Create a scatterplot in Excel of age and years worked. Comment on what this scatterplot tells you about the data.
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Create a scatterplot in Excel of age and years worked.
Comment on what this scatterplot tells you about the data.
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Solved in 3 steps with 1 images
- year per capita income (US$) 1970 3399.299 1971 3768.298 1972 4251.175 1973 4804.463 1974 5576.515 1975 5998.144 1976 7062.131 1977 7100.126 1978 7247.967 1979 7602.913 1980 8355.968 1981 9434.391 1982 9619.438 1983 10416.54 1984 10790.33 1985 11018.96 1986 11482.89 1987 12974.81 1988 15080.28 1989 16426.73 1990 16838.67 1991 17266.1 1992 16412.08 1993 15875.59 1994 15755.82 1995 16369.32 1996 16699.83 1997 17310.76 1998 16622.67 1999 17581.02 2000 18987.38 2001 18601.4 2002 19232.18 2003 22739.43 2004 25719.15 2005 29198.06 2006 32738.26 2007 36144.48 2008 37446.49 2009 32755.18 2010 38420.52 2011 42334.71 2012 42665.26 2013 42676.47 2014 41039.89 2015 35175.19 2016 34229.19ID Student Number Surname Name Test 1 Test 2 Test 3 Test 4 Final mark PASS/FAIL 1 217545455 Johaness Wheeler 45% 34% 49% 21% 37 FAIL 2 217452154 David Albertina 45% 34% 49% 4% 33 FAIL 3 217454151 Waldo Gertze 75% 75% 63% 88% 75 PASS 4 217486414 Kalimbo Andreas 51% 56% 90% 90% 72 PASS 5 217454155 Hakweenda Junior 44% 28% 35% 14% 30 FAIL Answer the following questions using the table above Use student 2017 table to create a query that will display Student Number, Surname, Name and Pass/Fail field for all the students whose final result is "PASS". Save the query as "Pass". Use student 2017 to create a query that will display the student's surname and final mark field for all the students whose final mark is between 0 - 40. Save the query as "Fail" Use student 2017 to create a query that will display the student number and surname for all the students whose surname consist of letter "O" in it. Save the query as "Surname"."id" "surgery" "sex" "age" "weight" "length" "BMIpre" "BMIpost" "complic" "comorb" "depressi" "diabetes" "SES"1 0 "Female" 26 100 1,57 40,56959714 31,03574182 0 0 0 0 22 0 "Female" 26 71 1,48 32,41417093 29,67494522 0 0 0 0 23 0 "Female" 53 97 1,6 37,890625 NA 0 0 0 0 24 0 "Female" 18 109 1,68 38,61961451 31,17913832 0 1 0 1 35 0 "Female" 37 100 1,63 37,63784862 27,47562949 0 0 0 0 16 0 "Female" 43 94 1,56 38,62590401 34,92767916 0 0 0 0 27 0 "Female" 36 105 1,64 39,03926234 24,5389649 1 1 0 0 38 0 "Female" 43 107 1,57 43,40946894 27,99302203 1 0 0 0 29 0 "Female" 41 103 1,6 40,234375 37,5 1 0 0 0 210 0 "Female" 24 93…
- "id" "surgery" "sex" "age" "weight" "length" "BMIpre" "BMIpost" "complic" "comorb" "depressi" "diabetes" "SES"1 0 "Female" 26 100 1,57 40,56959714 31,03574182 0 0 0 0 22 0 "Female" 26 71 1,48 32,41417093 29,67494522 0 0 0 0 23 0 "Female" 53 97 1,6 37,890625 NA 0 0 0 0 24 0 "Female" 18 109 1,68 38,61961451 31,17913832 0 1 0 1 35 0 "Female" 37 100 1,63 37,63784862 27,47562949 0 0 0 0 16 0 "Female" 43 94 1,56 38,62590401 34,92767916 0 0 0 0 27 0 "Female" 36 105 1,64 39,03926234 24,5389649 1 1 0 0 38 0 "Female" 43 107 1,57 43,40946894 27,99302203 1 0 0 0 29 0 "Female" 41 103 1,6 40,234375 37,5 1 0 0 0 210 0 "Female" 24 93…"id" "surgery" "sex" "age" "weight" "length" "BMIpre" "BMIpost" "complic" "comorb" "depressi" "diabetes" "SES"1 0 "Female" 26 100 1,57 40,56959714 31,03574182 0 0 0 0 22 0 "Female" 26 71 1,48 32,41417093 29,67494522 0 0 0 0 23 0 "Female" 53 97 1,6 37,890625 NA 0 0 0 0 24 0 "Female" 18 109 1,68 38,61961451 31,17913832 0 1 0 1 35 0 "Female" 37 100 1,63 37,63784862 27,47562949 0 0 0 0 16 0 "Female" 43 94 1,56 38,62590401 34,92767916 0 0 0 0 27 0 "Female" 36 105 1,64 39,03926234 24,5389649 1 1 0 0 38 0 "Female" 43 107 1,57 43,40946894 27,99302203 1 0 0 0 29 0 "Female" 41 103 1,6 40,234375 37,5 1 0 0 0 210 0 "Female" 24 93…Complete the following table using Excel: Perform the following: In Excel: Result: EX. 8.9456 ÷ 4.65 =8.9456/4.65 1.92375484 a. 108 × 72 – 66.7 b. 3.412 c. √3.76*4.5677 + 12.013 d. 42 × 43 × 42 e. 9.099 ÷ 15087 f. 215.06 × (12.7 – 14.33) g. 14.6712 h. 19.6 ÷ 900087521
- State # letters in name Year entered the Union Rank for entering the Union Area (square miles) Alabama 77 1819 2222 52,42352,423 Colorado 88 1876 3838 104,100104,100 Hawaii 66 1959 5050 10,93210,932 Iowa 44 1846 2929 56,27656,276 Maryland 88 1788 77 12,40712,407 Missouri 88 1821 2424 69,70969,709 New Jersey 99 1787 33 8,7228,722 Ohio 44 1803 1717 44,82844,828 South Carolina 1313 1788 88 32,00832,008 Utah 44 1896 4545 84,90484,904 Wisconsin 99 1848 3030 65,49965,499 We are interested in whether or not the number of letters in a state name depends upon the year the state entered the Union. (a) Decide which variable should be the independent variable and which should be the dependent variable.Year the state entered the Union is the Click for List variable and the number of letters in a state name is the Click for List variable (c) Does it appear from inspection that there is a…"id" "surgery" "sex" "age" "weight" "length" "BMIpre" "BMIpost" "complic" "comorb" "depressi" "diabetes" "SES" 1 0 "Female" NA NA NA NA NA NA 0 0 0 12 0 "Female" 63 94 1,63 35,3795777 26,34649403 1 0 0 0 33 0 "Female" 29 74 1,57 30,02150189 NA 1 0 0 0 14 0 "Female" 32 112 1,67 40,15920255 25,4580659 0 0 0 0 15 0 "Female" 33 92 1,66 33,38655828 23,22543185 0 1 0 0 26 0 "Female" 33 108 1,55 44,95317378 NA 0 0 0 0 37 0 "Female" 41 70 1,62 26,6727633 NA 0 0 0 0 2 8 1 "Female" 20 102 1,76 32,92871901 25,82644628 0 0 0 0 39 1 "Female" 33 150 1,77 47,87896198 34,47285263 1 1 1 0 110 1 "Female" 37 113 1,69 39,56444102…Normalize the following table to the 3rd Normal form: Student Student Phone Course Term Grade Instructor Instructor Phone Lauren Fernell 555-7771 MIS 350 F12 A Hess 555-2222 Lauren Fernell 555-7771 MIS 372 F12 B Sarker 555-2224 Lauren Fernell 555-7771 MIS 426 F12 A Fuller 555-2227 Lauren Fernell 555-7771 MIS 375 F12 B+ Wells 555-2228 Brigit Schnieder 555-2215 MIS 350 F12 A Hess 555-2222 Brigit Schnieder 555-2215 MIS 375 F12 B+ Wells 555-2228 Brigit Schnieder 555-2215 MIS 372 F12 A Sarker 555-2224 Brigit Schnieder 555-2215 MIS 374 F12 B Clay 555-2221 Jackie Judson 555-1245 MIS 350 F12 A Hess 555-2222 Jackie Judson 555-1245 MIS 372 F12 B+ Sarker 555-2224 How many tables did you create after normalizing the table? List each of…
- BookID CustID Name Phone DateTimeRented DateTimeReturned 1 10 Henry Lawson (802)218-7318 (802)584-8249 7/22/2006 7:00:00 PM 7/23/2006 10:00:00 PM 2 3 Bob O'Connor (802)918-7565 7/21/2006 1:00:00 PM 7/22/2006 5:00:00 PM 3 6 Cary Jones (603)536-8739 7/21/2006 6:00:00 PM 7/22/2006 10:00:00 AM 4 4 Harry Salomon (603)536-7565 7/12/2006 10:00:00 AM 7/13/2006 9:00:00 AM 5 5 Mary Combs (603)536-3632 7/17/2006 4:00:00 PM 7/18/2006 3:00:00 PM 6 7 Mary Tyler (603)669-7431 7/10/2006 8:00:00 PM 7/11/2006 10:00:00 AM 7 2 Bonnie Artest (603)819-0387 7/1/2006 5:00:00 PM 7/2/2006 11:00:00 AM 8 9 Bobby Lamson (603)347-5592 7/11/2006 4:00:00 PM 7/12/2006 10:00:00 PM 9 1 Lorry Kovacs (603)536-0987 (603)536-1294 7/23/2006 7:00:00 PM 7/24/2006 6:00:00 PM 10 4 Harry Salomon (603)536-7565 7/20/2006 5:00:00 PM 7/21/2006 4:00:00 PM 11 8 Johny Milano…Errors.. ?Geographical Information System The table below shows the true and measured data coordinates from a set of 5 points for accuracy assessment. Calculate the RMSE based on these data. Point X True X Data Y True Y Data 1 14 15 93 90 2 65 63 78 78 3 23 27 9 10 4 39 38 16 14 5 42 45 51 56
