MY-ASSIGNMENTEXPERT™可以为您提供stat.psu.edu STAT501 Regression Analysis回归分析课程的代写代考和辅导服务！
这是埃伯利理学院回归分析课程的代写成功案例。
STAT501课程简介
This graduate level course offers an introduction into regression analysis. A researcher is often interested in using sample data to investigate relationships, with an ultimate goal of creating a model to predict a future value for some dependent variable. The process of finding this mathematical model that best fits the data involves regression analysis.
STAT 501 is an applied linear regression course that emphasizes data analysis and interpretation. Generally, statistical regression is collection of methods for determining and using models that explain how a response variable (dependent variable) relates to one or more explanatory variables (predictor variables).
Prerequisites
This graduate level course covers the following topics:
- Understanding the context for simple linear regression.
- How to evaluate simple linear regression models
- How a simple linear regression model is used to estimate and predict likely values
- Understanding the assumptions that need to be met for a simple linear regression model to be valid
- How multiple predictors can be included into a regression model
- Understanding the assumptions that need to be met when multiple predictors are included in the regression model for the model to be valid
- How a multiple linear regression model is used to estimate and predict likely values
- Understanding how categorical predictors can be included into a regression model
- How to transform data in order to deal with problems identified in the regression model
- Strategies for building regression models
- Distinguishing between outliers and influential data points and how to deal with these
- Handling problems typically encountered in regression contexts
- Alternative methods for estimating a regression line besides using ordinary least squares
- Understanding regression models in time dependent contexts
- Understanding regression models in non-linear contexts
STAT501 Regression Analysis HELP（EXAM HELP， ONLINE TUTOR）
Problem 1
Suppose we are modeling house price as depending on house size, the number of bedrooms in the house and the number of bathrooms in the house. Price is measured in thousands of dollars and size is measured in thousands of square feet.
Suppose our model is:
$$
P=20+50 \text { size }+10 \text { nbed }+15 \text { nbath }+\epsilon, \epsilon \sim N\left(0,10^2\right) .
$$
(a) Suppose you know that a house has size $=1.6$, nbed $=3$, and nbath $=2$.
What is the distribution of its price given the values for size, nbed, and nbath.
(hint: it is normal with mean $=? ?$ and variance $=? ?$ )
$\begin{aligned} & 20+50 \times 1.6+10 \times 3+15 \times 2=160 \ & P=160+\epsilon \text { so that } P \sim N\left(160,10^2\right)\end{aligned}$
(b) Given the values for the explanatory variables from part (a), give the 95\% predictive interval for the price of the house.
$$
160 \pm 20
$$
(c) Suppose you know that a house has size $=2.6$, nbed $=4$, and nbath $=3$. Give the $95 \%$ predictive interval for the price of the house.
$$
20+50 \times 2.6+10 \times 4+15 \times 3=235
$$
$P=235+\epsilon$ so that $P \sim N\left(235,10^2\right)$ and the $95 \%$ predictive interval is
$$
235 \pm 20
$$
(d) In our model the slope for the variable nbath is 15 . What are the units of this number?
Thousands of dollars per bathroom.
(e) What are the units of the intercept 20? What are the units of the the error standard deviation 10 ?
The intercept has the same units as $P \ldots$ in this case, thousands of dollars. The error std deviation is also in the same units as $P$, ie, thousands of dollars.
MY-ASSIGNMENTEXPERT™可以为您提供STAT.PSU.EDU STAT501 REGRESSION ANALYSIS回归分析课程的代写代考和辅导服务！
