Use Excel to develop a regression model for the Consumer Food Database (using the “Excel Databases.xls” file on Blackboard) to predict Annual Food Spending by Annual Household Income for those living in the Metro area only.     Suppose a household in the metro area has an annual income of $60,000.  Predict how much they spend on food per year.  Write your answer as a number (do not include the $ sign or comma) and round to 2 decimal places Annual Food Spending ($) Annual Household Income           ($) Non mortgage household debt ($) Region:   1 = NE     2 = MW    3 = S       4 = W Location:   1 = Metro      2 = Outside Metro 8909 56697 23180 1 1 5684 35945 7052 1 1 10706 52687 16149 1 1 14112 74041 21839 1 1 13855 63182 18866 1 1 15619 79064 21899 1 1 2694 25981 8774 1 1 9127 57424 15766 1 1 13514 72045 27685 1 1 6314 38046 8545 1 1 7622 52408 28057 1 1 4322 41405 6998 1 1 3805 29684 4806 1 1 6674 49246 13592 1 1 7347 41491 4088 1 1 2911 26703 15876 1 1 8026 48753 16714 1 1 8567 55555 16783 1 1 10345 71483 21407 1 1 8694 50980 19114 1 1 8821 46403 7817 1 1 8678 51927 14415 1 1 14331 84769 17295 1 1 9619 59062 16687 1 1 9286 57952 14161 1 1 8206 58355 19538 1 1 16408 81694 15187 1 1 12757 69522 14651 1 1 17740 96132 0 1 1 7739 57796 22057 1 1 15383 88276 1896 1 1 4579 32264 7979 1 1 11679 65928 0 1 1 12877 69924 27330 1 1 16232 91108 9876 1 1 9621 54070 19908 1 1 8171 47238 17819 1 1 12128 77427 31340 1 1 8642 59805 4963 1 1 12400 60334 6632 1 1 9185 54114 18593 1 2 7862 40680 15202 1 2 9775 58263 1486 1 2 6771 52008 21713 1 2 3059 39643 12179 1 2 13211 70309 13221 1 2 7408 46450 5602 1 2 11581 76140 33874 1 2 14233 80833 11478 1 2 3352 31899 2762 1 2 2630 21647 2663 1 2 9093 65924 11355 1 2 12652 65923 5132 1 2 9559 62811 12613 1 2 6112 42335 3149 1 2 10431 65134 15196 1 2 12630 64621 21433 1 2 4578 36553 5502 1 2 9551 62910 11376 1 2 10262 70727 13287 1 2 9551 57634 11857 2 1 10143 56549 16136 2 1 8955 59662 11627 2 1 10197 57350 18432 2 1 11234 56447 10871 2 1 9320 61136 0 2 1 9089 51526 4902 2 1 12300 79979 17270 2 1 11484 66733 15145 2 1 11215 75359 15611 2 1 7204 40795 8975 2 1 5579 39128 6576 2 1 11723 75482 12508 2 1 9353 63998 0 2 1 7761 45845 6671 2 1 4261 38223 8576 2 1 9830 66787 1178 2 1 12386 77852 936 2 1 8673 55825 14167 2 1 10944 57022 9018 2 1 9910 64263 12768 2 1 9928 75881 17423 2 1 4264 34343 21323 2 1 7971 41243 21009 2 1 8290 53021 20151 2 1 12669 66991 9250 2 1 7272 49719 20838 2 1 9784 58399 16065 2 1 9187 50477 9407 2 1 5866 39112 20409 2 1 9456 51886 11668 2 2 6270 34797 146 2 2 9518 62348 5201 2 2 10968 78704 17002 2 2 8865 53620 32004 2 2 9226 51577 15922 2 2 4913 34761 17704 2 2 6976 60968 17799 2 2 8152 51281 8167 2 2 2887 25013 18763 2 2 8062 59238 10815 2 2 8895 47344 11814 2 2 8444 52645 22469 2 2 6148 35309 17139 2 2 4563 34355 10612 2 2 8185 50630 21187 3 1 3391 29056 15735 3 1 7436 48721 18363 3 1 9522 50459 16478 3 1 11290 72805 21238 3 1 10403 56954 22218 3 1 4693 39343 24696 3 1 5626 38833 14371 3 1 11869 55021 35576 3 1 13055 77605 817 3 1 8783 57937 18591 3 1 13031 63343 25531 3 1 3681 36479 17950 3 1 5549 40381 14257 3 1 4108 26309 26581 3 1 6314 41421 22470 3 1 7700 54579 29065 3 1 7479 40551 31757 3 1 9093 50369 6404 3 1 9863 54422 24334 3 1 8043 51836 26213 3 2 9552 73600 36374 3 2 9286 51873 29631 3 2 7987 48003 17261 3 2 3875 36519 13579 3 2 10746 75152 10659 3 2 6888 44974 23711 3 2 5479 48923 4594 3 2 6949 43769 21221 3 2 10650 75947 33357 3 2 5188 41423 33641 3 2 5311 40189 17791 3 2 4691 36772 5829 3 2 8056 59690 19594 3 2 11304 53654 23066 3 2 8112 59067 240 3 2 8696 65962 0 3 2 5869 37254 10157 3 2 3776 33568 14143 3 2 11829 56934 0 3 2 13087 88822 17565 4 1 10986 59635 27863 4 1 5762 38407 18867 4 1 11617 78627 11894 4 1 9895 47710 22930 4 1 16293 64443 31687 4 1 8185 58871 35424 4 1 13972 87954 11549 4 1 11243 54778 12552 4 1 4635 39825 19494 4 1 10063 49536 12195 4 1 8426 60102 13787 4 1 7436 49139 22356 4 1 11747 51052 4553 4 1 15397 70500 12025 4 1 6842 54894 16217 4 1 9678 60570 4106 4 1 12852 57625 31228 4 1 10114 56956 25907 4 1 8496 61400 1093 4 1 6689 50532 17106 4 1 15696 72774 17793 4 1 9841 69981 21607 4 1 12529 66891 17689 4 1 10210 67431 19995 4 1 8868 64782 14489 4 1 6426 38987 17864 4 1 11096 64867 5839 4 1 10086 50421 8689 4 1 2587 27076 17534 4 1 12492 51784 20284 4 2 8456 54135 22037 4 2 6801 53291 23342 4 2 6339 49804 34943 4 2 7802 52205 28579 4 2 9717 72841 22349 4 2 6026 46238 20165 4 2 5618 45938 10538 4 2 10217 77716 18516 4 2 8338 59711 7980 4 2 9048 42106 19786 4 2 4017 36462 9935 4 2 10906 53403 18177 4 2 15148 71290 6696 4 2 8830 66759 20972 4 2 8481 57616 28767 4 2 11358 76221 1373 4 2 10553 78202 5920 4 2 6969 55164 24795 4 2 13219 61171 21482 4 2 3543 34093 25969 4 2 7326 50647 10750 4 2 8458 59898 22940 4 2 11766 52884 25970 4 2 9908 73629 7112 4 2

Using the previous regression model, what is the p-value associated with the hypothesis test of significance between GPA and Salary Expectation?  Round your answer to 3 decimal places.

Estimates for Medicare are given below:             Year   Cost (billion dollars)           1995    157           1996     178           1997     194           1998    211          1999     229          2000    247 Write the linear equation using the years 1997 and 2000. Write the linear regression equation Using the regression equation, predict the Medicare cost this year. Using the regression equation, interpret the slope in terms of this problem.

A car initially sold for $23,999. Its class life is 12 years, and the car depreciates by $750 each year. Express this as a linear function. Find the salvage value. Then, find the value after six years.

In 2000, 12.8% of vehicles sold were off-road vehicles. In 2010, that number decreased to 10.2%. Calculate and interpret the relative change in the number of off-road vehicles sold from 2000 to 2010.

The number of Master’s degrees granted at a particular university is given for selected years in the table below.   Year 2005 2010 2015 2020 Number of Master’s Degrees 58 69 76 83   Use the linear regression equation for this data to predict the number of Master’s degrees that this university will grant in the year 2021.    Blank 1. Calculate the answer by read surrounding text.  Round to the nearest whole number of Master's degrees.

Mary used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). Her estimated regression equation was Crime = 428 + 0.050 Income. If Income decreases by 500, we would expect that Crime will Group of answer choices remain unchanged. decrease by 25. increase by 500. decrease by 50.

The table shows the lengths and weights of seven muskies captured by the Department of Natural Resources in Catfish Lake in Eagle River, Wisconsin. Use the linear regression feature on a graphing calculator to determine an equation of the line that best fits the data. Round to the hundredths. Musky 1 2 3 4 5 6 7 Length (in.) 26 27 29 33 35 36 38 Weight (lb) 5 8 9 12 14 14 19

With the rise of e-books and online retailers, the demand for physical bookstores has been declining. The number of bookstores from 2008 through 2013 (in hundreds) are shown in the following table (x = 0 corresponds to 2008): Year 0 1 2 3 4 5 Number of Bookstores 4.2 3.8 3.4 3.0 2.6 2.2 Using the equation, estimate the number of bookstores in 2016. Group of answer choices 200 300 100 400

The following table shows retail sales in drug stores in billions of dollars in the U.S. for years since 1995. 220- 210 200 190 180 170 160 150 Year 0 130- 120- 110- 100- 90 801 6 12 15 Let S(t) be the retails sales in billions of dollars in t years since 1995. A linear model for the data is F(t) = 9.44t + 84.182. Retail Sales 85.851 108.426 141.781 169.256 202.297 222.266 3 6 9 12 15 Use the above scatter plot to decide whether the linear model fits the data well. The function is a good model for the data. The function is not a good model for the data Estimate the retails sales in the U. S. in 2015. billions of dollars.