Answer:
Interference for regression
Explanation:
Interference for regression is the most suitable statistical test to use to find out if there is any link between number of missed classes and the final test scores.
Because those two variables are related and student test score can be predicted using number of classes that are missed.
Step-by-step explanation:
28+10t is the simplest expression
Answer: y= -4x-2
Step-by-step explanation:
glad i could help!
The image is kinda blurry, but from what I can gather, the notation in the attachment means
![p_X[x_k]\equiv\mathbb P(X=k)=\begin{cases}(1-p)^{k-1}p&\text{for }k=1,2,\ldots\\0&\text{otherwise}\end{cases}](https://tex.z-dn.net/?f=p_X%5Bx_k%5D%5Cequiv%5Cmathbb%20P%28X%3Dk%29%3D%5Cbegin%7Bcases%7D%281-p%29%5E%7Bk-1%7Dp%26%5Ctext%7Bfor%20%7Dk%3D1%2C2%2C%5Cldots%5C%5C0%26%5Ctext%7Botherwise%7D%5Cend%7Bcases%7D)
Then
a)
![p_X[x_k\le4]\equiv\mathbb P(X\le4)=\mathbb P(X=1)+\mathbb P(X=2)+\mathbb P(X=3)+\mathbb P(X=4)](https://tex.z-dn.net/?f=p_X%5Bx_k%5Cle4%5D%5Cequiv%5Cmathbb%20P%28X%5Cle4%29%3D%5Cmathbb%20P%28X%3D1%29%2B%5Cmathbb%20P%28X%3D2%29%2B%5Cmathbb%20P%28X%3D3%29%2B%5Cmathbb%20P%28X%3D4%29)
b)
c)
![p_X[1\le x_k\le2]\equiv\mathbb P(1\le X\le2)=\mathbb P(X=1)+\mathbb P(X=2)](https://tex.z-dn.net/?f=p_X%5B1%5Cle%20x_k%5Cle2%5D%5Cequiv%5Cmathbb%20P%281%5Cle%20X%5Cle2%29%3D%5Cmathbb%20P%28X%3D1%29%2B%5Cmathbb%20P%28X%3D2%29)
A + b = 8
a - b = -4
a = b - 4
(b - 4) + b = 8
2b - 4 = 8
2b = 12
b = 6
a + 6 = 8
a = 2
a = 2
b = 6
2 + 6 = 8
2 - 6 = -4
