Tuesdsay, October 11Th 1. Write Homework in Your Planner

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Tuesdsay, October 11th 1. Write homework in your planner - Study Guide due Tomorrow! 2. Today you will need - Notebook - Folder Hali A Comparing Decimals To determine which of two decimals is greater, you can compare the digits in each place-value position, or you can use a number line. Which is greater, 7.4 or 7.63? Method 1 Use place value 7.4 Line up the decimal points 7.63 Starting at the left, compare the digits in each place-value position. The digits in the tenths place are not the same. Since 6 tenths > 4 tenths, 7.63 > 7.4 Which is greater, 7.4 or 7.63? Method 2 Use a number line. Graph each decimal on a number line and compare. 7.4 7.63 7.0 7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8 7.9 8.0 On a number line, numbers to the right are greater than numbers to the left. 7.63 is to the right of 7.4, so 7.63 > 7.4 Which is larger? 63 hundredths 69 hundredths Erase between the two numbers to reveal the .63 .69 pull < answer. Compare. Drag and drop the symbol <, >, or = for each pair of decimals. 1. 7.23 > 7.2 > 2. 0.9 = 0.900 = 3. 0.622 > 0.62 < 4. 5.307 < 5.73 How do we order decimal numbers? Order 12.15, 12.08, and 12.103 from least to greatest. Step 1: Align the decimal points. 12.15 12.08 12.103 Step 2: Annex zeroes so that each number has the same number of decimal places. 12.15 0 12.08 0 12.103 Step 3: Use place value to compare the decimals. 12.08 < 12.103 < 12.15 Order the Decimals Least to Greatest Order the decimals least to greatest 35.5 Always make sure Helpfulyour decimals Hint are 30.53 lined up! 5.30 5.03 5.35 Write the numbers in the place value chart from least to greatest. ones . tenths hundredths 5.25 5.80 5.75 5.15 5.50 Sonja kept track of the amount of money she spent on lunch each day this week in the table below. Day Mon. Tues. Wed. Thu. Fri. Amount Spent ($) 4.45 4.39 4.23 4.53 4.38 Drag and drop the amounts to order from least to greatest. 4.23 (Wed.) 4.38 (Fri.) Pull 4.39 (Tues.) 4.45 (Mon.) 4.53 (Thu.) The table shows lifetime batting averages for leading baseball players. Lifetime Batting Averages for Drag and drop the players in Leading Team Players order of their ranking. Batting Player Team Avg. San Tony Gwynn Diego 0.338 Padres Derek New York 0.314 Jeter Yankees Edgar Seattle 1st place - Tony Gwynn Mariner 0.312 Martinez s New 2nd place - Derek Jeter Mike Piazza York 0.311 Mets Chipper Atlanta 3rd place - Edgar Martinez 0.303 Jones Braves 4th place - Mike Piazza 5th place - Chipper Jones Games.

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Problem of the Day Make a Scatter Plot of the Data. Is Linear Regression
Problem of the Day Weight in Static motion(kg) Weight(kg) Make a scatter plot 26 27.9 of the data. 29.9 29.1 Is linear regression 39.5 38.0 appropriate? Why 25.1 27.0 or why not? 31.6 30.3 36.2 34.5 25.1 27.8 31.0 29.6 35.6 33.1 40.2 35.5 Salary(in Problem of the Day Player Year millions) Nolan Ryan 1980 1.0 Is it appropriate to use George Foster 1982 2.0 linear regression Kirby Puckett 1990 3.0 to predict salary Jose Canseco 1991 4.7 from year? Roger Clemens 1996 5.3 Why or why not? Ken Griffey, Jr 1997 8.5 Albert Belle 1997 11.0 Pedro Martinez 1998 12.5 Mike Piazza 1999 12.5 Mo Vaughn 1999 13.3 Kevin Brown 1999 15.0 Carlos Delgado 2001 17.0 Alex Rodriguez 2001 22.0 Manny Ramirez 2004 22.5 Alex Rodriguez 2005 26.0 Chapter 10 ReExpressing Data: Get It Straight! Linear Regressioneasiest of methods, how can we make our data linear in appearance Can we reexpress data? Change functions or add a function? Can we think about data differently? What is the meaning of the yunits? Why do we need to reexpress? Methods to deal with data that we have learned 1. 2. Goal 1 making data symmetric Goal 2 make spreads more alike(centers are not necessarily alike), less spread out Goal 3(most used) make data appear more linear Goal 4(similar to Goal 3) make the data in a scatter plot more spread out Ladder of Powers(pg 227) Straightening is good, but limited multimodal data cannot be "straightened" multiple models is really the only way to deal with this data Things to Remember we want linear regression because it is easiest (curves are possible, but beyond the scope of our class) don't choose a model based on r or R2 don't go too far from the Ladder of Powers negative values or multimodal data are difficult to reexpress Salary(in Player Year Find an appropriate millions) Nolan Ryan 1980 1.0 linear model for the George Foster 1982 2.0 data.
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