Complete Week 8 Package

Transcription

1 Complete Week 8 Package 2015

2 Table of Contents Unit 3 Pacing Chart Lesson Plans Day 36 Bellringer Day 36 Activity Day 36 Practice Day 36 Practice Day 36 Exit Slip Day 37 Bellringer Day 37 Practice Day 37 Exit Slip Day 38 Bellringer Day 38 Practice Day 38 Exit Slip Day 39 Bellringer Day 39 Activity Day 39 Activity Day 39 Practice Day 39 Exit Slip Weekly Assessment

3 CCSS Algebra 1 Pacing Chart Unit 3 Unit Week Day CCSS Standards Mathematical Practices Objective I Can Statements 3 Modeling Linear Data 3 Modeling Linear Data 3 Modeling Linear Data 8 Data to Functions 8 Data to Functions 8 Data to Functions CCSS.MATH.CONTENT.HSS.ID.B.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. CCSS.MATH.CONTENT.HSS.ID.B.6.A Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models. CCSS.MATH.CONTENT.HSS.ID.B.6.B Informally assess the fit of a function by plotting and analyzing residuals. CCSS.MATH.CONTENT.HSS.ID.B.6.C Fit a linear function for a scatter plot that suggests a linear association. CCSS.MATH.CONTENT.HSN.Q.A.2 Define appropriate quantities for the purpose of descriptive modeling. CCSS.MATH.CONTENT.HSS.ID.B.6.A Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models. CCSS.MATH.PRACTIC E.MP1 Make sense of problems and persevere in solving them. CCSS.MATH.PRACTIC E.MP4 Model with mathematics. CCSS.MATH.PRACTIC E.MP6 Attend to precision. CCSS.MATH.PRACTIC E.MP7 Look for and make use of structure. CCSS.MATH.PRACTIC E.MP6 Attend to precision. CCSS.MATH.PRACTIC E.MP7 Look for and make use of structure. Students will be able to make predictions using a trend line from a scatter plot. Students will be able to fit a linear function (trend line) to a scatter plot with and without technology. Students will be able to create a scatter plot of bivariate data and estimate a linear function that fits the data and use this function to solve problems in the context of the data. I can make predictions using a trend line from a scatter plot. I can fit a linear function (trend line) to a scatter plot with and without technology. I can create a scatter plot of data and estimate a linear function that fits the data and use this function to solve problems in the context of the data Page 1

4 CCSS Algebra 1 Pacing Chart Unit 3 3 Modeling Linear Data 3 Modeling Linear Data 8 Data to Functions 8 Data to Functions 39 CCSS.MATH.CONTENT.HSN.Q.A.2 Define appropriate quantities for the purpose of descriptive modeling. CCSS.MATH.PRACTIC E.MP6 Attend to precision. CCSS.MATH.PRACTIC E.MP7 Look for and make use of structure. Students will be able to determin the line of best fit for a set of data and use it to make predictions. I can determin the line of best fit for a set of data and use it to make predictions. 40 Assessment Assessment Assessment Assessment 2015 Page 2

5 Lesson Plans for CCSS Algebra 1 Unit 3 Modeling Linear Data Week 8 Data to Functions Day 36 Common Core State Standard(s): CCSS.MATH.CONTENT.HSS.ID.B.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. CCSS.MATH.CONTENT.HSS.ID.B.6.A Fit a function to the data; use functions fitted to data to solve problems in the conte Mathematical Practices: CCSS.MATH.PRACTICE.MP1 Make sense of problems and persevere in solving them. CCSS.MATH.PRACTICE.MP4 Model with mathematics. Objective: Students will be able to make predictions using a trend line from a scatter plot. I Can: I can make predictions using a trend line from a scatter plot. Procedure: 1. Students will complete the bellringer. 2. Students will work in groups of 5 or 6 and complete the Day 36 Activity relating their height and their foot length. 3. The class will work through the Day 36 presentation on scatterplots. 4. Students will practice finding trend lines from scatterplots independently. 5. Students will complete the exit slip before leaving for the day Resources: Bellringer 36 Day 36 Activity Day 36 Presentation Day 36 Practice Exit Slip 36 Technology: Create Scatter Plot in Excel 2015 Page 3

6 Lesson Plans for CCSS Algebra 1 Aligned Assessment Example (if applicable): A group of 66 students took two tests; Test A and Test B. In the scatter diagram, each square represents one student and shows the scores that the students got in the two tests. 1. The mean for Test A was 19 and the mean score for Test B was 16. Plot a point to show this on the scatter diagram. 2. Draw a line of best fit on the scatter diagram. How can a line of best fit be used? Credit: Inside Mathematics; Reflection: 2015 Page 4

7 Day 36 Bellringer Name Day 36 Graph and find the slope of each line 1. y. 8 x 5 3. y = 2 3 x 1 2. y = 1 2 x x + 3y = Page 5

8 Day 36 Bellringer Name Answer Key Day Page 6

9 Day 36 Activity Name Work in a group with 5 or 6 students. 1. Measure and record each person s height and foot length. Names Height Foot Length 2. Graph the data (height, foot) on a coordinate plane. 3. Does your graph consist of points or a line? Why? 4. On the basis of your graph, make a statement about the relationship between height and foot length Page 7

10 Day 36 Activity Name Answer Key Answers will vary but students should see a scatter plot with a positive correlation Page 8

11 Day 36 Practice Name In Exercises 1 6, (a) draw a scatter plot of the data, (b) approximate the best-fitting line, and (c) estimate y when x = Page 9

12 Day 36 Practice Name MULTIPLE CHOICE Which equation best models the data in the scatter plot? 8. ERROR ANALYSIS The graph shows one student s approximation of the best-fitting line for the data in the scatter plot. Describe and correct the error in the student s work Page 10

13 Day 36 Practice Name Answer Key In Exercises 9 14, (a) draw a scatter plot of the data, (b) draw a line of best fit, (c) describe the correlation Positive Linear 4. Negative Linear 5. Negative Linear 6. Positive Linear Positive Linear Negative Linear 2015 Page 11

14 Day 36 Practice Name 7. MULTIPLE CHOICE Which equation best models the data in the scatter plot? B. 8. ERROR ANALYSIS The graph shows one student s approximation of the best-fitting line for the data in the scatter plot. Describe and correct the error in the student s work. The line should go through the middle of the data points 2015 Page 12

15 Day 36 Practice 2 Name The coaches of a group of debate teams answered a survey about hours of debate, team practice and number of team wins. The graph shows the results of this survey. 1. What is the correlation of the scatter plot? 2. Based on these results, if a team practices 4 hours per week next season, find an estimate of the number of debates the team can expect to win? Josie and some of her friends rode motorcycles all day on Saturday. She made a table that showed the number of gallons of gas remaining at the end of each hour. The scatterplot below shows the gas that remained in terms of the hours that had passed. 3. What is the correlation between the gas that remained and the hours that had passed? 4. Teresa records the ages and weights of 12 children in her neighborhood. If she records this data in a scatterplot, what type of relationship will she most likely see? A Positive correlation B Negative correlation C No correlation D Constant correlation 2015 Page 13

16 Day 36 Practice 2 Name A carpenter recorded the amount of money he earned for different jobs and the amount of time he spent on each job. The data are shown in the scatterplot below: 5. Based on the data, estimate the amount of money the carpenter would earn from a job that took 5 days to complete? 6. According to the graph above, the relationship between the carpenter s earnings and the amount of time he spent on jobs is: A a positive correlation B a negative correlation C no correlation D multiple correlations 2015 Page 14

17 Day 36 Practice 2 Name 7. As the age of a car increases, its value decreases. Which scatterplot best represents this relationship? 2015 Page 15

18 Day 36 Practice 2 Name 8. A trucking company keeps track of the number of miles each of its drivers logs each week. The scatterplot below shows the relationship between a driver s age and the number of miles the driver drove last week. 9. Describe the correlation between the number of miles a driver logs and the drivers age. The table below shows Cobi s hours of exercise and weight loss each week. Hours of exercise Weight loss (pounds) Page 16

19 Day 36 Practice 2 Name 10. Create a scatterplot from the data in the table. 10. What type of correlation did you find between hours of exercise and weight loss? 2015 Page 17

20 Day 36 Practice 2 Name Answer Key 1. What is the correlation of the scatter plot? The correlation of the scatter plot is positive. 2. Based on these results, if a team practices 4 hours per week next season, find an estimate of the number of debates the team can expect to win? If a team practices 4 hours per week, the number of debates the team can expect to win is What is the correlation between the gas that remained and the hours that had passed? The correlation between the gas that remained and the hours that had passed is negative. 4. Teresa records the ages and weights of 12 children in her neighborhood. If she records this data in a scatterplot, what type of relationship will she most likely see? The answer is: A Positive correlation 5. Based on the data, estimate the amount of money the carpenter would earn from a job that took 5 days to complete? The amount of money the carpenter would earn from a job that took 5 days to complete is $ According to the graph above, the relationship between the carpenter s earnings and the amount of time he spent on jobs is: The answer is: A positive correlation 7. As the age of a car increases, its value decreases. Which scatterplot best represents this relationship? The scatterplot C best represents the relationship. 8. A trucking company keeps track of the number of miles each of its drivers logs each week. The scatterplot below shows the relationship between a driver s age and the number of miles the driver drove last week. 9. Describe the correlation between the number of miles a driver logs and the drivers age. The correlation between the number of miles a driver logs and the drivers age is no or zero correlation. 10. Create a scatterplot from the data in the table 11. What type of correlation did you find between hours of exercise and weight loss? The correlation between hours of exercise and the weight loss is positive Page 18

21 Day 36 Exit Slip Name Day A line that lies as close as possible to a set of data points (x, y) is called the for the data points. 2. Describe how to tell whether a set of data points shows a positive correlation, a negative correlation, or approximately no correlation. Tell whether the data have a positive correlation, a negative correlation, or approximately no correlation Page 19

22 Day 36 Exit Slip Name Answer Key Day A line that lies as close as possible to a set of data points (x, y) is called the best-fitting line for the data points. 2. Describe how to tell whether a set of data points shows a positive correlation, a negative correlation, or approximately no correlation. Sample Answer: If the data points show a positive correlation, the points lie close to a line with positive slope. If the data points show a negative correlation, the points lie close to a line with negative slope. If the data points have approximately no correlation, the points do not lie close to any line. Tell whether the data have a positive correlation, a negative correlation, or approximately no correlation Neg Corr Pos. corr no correlation 2015 Page 20

23 Day 37 Bellringer Name Day 37 Does this scatter plot show a positive trend, a negative trend, or undetermined Page 21

24 Day 37 Bellringer Name Answer Key Day Undetermined 2. Negative Trend 3. Positive Trend 4. Undetermined 2015 Page 22

25 Day 37 Practice Name The data below shows the height and the weight of various people in a town. Use it to answer question 1-10 weight(lb) Height(in) Draw a scatter plot representing the data. 2. On the same axes, draw the line of the best fit 3. Determine the slope of the line (express your answer as a decimal in 4 significant figures) 4. Determine the equation of the line of the best fit in point-slope form. 5. Determine the equation of the line of the best fit in slope-intersection form. 6. Identify the y-intercept of the line 2015 Page 23

26 Day 37 Practice Name 7. According to the equation, what should be the weight of a person whose height is 58 inches. 8. Based on the formula, what should be the weight of a person with 62 inches. 9. Compare the answer in 8 above with that in the table. 10. Determine the height of a person whose weight is Determine the height of a person whose height is 170. Use the information below to answer questions Page 24

27 Day 37 Practice Name The table below shows the mean score of students in mathematics in 10 different examinations. Mean Exams Draw a scatter plot representing the data. 14. Draw the line of the best fit to represent the data 15. Determine the slope of the line of the best fit. 16. Determine the equation representing two variables. 17. Determine the mean score before the beginning of the recordings Page 25

28 Day 37 Practice Name 18. What could be the performance in the students in the 14 th exam. 19. If a mini exam was done in between the fourth and the third exams, what was its results? 20. What could be the performance in the students in the 10 th exam Page 26

29 Day 37 Practice Name Answer Keys Day 37: Page 27

30 Day 37 Practice Name 3. Slope 2.5 lb per in. 4. y 145 = 2.5(x 55) 5. y = 2.5x lb lb lb 9. From the table, the weight is 164 lb Comparing with one computed, the difference is 1.5 lb lb lb Page 28

31 Day 37 Practice Name Mean = exams Initial mean score is 56% % % % 2015 Page 29

32 Day 37 Exit Slip Name Day 37 Consider the set of data point given below. Table 1 x y Create the scatter plot of the data. 2. Write a function for the line of best fit Page 30

33 Day 37 Exit Slip Name Answer Key Day 37 y = 2x 6 (Answers will vary) 2015 Page 31

34 Day 38 Bellringer Name Day 38 Find the next term of a sequence 1. 16, 23, 30, 37, 44, , 13, 22, 31, 40, , 9, 12, 15, 18, , 8, 10, 12, 14, Page 32

35 Day 38 Bellringer Name Answer Key Day Page 33

36 Day 38 Practice Name 1. The following table has height in inches and weight Height Weight Label the x axis for height and Y axis (go by 5 s) for weight. Plot points Draw line of best fit Equation - 2. Tree Age and Height (in feet) x y Label the x axis for age and y axis for height. Plot points. Draw line of best fit. Equation 2015 Page 34

37 Day 38 Practice Name 3. Time and distance walked x y Label your graph and plot points Draw line of best fit. Equation 4 Miles Driven Gas in Tank Miles Gallons Plot points (x axis miles driven go by 10), y axis gallons (go by 3). Draw line of best fit. Equation 2015 Page 35

38 Day 38 Exit Slip Name Day The following table has height in inches and weight Height Weight Plot points Draw line of best fit Equation Page 36

39 Day 38 Exit Slip Name Answer Key Day 38 y = 1.3x (answers may vary) 2015 Page 37

40 Day 39 Bellringer Name Day 39 Graph the Statistics below. Percentage of women age who have had a live birth or who are pregnant with their first child, and percentage who have begun childbearing, by background characteristics, Philippines 2013 Percentage who age have had a live birth are pregnant with first child who have begun child bearing The percentage of women that are pregnant with their first child shows what trend, based on the graph? 2015 Page 38

41 Day 39 Bellringer Name Day The graph shows a negative trend for women pregnant with their first child Page 39

42 Day 39 Activity Name Line of Best Fit Classwork Linear Regression Line --- a best fitting line for a certain group of data that have been plotted. This allows you to make predictions about where other points would most likely fall. Example: Below is a table of asteroid names, their average distances from the sun (in millions of miles), and their orbital periods (the time it takes them, in years, to revolve around the sun). Question 1: About how long would it take an asteroid that is 230 million miles from the sun to make 1 revolution? Question 2: If an asteroid was discovered, and astronomers knew that its orbital period was almost exactly 4 years, about how far would you predict this asteroid to be from the sun? Asteroid Name Average Distance from the Orbital Period Sun Ceres Pallas Juno Vesta Astraea Hebe Iris Flora Metis Hygeia Make a scatterplot of the table above on your graphing calculator. 2. Graph the Linear Regression Equation in the form y = mx + b Answer to Question #1 above: It takes about years for an asteroid that is 230 million miles from the sun to make one revolution. Answer to Question #2 above: An asteroid that has an orbital period of 4 years could be predicted to be about miles from the sun Page 40

43 Day 39 Activity Name Instructions for Creating a Scatterplot and Linear Regression Line on the TI - 83 Calculator 1. Let¹s begin solving the asteroid problem given above by entering our data points into 2 lists in the calculator. The lists are found under the STAT key. 2. To enter or edit data points, which is what we want to do, you must use the EDIT menu. 3. So, hit STAT, then the EDIT menu, then edit again. Enter the values for the asteroids' distances into the first list, which the calculator creatively calls L1. Enter the asteroids' orbital periods into the second list, L2. 4. To plot these data points on a graph, we must create a stat plot; this key is located above the Y= key, just below the screen on the far left. Hit the STAT PLOT key. 5. Now, you must choose Plot 1 by turning it dark, or selecting it, by moving the cursor on top of it (use the arrow keys). Now, hit ENTER; now that you¹re inside the Plot 1 area, turn it on by selecting ON, then hit ENTER. 6. Select the first graph to draw, let the Xlist be L1 and let the Ylist be L2. The bottom line inside here lets you choose what kind of marks you want on your graph: dots, little plus signs, or little squares. Select whichever one you like best. We are now ready to graph! 7. In order to see your points on the graph, we must set the window up accordingly. Hit the WINDOW key. Our lowest X value (smallest distance) in L1 is 204.4, so let¹s let Xmin = 200. Our largest X value is 257.4, so let Xmax = 260. Since the difference between Xmax and Xmin is 60, let the Xscl = 10. That way, our x-axis will show 6 marks each 10 units apart. Similarly, let Ymin = 3, Ymax = 6, and Yscl = Now graph the scatterplot by hitting GRAPH. ***If you don¹t see your scatterplot, here are a couple of possible reasons why: a. If your calculator says, ERR: DIM Mismatch, check your 2 lists to see if you have the same number of elements in each list (you may not). Do this using STAT, EDIT, edit. b. If nothing appears on your graph, you may not have turned Plot 1 on. Do STAT PLOT, then turn Plot 1 on. Now, hit GRAPH again. c. Your Window is not set up as you thought it was. Hit WINDOW and check it Page 41

44 Day 39 Activity Name 9. It¹s time to get the linear regression line to go through the scatterplot. Hit STAT, go to the CALC menu, then choice #4, LinReg(ax + b). This will take you to the home screen, showing you LinReg (ax+b). Hit ENTER, and values for a and b will be given. You should get: a = b = You can write these values down and then go into the Y= menu, then manually type in y =.0196x.3963 OR, you can import these values, letting the calculator copy them in for you. To do this, hit the y= key. (Clear out any equations currently in here.) Put the cursor to the right of \Y1 =. Let¹s find the linear regression equation and put it here. Hit the VARS key located just below the down arrow key. Go to #5, statistics, and enter this. See the new menu at the top? The regression equation is under the EQ menu, so select EQ using the right arrow key. Now, choice #1 is RegEQ... select this one, then hit ENTER. Your regression equation should have been copied into the Y1 = section of the calculator, and it should be in the form y = ax + b. Now, hit GRAPH, and you should see the line of regression cut through the scatterplot. YOU DID IT!!! 10. You can now hit the TRACE key to answer Question 1 about how many years it takes an asteroid to make one revolution, given its distance. Simply hit TRACE, hold down the right arrow key until the x -value at the bottom of the screen is around 230, and record the corresponding y - value. To answer Question 2, get the y - value to be near 4, and record the corresponding x - value to predict the distance. *NOTE: When doing the next problem, you can use L1 and L2 again, or L3 and L4 if you want to keep the previous data in L1 and L2. If you use L3 and L4, you must remember to turn Plot 1 off (since it is using L1 and L2) and turn Plot 2 on, using L3 and L4 inside of Plot 2. Also, don¹t forget to change the window, or range, for the new problem, or you probably won¹t see your scatterplot when you hit GRAPH Page 42

45 Day 39 Activity Name Practice Activity #1 Student Number High School GPA Freshmen College GPA Let High School GPA be your x values (List 1) and College GPAs be your y values (List 2). 1. Make a scatterplot of the data. (You may need to clear your old statistics and your old graph: CLRSTAT and CLRDRAW) 2. Find the Regression Equation in the form y = mx + b 3. Graph the Regression Equation on your scatterplot to make sure it looks like the best - fitting line. 4. a.) If you earn a 3.80 GPA in high school, predict what you would get in college for your Freshman year. Freshman year GPA would be. b.) If a freshman in college got a 3.60 GPA, what would she have got for her high school GPA? High School GPA would have been Page 43

46 Day 39 Activity Name Practice Activity #2 Chirping Frequency and Temperature for the Striped Ground Cricket chirps / second temperature, F Chirping Frequency Temperature Let chirps / sec be your x values (List 1) and temp., F be your y values (List 2). 1. Make a scatterplot of the data. (You may need to clear your old statistics and your old graph: CLRSTAT and CLRDRAW) 2. Find the Regression Equation in the form y = mx + b 2015 Page 44

47 Day 39 Activity Name 3. Graph the Regression Equation on your scatterplot to make sure it looks like the best - fitting line. 4. a.) If you had a listening device and used it in the morning when you woke up and measured a striped ground cricket chirping at a rate of 18 chirps per second, how warm would you say the ground temperature is? The ground temperature would be. b.) If the ground temperature reached 95 F, at what rate would you expect those little guys to be chirping? They would be chirping at chirps / second Page 45

48 Day 39 Activity DESMOS Name Line of Best Fit Classwork Linear Regression Line --- a best fitting line for a certain group of data that have been plotted. This allows you to make predictions about where other points would most likely fall. Example: Below is a table of asteroid names, their average distances from the sun (in millions of miles), and their orbital periods (the time it takes them, in years, to revolve around the sun). Question 1: About how long would it take an asteroid that is 230 million miles from the sun to make 1 revolution? Question 2: If an asteroid was discovered, and astronomers knew that its orbital period was almost exactly 4 years, about how far would you predict this asteroid to be from the sun? Asteroid Name Average Distance from the Sun Orbital Period Ceres Pallas Juno Vesta Astraea Hebe Iris Flora Metis Hygeia Make a scatterplot of the table above on your graphing calculator. 2. Graph the Linear Regression Equation in the form y = mx + b Answer to Question #1 above: It takes about years for an asteroid that is 230 million miles from the sun to make one revolution. Answer to Question #2 above: An asteroid that has an orbital period of 4 years could be predicted to be about miles from the sun Page 46

49 Day 39 Activity DESMOS Name Instructions for Creating a Scatterplot and Linear Regression Line on Desmos.com Here is what you should copy and paste into Desmos: 257, , , , , , , , , , 5.59 When you enter the linear regression line, you need to type: y_1 ~ mx_1 + b (it says this in the directions, but it took me a bit to figure out that I needed to click the right arrow to get out of the subscript mode.) Here is a partial screenshot of what you will see on Desmos.com. :) You should get: m = and b = So, this means that your line of best fit is: y =.0196x Page 47

50 Day 39 Activity DESMOS Name To answer Question #1, simply click on the line and drag the point until the x-value is around 230 and record the corresponding y-value. To answer Question #2, follow the same instructions until the y-value is near 4 and record the corresponding x-value. Practice Activity #1 Student Number High School GPA Freshmen College GPA Let High School GPA be your x values (List 1) and College GPAs be your y values (List 2). 1. Make a scatterplot of the data. Here is your copy/paste: 2, , 2 2.6, , , , 2 2.9, , , , , Page 48

51 Day 39 Activity DESMOS Name 2. Find the Regression Equation in the form y = mx + b 3. Graph the Regression Equation on your scatterplot to make sure it looks like the best - fitting line. 4. a.) If you earn a 3.80 GPA in high school, predict what you would get in college for your Freshman year. Freshman year GPA would be. b.) If a freshman in college got a 3.60 GPA, what would she have got for her high school GPA? High School GPA would have been. Practice Activity #2 Chirping Frequency and Temperature for the Striped Ground Cricket chirps / second temperature, F Chirping Frequency Temperature Page 49

52 Day 39 Activity DESMOS Name Let chirps / sec be your x values (List 1) and temp., F be your y values (List 2). 1. Make a scatterplot of the data. Here is your copy/paste: 20, , , , , , , , , , , , , , , Find the Regression Equation in the form y = mx + b 3. Graph the Regression Equation on your scatterplot to make sure it looks like the best - fitting line. 4. a.) If you had a listening device and used it in the morning when you woke up and measured a striped ground cricket chirping at a rate of 18 chirps per second, how warm would you say the ground temperature is? The ground temperature would be. b.) If the ground temperature reached 95 F, at what rate would you expect those little guys to be chirping? They would be chirping at chirps / second Page 50

53 Day 39 Practice Name For each of the following, write the prediction equation and then solve the problem. 1. A student who waits on tables at a restaurant recorded the cost of meals and the tip left by single diners. Meal Cost $4.75 $6.84 $12.52 $20.42 $8.97 Tip $0.50 $0.90 $1.50 $3.00 $1.00 If the next diner orders a meal costing $10.50, how much tip should the waiter expect to receive? Equation Tip expected 2. The table below gives the number of hours spent studying for a science exam (x) and the final exam grade (y). X Y Predict the exam grade of a student who studied for 6 hours. Equation Grade expected 3. The table below shows the lengths and corresponding ideal weights of sand sharks. Length Weight Predict the weight of a sand shark whose length is 75 inches. Equation Weight expected 4. The table below gives the height and shoe sizes of six randomly selected men. Height Shoe size If a man has a shoe size of 10.5, what would be his predicted height? Equation Height expected 2015 Page 51

54 Day 39 Practice Name Answers 1. y = 0.16x 0.30, $ y = 6x + 64, 100 hours 3. y = 4.4x 156.1, 170 pounds 4. y = 0.4x 20, 71 inches 2015 Page 52

55 Day 39 Exit Slip Name Day 39 A student who waits on tables at a restaurant recorded the cost of meals and the tip left by single diners. Meal Cost $3.75 $7.89 $14.65 $23.42 $7.75 Tip $0.50 $0.90 $1.50 $3.00 $1.00 If the next diner orders a meal costing $10.50, how much tip should the waiter expect to receive? Equation Tip expected Does this seem reasonable? Please explain your answer Page 53

56 Day 39 Exit Slip Name Answer Key Day 39 y = 0.12x $1.26 Answers may vary 2015 Page 54

57 Complete Week 8 Algebra 1 Teachers Weekly Assessment Package Unit 3 Created by: Jeanette Stein 2015 Algebra 1 Teachers 55

58 Complete Week 8 Algebra 1 Common Core Semester 1 Skills Number Unit CCSS Skill 1 1 A.REI.3 Solve two step equations (including proportions) 2 1 Order of Operations 3 1 Create a table from a situation 4 1 A.REI.10 Create a graph from a situation 5 1 F.BF.1 Create an equation from a situation 6 1 F.IF.1 Identify a function 7 1 F.IF.2 Evaluate a function 8 1 A.REI.6 Basic Systems with a table and graph 9 1 F.LE.1 Identify linear, exponential, quadratic, and absolute value functions 10 2 F.BF.3 Translate a graph in function notation 11 2 F.IF.6 Calculate Slope 12 2 S.ID.7 Interpret meaning of the slope and intercepts 13 2 F.BF.2 Construct an arithmetic sequence 14 2 F.BF.4 Find the inverse of a function 56

59 Complete Week 8 Number Unit CCSS Skill 15 3 S.ID.6 Find the line of best fit 16 3 S.ID.6 Predict future events given data 17 3 S.ID.8 Calculate Correlation Coefficient with technology 18 3 S.ID.9 Understand the difference between Causation and Correlation 19 4 S.ID.1 Create box plots 20 4 S.ID.2 Calculate and compare measures of central tendencies 21 4 S.ID.3 Understand the effects of outliers 22 4 S.ID.5 Use two way frequency tables to make predictions 23 4 N.QA.1 Convert Units 24 4 N.QA.3 Understand Accuracy 25 5 A.REI.3 Solve advanced linear equations 26 5 A.REI.1 A.CED.4 Solve literal equations and justify the steps 27 5 A.REI.3 Solve inequalities 28 5 A.REI.12 Graph inequalities 29 6 A.REI.6 Solve a system of equations by graphing 30 6 A.REI.6 Solve a system of equations by substitution 31 6 A.REI.5 Solve a system of equations by elimination 57

60 Complete Week 8 Unit 3 Weekly Assessments 58

61 Complete Week 8 Week #8 1. The table gives the number of hours spent studying for a science exam and the final exam grade. Study hours Grade a. Draw a scatter plot of the data and draw in the line of best fit. b. What is the equation for the line of best fit? c. Predict the grade for a student who studied for 6 hours. 2. Solve two step equations 5 3x = Write a story problem for the following equation. 2x + 4 = Evaluate the function f(3) = 2x

62 Complete Week 8 Unit 3 - KEYS Weekly Assessments 60

63 Complete Week 8 Week #8 KEY 1. The table gives the number of hours spent studying for a science exam and the final exam grade. Study hours Grade a. Draw a scatter plot of the data and draw in the line of best fit. b. What is the equation for the line of best fit? Answers may vary: y = 5x + 60 c. Predict the grade for a student who studied for 6 hours. Answers may vary: Solve two step equations 5 3x = 11 x = Write a story problem for the following equation. 2x + 4 = 10 Answers may vary: You have $4 and your grandma gives you $2 per week. How long will it take you to have $10? 4. Evaluate the function f(3) = 2x 2 4 f(3) = 14 61