Strong Positive Strong Positive Weak Positive Strong Negative Calculator Models “Pre-covery Packet” Stat, Edit, Stat, Calc, 4:LinReg, L1, L2 Write the appropriate linear equation to model the data, find the correlation coefficient, and determine strength. Round to nearest hundredth. 1. a) Year 1990 1991 1992 1993 1994 1995 1996 1997 $ 1910 1800 1881 2083 2266 2305 2389 2461 Strong Positive Strong Positive b) c) Wt. 17.5 20.0 22.5 25.0 27.5 35.0 Mpg 65.4 49.0 59.2 41.1 38.9 40.7 46.9 27.7 cm3 0.3 0.9 1.1 2.0 3.4 4.8 8.1 10.5 100 km2 233 7985 10161 17042 7900 3978 28389 7646 Weak Positive Strong Negative

In 2003 In 2027 In 2020 In 2033 Calculator Models “Pre-covery Packet” Use the given regression equation to predict the requested value. Round to nearest whole number. 3. Based on the given equation, in what year would the median salary for men be expected to equal $27,560. a) Based on the given equation, in what year would the median salary for women be expected to equal $27,560. In 2003 In 2027 b) Based on the given equation, in what year would the median salary for men be expected to equal $37,800. c) Based on the given equation, in what year would the median salary for women be expected to equal $30,500. In 2020 In 2033

Calculator Models “Pre-covery Packet” Stat, Edit, Stat, Calc Plot the data to determine if the data represents a quadratic, cubic, or quartic regression. Then, find the appropriate regression equation to model the data, and the corresponding coefficient of determination. Remember, you have to have diagnostics on in order to find this. 4. a) Quadratic Regression: Quartic Regression: b) c) Cubic Regression: Quartic Regression:

Calculator Models “Pre-covery Packet” Stat, Edit, Stat, Calc Use the given exponential regression equations to predict the requested value. Round final answer to nearest whole number. 5. a) Find the expected population in 2070. 31.5 (100,000,000) 3,150,000,000 48.69459027 (100,000,000) 4,869,459,027 Notice we plug in numbers based on the form we originally used them in the table. However, we must convert our final answer to what it truly represents. b) Find the expected population in 2030. c) Find the expected population in 2010. 20.39129858 (100,000,000) 2,039,129,858 13.19553394 (100,000,000) 1,319,553,394

Calculator Models “Pre-covery Packet” Round to the nearest dollar. Using the number of years after Jan. 1, 1955 as the independent variable, the equation that represents this data is: 7. How much would have been in the account on Jan. 1, 1965? a) How much would have been in the account on Jan. 1, 1975? b) c) How much would have been in the account on Jan. 1, 1985? How much would have been in the account on Jan. 1, 1995?

Calculator Models “Pre-covery Packet” Round to the nearest dollar. Using the number of years after Jan. 1, 1955 as the independent variable, the equation that represents this data is: 8. What year will the balance reach $75,000? a) What year will the balance reach $100,000? Put the equation in Y1 TABLE (2nd graph) Scroll to find the “y” value closest to, but not greater than 75000. (=68) Convert this number to the year by adding to 1955. Year is 1955+68 = 2023 1955 + 73 =2028 b) c) What year will the balance reach $30,000? What year will the balance reach $50,000? 1955 + 50 = 2005 1955 + 60 = 2015

Calculator Models “Pre-covery Packet” Stat, Edit, Stat, Calc Find the appropriate exponential regression equation to represent this data. Then, determine whether the data represents an “exponential growth” or “exponential decay” relationship, and explain why. Round equations to nearest thousandth as shown. 9. a) Let x represent time (s). 37.43 Exponential growth – as hours increase, bacteria increase. Exponential decay – as time increases, velocity decreases. b) c) Exponential decay – as time increases, Pb-211 decreases. Exponential growth – as hours increase, bacteria increase.