Warm-up A.P. Stats – Ch. 3 Activity; Stats – Linear Regression Wksheet

Slides:



Advertisements
Similar presentations
Residuals.
Advertisements

HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Section 12.2.
2-7 Curve Fitting with Linear Models Warm Up Lesson Presentation
Warm-up A.P. Stats 3.4 Diagnostic Notes/ Stats – Candy Activity
Chapter 3 Bivariate Data
Warm up Use calculator to find r,, a, b. Chapter 8 LSRL-Least Squares Regression Line.
Warm-up Ch. 3 Activity 1) 2) 3) 4) 5). Student of the day! Block 1.
AP Statistics Mrs Johnson
Regression and Correlation
Correlation A correlation exists between two variables when one of them is related to the other in some way. A scatterplot is a graph in which the paired.
H OW TECHNOLOGY CAN MAKE MY LIFE EASIER WHEN GRAPHING ! Compute (using technology) and interpret the correlation coefficient of a linear fit. MAFS.912.S-ID.3.8.
P.33 #14-19, p. 34 #32-34, Lesson Scatter Plots and Least-Squares Lines.
Warm-up Day of Ch. 7 Review Free Response A h.s. math teacher believes the greater number of hours of sleep before taking an AP exam, the better the score.
Warm-up with Multiple Choice Practice on 3.1 to 3.3
Warm-up A. P Stats Shape-Changing Transformations/ Stats – 3.4 Diagonstics Copy the two columns and match them.
Warm-up with 3.3 Notes on Correlation The fat and calorie contents of 5oz of 3 kinds of pizza are represented by the data points (9, 305), (11, 309)
Warm-up Ch. 3 Practice Test
Warm-up 3.2 Getting a line on the pattern Suppose you were to collect data for each pair of variables. You want to make a scatterplot. Which variable would.
Warm-up with 3.3 Notes on Correlation
Biostatistics Unit 9 – Regression and Correlation.
New Seats – Block 1. New Seats – Block 2 Warm-up with Scatterplot Notes 1) 2) 3) 4) 5)
Least-Squares Regression Section 3.3. Why Create a Model? There are two reasons to create a mathematical model for a set of bivariate data. To predict.
Warm-up 3.4 Diagnostic of Influential Points 4) 5) 6)
1 Chapter 10, Part 2 Linear Regression. 2 Last Time: A scatterplot gives a picture of the relationship between two quantitative variables. One variable.
Get out your Interpretation WS! You will be able to predict values based on a regression line. You will be able to communicate the risk in extrapolation.
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
Warm-up with 3.3 Notes on Correlation Universities use SAT scores in the admissions process because they believe these scores provide some insight into.
Warm-up Day of Ch. 6 Practice Test 4% of people have AB blood. What the probability that there is a Type AB donor among the first five people checked?
Warm-up Day 2 of Review and Day before Ch. 1 and Ch. 2 Test Multiple Choice Warm-up # ) 2) 3) 4) Complete #5 – 8 multiple choice the day of test.
Regression Regression relationship = trend + scatter
Warm-up An Exercise in Sampling: Rolling Down the River
Regression.
WARM-UP Do the work on the slip of paper (handout)
Warm-up Ch. 3 Textbook Review A simple random sample of eight drivers was selected. All eight drivers are insured with the same insurance company, and.
7-3 Line of Best Fit Objectives
Warm Up Feel free to share data points for your activity. Determine if the direction and strength of the correlation is as agreed for this class, for the.
Quick Start Expectations 1.Fill in planner and HWRS HW: p. 98, #4-5, Get a signature on HWRS 3.On desk: calculator, journal, HWRS, pencil, pen.
Least Squares Regression Remember y = mx + b? It’s time for an upgrade… A regression line is a line that describes how a response variable y changes as.
Linear Regression Day 1 – (pg )
Residuals Recall that the vertical distances from the points to the least-squares regression line are as small as possible.  Because those vertical distances.
Warm-up O Turn in HW – Ch 8 Worksheet O Complete the warm-up that you picked up by the door. (you have 10 minutes)
LSRLs: Interpreting r vs. r 2 r – “the correlation coefficient” tells you the strength and direction between two variables (x and y, for example, height.
Unit 4 Lesson 3 (5.3) Summarizing Bivariate Data 5.3: LSRL.
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
6.7 Scatter Plots. 6.7 – Scatter Plots Goals / “I can…”  Write an equation for a trend line and use it to make predictions  Write the equation for a.
Chapter 5 Lesson 5.2 Summarizing Bivariate Data 5.2: LSRL.
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
Chapter 3: Describing Relationships
CHAPTER 5: Regression ESSENTIAL STATISTICS Second Edition David S. Moore, William I. Notz, and Michael A. Fligner Lecture Presentation.
Describing Relationships. Least-Squares Regression  A method for finding a line that summarizes the relationship between two variables Only in a specific.
1. Analyzing patterns in scatterplots 2. Correlation and linearity 3. Least-squares regression line 4. Residual plots, outliers, and influential points.
 Understand how to determine a data point is influential  Understand the difference between Extrapolation and Interpolation  Understand that lurking.
Warm-up Get a sheet of computer paper/construction paper from the front of the room, and create your very own paper airplane. Try to create planes with.
Lesson 4.5 Topic/ Objective: To use residuals to determine how well lines of fit model data. To use linear regression to find lines of best fit. To distinguish.
Unit 4 LSRL.
LSRL.
Least Squares Regression Line.
Sections Review.
Regression and Correlation
Chapter 5 LSRL.
LSRL Least Squares Regression Line
Chapter 3.2 LSRL.
Least Squares Regression Line LSRL Chapter 7-continued
residual = observed y – predicted y residual = y - ŷ
Chapter 5 LSRL.
Chapter 5 LSRL.
Chapter 5 LSRL.
11C Line of Best Fit By Eye, 11D Linear Regression
Day 68 Agenda: 30 minute workday on Hypothesis Test --- you have 9 worksheets to use as practice Begin Ch 15 (last topic)
Ch 9.
Presentation transcript:

Warm-up A.P. Stats – Ch. 3 Activity; Stats – Linear Regression Wksheet If we are trying to predict a value of y from a value x, it is called Interpolation, if we are predicted an x-value within the range of xvalues. It is called extrapolation if we are predicted from a value of x outside the x-values. (months) Age: 18 19 20 21 22 23 24 25 26 27 Height:76 77.1 78.1 78.3 78.8 79.4 79.9 81.3 81.1 82.0 (cm) Find the Linear Regression for the data above and find the height of a 19.4 month year old. This is considered to be a(n) _____________. 2) Predict the height of 29 month old using the linear regression line from 1). This is considered to be a(n) ______________ .

A.P. Stastics and Statistics H.W. Answers E #27, and 34; AP Stats 37 27. a. 0.66 b. 0.25 c.-0.06 d. 0.04 e. 0.85 f. 0.52 g. 0.9 h. 0.74 34. R = 0.5 sx = 4.3 = 11.7 sy = 8.3 = 82.7 37 a. Life span will be longer for larger animals because it takes them longer to reach adulthood, that does not mean they have larger brains. Think alligators. b. Inflation is really to blame for increasing the prices of cheeseburgers and tuition. c. Websites have increased steadily since the creation of the internet and stock prices raise naturally due to inflation. Not related to eachother.

A.P. Statistics H.W. Answer to 38 38. a. Calorie content and fat content is 0.95 Calorie content and saturated fat content is 0.95 fat content and saturated fat content is 0.95 sodium content and calorie content is -0.5 sodium content and fat content is – 0.5 sodium conent and saturated fat content is – 0.5 b. Negative correlation indicates as one value goes up the other goes down. There might be a lurking variable affecting the relationship. c. Some cheese that had more fat, had less sodium, but that didn’t necessarily mean that all low-fat cheese had more sodium. Some manufacturers added more sodium to their lowfat cheeses to add flavor.

Computer Printout

Computing r2 from Printout

Answers to Multiple Choice 1)d 2)c 3)a 4)c 5)c 6)b 7)c 8)b 9)e

Student of the day! Block 4

Student of the day! Block 5

Student of the day! Block 6

A.P. Statistics Directions for Activity Everyone is writing on their own sheet and graph paper. Everyone is working with their table mates (3-4 people). Read carefully what you are actually graphing on paper. Notice the rubric at the end. The 10 pts for bringing the candy will be added after your score is calculated out of 100 (Score/25) + 10 = 100. Every answer for #1 – 10 should be in a complete sentence, unless you want to lose points. * When you are finished work on the Linear Regression Worksheet , I will put up specific directions about the Linear Regression worksheet soon! Follow these!!!

Statistics Directions for Quiz Answers for #1 ,2 and 4 are multiple choice. #3 has to be answered on a separate sheet of paper. a. Plot the points on graph paper and on your calculator. b. When you calculate the LSRL using your calculator you need to mark it on your graph on your graph paper. Be sure to answer c – f in complete sentences. For 3g. Make a table showing women, men (actual), predicted, and residual and use that table to show that the sum of the residuals is zero.

Statistics H.W. 3.3 H.W. Solve #37 and 38. Bring graph paper for the activity next class. Bring multiple choice problems, with Linear Regressionworksheet on the back, we will be working on this next class as well. Optional extra 10 pts to Ch. 3 Activity. Bring a bag of small square or round shaped wrapped candy like Starbursts or Jolly Ranchers.

Instructions for Linear Regression Worksheet H.W. 1) Be sure to have age as your x values and muscle mass as y. 11) You will list the residuals in order by the x values 43 45 45 … 78 Put them in a table. -11.5 14.0 -12.7 … 8.8

Table for # 11 to help with residual plot