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Algebra II Chapter 2 Functions, Equations, and Graphs
© Tentinger
   Essential Understanding: Sometimes it is possible
    to model data from a real-world situation with a
    linear equation. You can then use the equation to
    draw conclusions about the situation.

   Objectives:
   Students will be able to
     write linear equations that model real world data
     make predictions from linear models of data
     define and identify various types of correlation
   Algebra
   A-CED.2. Create equations in two or more variables to represent
    relationships between quantities; graph equations on coordinate
    axes with labels and scales.
   Functions
   F-IF.4. For a function that models a relationship between two
    quantities, interpret key features of graphs and tables in terms of
    the quantities, and sketch graphs showing key features given a
    verbal description of the relationship★
   F-IF.6. Calculate and interpret the average rate of change of a
    function (presented symbolically or as a table) over a specified
    interval. Estimate the rate of change from a graph.★
   F-BF.1. Write a function that describes a relationship between two
    quantities.★
   What is a scatter plot?
   A graph that relates two sets of data by
    plotting the data as ordered pairs.
   Can be used to determine strength of a
    relationship. The closer the points fall
    together the stronger the
    correlation(Correlation does not mean
    causation)
   5 basic types of correlation
   The following table shows the number of
     hours students spent online the day before a
     test and the scores on the test. Make a
     Scatter Plot and describe the correlation.
    What would you predict the test score to be
     of someone who was online for 2.5 hours?
                         Computer Use and Test Scores
 # of    0     0    1       1     1.5   1.75   2        2    3    4    4.5   5
Hours
Online
Test     100   94   98     88     92    89     75       70   78   72   57    60
Scores
   Trend Line: a line that approximates the
    relationship between the variables, or data
    sets, of a scatter plot.
   You can use a trend line to make predictions
    from the data
   You can pick to two points in the scatter plot
    to represent the equation of a trend line
   The table shows median home prices in
           California. What is the equation for a trend
           line that models the relationship between
           time and home prices?

                         California Median Home Prices
Year          1940    1950      1960      1970      1980     1990      2000

Median       36,700   57,900   74,400    88,700   167,300   249,800   211,500
Price ($)
   Line of Best Fit: trend line that gives the
    most accurate model of related data
   This is the linear regression (LinReg) function
    on your calculator

   Correlation Coefficient: r, indicates the
    strength of the correlation. The closer the
    data is to 1 or -1, the more closely the data
    resembles a line and the more accurate your
    model is.
   The table lists the cost of 2% milk. Use a
      scatter plot to find the equation of the line of
      best fit. Based on your linear model, how
      much would you expect to pay for a gallon of
      2% milk in 2025?
                     Cost of 2% Milk
       Year          1998 2000 2002 2004 2006 2008
Avg Cost for 1 gal   2.57   2.83   2.93   2.93   3.10   3.71
      ($)
   Pg. 96-97
   #1-4, 8-12 even, 13, 14, 18
   (10 problems)

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Alg II 2-5 Linear Models

  • 1. Algebra II Chapter 2 Functions, Equations, and Graphs © Tentinger
  • 2. Essential Understanding: Sometimes it is possible to model data from a real-world situation with a linear equation. You can then use the equation to draw conclusions about the situation.  Objectives:  Students will be able to  write linear equations that model real world data  make predictions from linear models of data  define and identify various types of correlation
  • 3. Algebra  A-CED.2. Create equations in two or more variables to represent relationships between quantities; graph equations on coordinate axes with labels and scales.  Functions  F-IF.4. For a function that models a relationship between two quantities, interpret key features of graphs and tables in terms of the quantities, and sketch graphs showing key features given a verbal description of the relationship★  F-IF.6. Calculate and interpret the average rate of change of a function (presented symbolically or as a table) over a specified interval. Estimate the rate of change from a graph.★  F-BF.1. Write a function that describes a relationship between two quantities.★
  • 4. What is a scatter plot?  A graph that relates two sets of data by plotting the data as ordered pairs.  Can be used to determine strength of a relationship. The closer the points fall together the stronger the correlation(Correlation does not mean causation)
  • 5. 5 basic types of correlation
  • 6. The following table shows the number of hours students spent online the day before a test and the scores on the test. Make a Scatter Plot and describe the correlation.  What would you predict the test score to be of someone who was online for 2.5 hours? Computer Use and Test Scores # of 0 0 1 1 1.5 1.75 2 2 3 4 4.5 5 Hours Online Test 100 94 98 88 92 89 75 70 78 72 57 60 Scores
  • 7. Trend Line: a line that approximates the relationship between the variables, or data sets, of a scatter plot.  You can use a trend line to make predictions from the data  You can pick to two points in the scatter plot to represent the equation of a trend line
  • 8. The table shows median home prices in California. What is the equation for a trend line that models the relationship between time and home prices? California Median Home Prices Year 1940 1950 1960 1970 1980 1990 2000 Median 36,700 57,900 74,400 88,700 167,300 249,800 211,500 Price ($)
  • 9. Line of Best Fit: trend line that gives the most accurate model of related data  This is the linear regression (LinReg) function on your calculator  Correlation Coefficient: r, indicates the strength of the correlation. The closer the data is to 1 or -1, the more closely the data resembles a line and the more accurate your model is.
  • 10. The table lists the cost of 2% milk. Use a scatter plot to find the equation of the line of best fit. Based on your linear model, how much would you expect to pay for a gallon of 2% milk in 2025? Cost of 2% Milk Year 1998 2000 2002 2004 2006 2008 Avg Cost for 1 gal 2.57 2.83 2.93 2.93 3.10 3.71 ($)
  • 11. Pg. 96-97  #1-4, 8-12 even, 13, 14, 18  (10 problems)