(a) Using a function of the form y = a*b^x, with x = 0 in 1900 and y equal to the national debt in billions, model the data. (Round your coefficients to four decimal places.) y = (b) Use the model to predict the debt in 2017. (Round your answer to the nearest billion.) $ billion (c) Predict the year in which the debt will be $99 trillion ($99,000 billion). Need Help? Read It
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- Tax Table Here are selected entries from the 2014 tax table that show the federal income tax owed by those married and filing jointly. The taxable income and the tax are both in dollars. Taxable income Tax 72, 000 9896 72, 200 9926 72, 400 9956 72, 600 9986 72, 800 10, 016 73, 000 10, 046 73, 200 10, 076 73, 400 10, 106 73, 600 10, 136 73, 800 10, 169 74, 000 10, 219 74, 200 10, 269 Over what two parts of this table is the tax a linear function of the taxable income? Find formulas for both linear functions, and explain in practical terms what the slopes mean.The following list gives the gross federal debt(in millions of dollars) for the U.S. every 5 years from 1945 to 2000: Year Gross Federal Debt ($millions) 1945 260,123 1950 256,853 1955 274,366 1960 290,525 1965 322,318 1970 380,921 1975 541,925 1980 909,050 1985 1,817,521 1990 3,206,564 1995 4,921,005 2000 5,686,338 Construct a scatter plot with this data. Do you observe a trend? If so, what type of trend do you observe? Use Excel to fit a linear trend and an exponential trend to the data. Display the models and their respective r^2. Interpret both models. Which model seems to be more approprate and why?The table below represents the monthly unemployment rates in the US from January of 2005 through May of 2016. Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2005 5.3% 5.4% 5.2% 5.2% 5.1% 5.0% 5.0% 4.9% 5.0% 5.0% 5.0% 4.9% 2006 4.7% 4.8% 4.7% 4.7% 4.6% 4.6% 4.7% 4.7% 4.5% 4.4% 4.5% 4.4% 2007 4.6% 4.5% 4.4% 4.5% 4.4% 4.6% 4.7% 4.6% 4.7% 4.7% 4.7% 5.0% 2008 5.0% 4.9% 5.1% 5.0% 5.4% 5.6% 5.8% 6.1% 6.1% 6.5% 6.8% 7.3% 2009 7.8% 8.3% 8.7% 9.0% 9.4% 9.5% 9.5% 9.6% 9.8% 10.0% 9.9% 9.9% 2010 9.7% 9.8% 9.9% 9.9% 9.6% 9.4% 9.5% 9.5% 9.5% 9.5% 9.8% 9.4% 2011 9.1% 9.0% 9.0% 9.1% 9.0% 9.1% 9.0% 9.0% 9.0% 8.8% 8.6% 8.5% 2012 8.2% 8.3% 8.2% 8.2% 8.2% 8.2% 8.2% 8.1% 7.8% 7.8% 7.8% 7.9% 2013 7.9% 7.7% 7.5% 7.5% 7.5% 7.5% 7.3% 7.2%…
- Suppose the table below gives the average tuition and fees at 2-year and 4-year state schools in a particular state. Values are adjusted to 2019 dollars. Academic Year 4-year state school 2-year state school 2005-06 $5,904 $2,661 2006-07 $6,066 $2,539 2007-08 $6,289 $2,604 2008-09 $7,222 $2,901 2009-10 $7,738 $3,065 2010-11 $8,035 $3,117 2011-12 $8,154 $3,108 2012-13 $8,497 $3,075 2013-14 $8,578 $3,025 2014-15 $9,390 $3,326 2015-16 $10,004 $3,504 2016-17 $10,474 $3,663 2017-18 $10,789 $3,830 2018-19 $10,874 $3,859 2019-20 $10,900 $3,907 Here is a graph of the information from the table. a. What is the absolute change in tuition and fees at this state's four-year institutions from 2005-06 to 2019-20? b. What is the relative change in tuition and fees at this state's four-year institutions from 2005-06 to 2019-20? Round to the nearest whole percentage…Coca-Cola Revenues ($ millions), 2005–2010 Quarter 2005 2006 2007 2008 2009 2010 Qtr1 5,206 5,226 6,103 7,379 7,169 7,525 Qtr2 6,310 6,476 7,733 9,046 8,267 8,674 Qtr3 6,037 6,454 7,690 8,393 8,044 8,426 Qtr4 5,551 5,932 7,331 7,126 7,510 10,494 Click here for the Excel Data File (a-1) Use MegaStat or Minitab to deseasonalize Coca-Cola’s quarterly data. (Round your answers to 3 decimal places.) 1 2 3 4 2005 Not attempted Not attempted 2006 Not attempted Not attempted Not attempted Not attempted 2007 Not attempted Not attempted Not attempted Not attempted 2008 Not attempted Not attempted Not attempted Not attempted 2009 Not attempted Not attempted Not attempted Not attempted 2010 Not attempted Not attempted mean Not attempted Not attempted Not attempted Not attempted (a-2) State the adjusted four quarterly indexes. (Round your answers to 3 decimal places.) Q1 Q2 Q3 Q4 0.923 0.923 Correct 1.087 1.087 Correct 1.048 1.048…Coca-Cola Revenues ($ millions), 2005–2010 Quarter 2005 2006 2007 2008 2009 2010 Qtr1 5,206 5,226 6,103 7,379 7,169 7,525 Qtr2 6,310 6,476 7,733 9,046 8,267 8,674 Qtr3 6,037 6,454 7,690 8,393 8,044 8,426 Qtr4 5,551 5,932 7,331 7,126 7,510 10,494 Click here for the Excel Data File (a-1) Use MegaStat or Minitab to deseasonalize Coca-Cola’s quarterly data. (Round your answers to 3 decimal places.) 1 2 3 4 2005 2006 2007 2008 2009 2010 mean (a-2) State the adjusted four quarterly indexes. (Round your answers to 3 decimal places.) Q1 Q2 Q3 Q4 (a-3) What is the trend model for the deseasonalized time series? (Round your answers to 2 decimal places.) yt = xt + (b) State the model found when performing a regression using seasonal binaries. (A negative value should be indicated by a minus sign. Round your answers to 4 decimal places.) yt = + t + Q1 + Q2 + Q3…
- Coca-Cola Revenues ($ millions), 2005–2010 Quarter 2005 2006 2007 2008 2009 2010 Qtr1 5,200 5,103 6,055 7,340 7,110 7,600 Qtr2 6,296 6,445 7,685 9,025 8,204 8,651 Qtr3 6,023 6,394 7,642 8,293 8,005 8,403 Qtr4 5,537 5,885 7,283 7,005 7,456 10,471 1. Use MegaStat or Minitab to deseasonalize Coca-Cola’s quarterly data. 1 2 3 4 2005 2006 2007 2008 2009 2010 mean 2. State the adjusted four quarterly indexes. Q1. Q2. Q3. Q4 3. What is the trend model for the deseasonalized time series? yt= xt+ State the model found when performing a regression using seasonal binaries. yt= + t+ Q1+ Q2+ Q3 4. Use the regression equation to make a prediction for each quarter in 2011. Quarter Predicted Q1 Q2 Q3 Q4Monthly Sales 6267.19 7058.06 7119.5 7147.18 7198.52 7298.09 7325.7 7335.68 7355.97 7481.05 7490.23 7530.08 7616.09 7682.69 7684.14 7704.12 7704.98 7779.28 7798.23 7815.15 7844.16 7890.21 7977.6 7993.16 8021.03 8028.37 8068.86 8082.42 8096.17 8119.25 8129.21 8190.68 8255.28 8282.44 8376.31 8392.4 8400.95 8451.16 8456.66 8505.35 8539.25 8543.65 8573.05 8641.78 8667.48 8751.08 8777.97 8800.08 8888.65 8907.03 9096.87 9241.74 9411.68 9450.73 9484.62 9514.57 9521.4 9524.91 9733.44 10123.24 If you view the company’s performance record as a representative sample of its overall sales performance, and considering what you know about normal distribution, what is the dollar value for the lowest 25th percentile?Monthly Sales 6267.19 7058.06 7119.5 7147.18 7198.52 7298.09 7325.7 7335.68 7355.97 7481.05 7490.23 7530.08 7616.09 7682.69 7684.14 7704.12 7704.98 7779.28 7798.23 7815.15 7844.16 7890.21 7977.6 7993.16 8021.03 8028.37 8068.86 8082.42 8096.17 8119.25 8129.21 8190.68 8255.28 8282.44 8376.31 8392.4 8400.95 8451.16 8456.66 8505.35 8539.25 8543.65 8573.05 8641.78 8667.48 8751.08 8777.97 8800.08 8888.65 8907.03 9096.87 9241.74 9411.68 9450.73 9484.62 9514.57 9521.4 9524.91 9733.44 10123.24 Given the company’s performance record and based on the empirical rule of normal distribution (also known as the 68%-95%-99.7% rule), what would be the lower bound of the range of sales values that contains 68% of the monthly sales? What would be the upper bound of the range of sales values that contains 68% of the monthly sales?
- At a high school reunion, a the 20 students in graduating from the class of 2001 got into a chat about their annual incomes. Here is the list that they formed. 61532 70568 84127 66569 38013 67252 71947 83710 247894 66328 77208 1386592 74472 136568 73424 62791 76862 66412 42777 66445 What will be the right parameter to describe the achievement of this particular class, with regards to the money they all make?Year Population 1790 3,929,214 1800 5,308,483 1810 7,239,881 1820 9,638,453 1830 12,866,020 1840 17,069,453 1850 23,191,876 1860 31,443,321 1870 39,818,449 1880 50,155,783 1890 62,947,714 1900 75,994,575 1910 91,972,266 1920 105,710,620 1930 122,775,046 1940 131,669,275 1950 150,697,361 1960 179,323,175 1970 203,302,031 1980 226,545,805 1990 248,709,873 2000 281,421,906 2010 308,745,538 What is the equation of the Least Squares Regression Line for the census data? (need to include correct values for a and b) Using the line, you calculated in number 5, what would you predict the population to have been in 1985? EXPLAIN. Should you use the previously calculated Regression Line to predict population in the year 2200? EXPLAIN.Year Population 1790 3,929,214 1800 5,308,483 1810 7,239,881 1820 9,638,453 1830 12,866,020 1840 17,069,453 1850 23,191,876 1860 31,443,321 1870 39,818,449 1880 50,155,783 1890 62,947,714 1900 75,994,575 1910 91,972,266 1920 105,710,620 1930 122,775,046 1940 131,669,275 1950 150,697,361 1960 179,323,175 1970 203,302,031 1980 226,545,805 1990 248,709,873 2000 281,421,906 2010 308,745,538 Use excel to calculate the Least Squares Regression Line for the census data? (need to include correct values for a and b) Using the line, you calculated in number 5, what would you predict the population to have been in 1985? EXPLAIN. Should you use the previously calculated Regression Line to predict population in the year 2200? EXPLAIN.