,7 @@ $$
where $S_x$ and $S_y$ are the estimates of standard deviations
for the $X$ observations and $Y$ observations, respectively.

---

## Some facts about correlation
* $Cor(X, Y) = Cor(Y, X)$
* $-1 \leq Cor(X, Y) \leq 1$
Expand Down
480 changes: 238 additions & 242 deletions 07_RegressionModels/01_02_notation/index.html

Large diffs are not rendered by default.

Loading