×

### Let's log you in.

or

Don't have a StudySoup account? Create one here!

×

or

by: Sydney Clark

2

0

3

# Statistics 121 notes week 4 STAT 121

Marketplace > Brigham Young University > STAT 121 > Statistics 121 notes week 4
Sydney Clark
BYU
GPA 4.0

Get a free preview of these Notes, just enter your email below.

×
Unlock Preview

Talking about responsive and explanatory variable, linear regression, and risiduals
COURSE
Principles of Statistics
PROF.
Dr. Christopher Reese
TYPE
Class Notes
PAGES
3
WORDS
CONCEPTS
Statistics
KARMA
25 ?

## Popular in Department

This 3 page Class Notes was uploaded by Sydney Clark on Friday September 23, 2016. The Class Notes belongs to STAT 121 at Brigham Young University taught by Dr. Christopher Reese in Winter 2016. Since its upload, it has received 2 views.

×

## Reviews for Statistics 121 notes week 4

×

×

### What is Karma?

#### You can buy or earn more Karma at anytime and redeem it for class notes, study guides, flashcards, and more!

Date Created: 09/23/16
Stats 121 notes week 4 *IMPORTANT* *SAMPLE QUIZ QUESTIONS*  Intro to Linear Regression o Correlation: One­number summary gives strength and direction of linear  relationship o Correlation: Does NOT indicate location or steepness of linear relationship o Regression  Summarizes linear pattern of scatterplot using “best­fitting” straight line  Requires that one variable be as explanatory and the other as response. o Statistical model  Mathematical expression for mean that relates response to explanatory  Allows for variation in response  Mean of y is a straight line function of x  What ability does regression give you that correlation does not? (y = resp., x = expl.)   (a) calculate x given y   (b) calculate mean of x given y   (c) calculate y given x      (d) calculate mean of y given x o Examples   mean systolic blood pressure as straight line function of age  • mean income for bank tellers as straight line function of number of years in school  mean profit as straight line function of minutes of advertising o Regression notation  yˆ=a+bx where: A=intercept B=slope yˆ=predicted y­value (mean of y for given x) o Regression line  Also called best fitting line, least squares line, least squares regression line  Line for which sum of squared vertical deviations of dots from line is  minimized Vertical deviation= the difference between the observed y and the  predicted y (also known as Residuals or prediction error) o Residuals  o o  If actual number is larger than predicted number the outcome is positive o Simple formulas for slope and intercept  Y^=a+bx  B= r Sy/Sx  A=Y bar­bX bar o Interpretatin of slope b  Change in the mean of y when x increases by 1 unit  Mean height of sons increases by abour .61 inc for every 1 inch increase in the heights of fathers o Interpretation of intercept a  Technically, mean of y when x is 0—anchors line in place, but not always  meaningful.  Mean height of sons predicted to be 25.68 inches when the height of  fathers is 0 inches! o Interpretation of predicted y hat  Mean of y when x equals a certain value  Mean height of sons for fathers who are 70 inches tall is 25.68+.61(70) o VERY RARLEY IS “SLOPE” USED. THEY WRITE THE NAME OF THE X  INTERECPT o Intercept is ‘a’ and slope is ‘b’  Correlation is an okay way to determine the strength of two variables but it doesn’t not  have a good interpretation.  Squared correlation (r^2) o R^2=% of the variability in y that is explained by the relationship between x and y o R^2 agrees with our i  Variability= how spread out the points are  Extrapolation: “extrapolation is bad” use of regression line to estimate mean of y for c far outside x­range of data o Problem: no information on nature of relationship outside x­range  All relationships bend somewhere  

×

×

### BOOM! Enjoy Your Free Notes!

×

Looks like you've already subscribed to StudySoup, you won't need to purchase another subscription to get this material. To access this material simply click 'View Full Document'

## Why people love StudySoup

Jim McGreen Ohio University

#### "Knowing I can count on the Elite Notetaker in my class allows me to focus on what the professor is saying instead of just scribbling notes the whole time and falling behind."

Janice Dongeun University of Washington

#### "I used the money I made selling my notes & study guides to pay for spring break in Olympia, Washington...which was Sweet!"

Steve Martinelli UC Los Angeles

#### "There's no way I would have passed my Organic Chemistry class this semester without the notes and study guides I got from StudySoup."

Parker Thompson 500 Startups

#### "It's a great way for students to improve their educational experience and it seemed like a product that everybody wants, so all the people participating are winning."

Become an Elite Notetaker and start selling your notes online!
×

### Refund Policy

#### STUDYSOUP CANCELLATION POLICY

All subscriptions to StudySoup are paid in full at the time of subscribing. To change your credit card information or to cancel your subscription, go to "Edit Settings". All credit card information will be available there. If you should decide to cancel your subscription, it will continue to be valid until the next payment period, as all payments for the current period were made in advance. For special circumstances, please email support@studysoup.com

#### STUDYSOUP REFUND POLICY

StudySoup has more than 1 million course-specific study resources to help students study smarter. If you’re having trouble finding what you’re looking for, our customer support team can help you find what you need! Feel free to contact them here: support@studysoup.com

Recurring Subscriptions: If you have canceled your recurring subscription on the day of renewal and have not downloaded any documents, you may request a refund by submitting an email to support@studysoup.com