M TN TOT P TOR - Using this spreadsheet 1. You can select calls by clicking on the select groups of cells by holding down yo 2. Mostly you will select entire columns. Do this by clicking on the gray letter (such a 3. You can scroll up and down your screen using the scroll bar on the right side of the To make graphs in Excel 1. Select the first column you want by clicking on the letter above it 2. Select the second column by holding down the control key d you are working in while you click on the Inter above the column you want 3. With two columns selected highlighted or outlined) click on the "graphing wizard" OR select the "Insert menu thon "Chart..." 4. Select the "XY scattery chart type, then click 'Next," 5. Then select the top left chart sub-type--a dot graph or scatter plot with NO line. CII 6. On the Data Range dialog box, simply click "Next." 7. Add a title to identify the variables in the graph For the X axis, enter the LEFT-MOST variable you selected in steps 1 and 2 abov For the Yaxis, select the RIGHT-MOST variable from steps 1 and 2 a. Click "Finish. The chart will appear on top of your spreadsheet You can move charts around and resize them by selecting them and dragging we 22 Italy b A B D ET F G H K Country HDi rank GNP Per Capta, Adult Literacy Life Expectancy a infant Mortality Contraptive Use, Birth Rate 1970 Popul 2000 Pop 2050 Pop Region 2 Canada 1 19,170 99 51.7 5.5 73 11.2 21.3 30.764 40.24 North America 3 France 21 24 210 99 732 77 126 50.8 59 363 65.098 Western Europe 4 Norway 3 34 310 99 726 4 76 133 3.9 4.487 5.071 Northern Europe 5 USA 41 2024 99 79.1 7 71 14.5 210.1 275,6 403 687 North America 6 looland 5 27,830 99 70.6 2.6 16.3 02 0.281 0.335 Northem Europe 7 Finland 6 24,280 99 70.9 42 BO 112 4 5.177 4.78 Northam Europe 8 Netherlan 7 24,780 99 76 5 78 12.5 13 15.921 1723 Western Furope 9 Japan 8 32,350 99 75 3.5 59 94 104.3 120 876 100.496 East Asia 10 New Zeal 9 14,800 99 60.5 5.5 69 14.9 28 3.830 4.49 Oceania 11 Sweden 10 25,580 99 474 3.5 78 99 8 8 8.800 9.200 Northern Europe 12 Spain 11 14,100 97.1 71.2 5.B 59 9.19 33.6 39.466 30.709 Southern Europe 13 Belgium 12 25,380 99 75.1 56 79 11.2 9.7 10.246 10 Wontem Europe 14 Austria 13 28,830 99 56.9 4.9 71 10 7.5 8,094 7.881 Westem Europe 15 United Kir 21,410 99 46.3 5.7 82 11.97 556 59.75 64.158 Northern Europe 16 Australia 15 20.640 99 54.4 13 76 13.1 12.5 192 24.9 Oceania 17 Switzerlar 16 39.980 99 722 48 71 11 6.2 7.142 7.356 Western Europe 18 Ireland 17 18.710 99 52.9 62 14.5 3 3.796 4.529 Northern Europe 19 Denmark 18 33 040 99 71.1 4.7 78 12.47 4.9 5.33 6,132 Northem Europe 20 Germany 19 26,570 99 76.7 4.7 75 9.36 77.7 42. 141 73.303 Western Europe 21 Greece 20 11,740 98.7 553 6.68 9.59 8.8 10.596 9.65 Southern Europe 21 20,090 98.1 68.6 5.5 93 538 57.82 41.645 Southern Europe 23 Israel 22 16.180 96 44.5 6 21.6 3 6.227 9.44 Westem Asia 24 Cyprus 23 11,920 94 7.6 13.8 0.6 0.882 1.113 Wasiem Atla 25 Barbados 24 97.4 69.5 14.2 55 14.1 0.2 0.259 0.266 Caribbean 26 Lucemboi 28 45,100 69.3 5 126 03 0.438 0.594 Westem Europe 27 Malta 27 10,100 91 742 5.3 11.9 0.3 0.39 0.432 Southarn Europe 28 Singapore 28 30,170 91.1 68.1 3.2 74 12.8 2.1 4001 10.371 Southeast As a 29 Antigua al 29 8.450 95 76.4 17.1 53 21.9 0.1 0.06a 0.079 Carbbean 30 Korea, Re 30 8,800 772 11 79 13B 31.9 47.275 51.148 East Asia 31 Chile 31 4,990 95.2 75.7 10.5 18.3 9.5 15 211 22.215 South America 32 Bahamas 32 98.2 72 18.4 62 20.7 0:2 0.31 0.485 Caribbean 33 Portugal 33 10,670 89.6 52 5.4 66 9 10.013 8.189 Southern Europe 34 Costa Ric 34 2.770 948 492 12.0 75 21.8 1.7 3.589 7.021 Central America 35 Brunei Da 35 882 76.4 24 25 0.1 0.331 0.704 Southeast Asia 36 Argentina 38 8.030 96.2 66.1 19.15 18.91 24 37.048 54.522 South America 37 Slovenia 37 9.780 76.9 5.2 9 1.7 1.968 1.642 Southern Europe 38 Uruguay 38 6,070 973 49 14.5 183 2.8 3.313 4.231 South America 39 Czech Re 39 5,150 99 78.2 4.5 69 8.8 9.8 10.275 9.306 Eastern Europe 40 Trinidad a 40 4,520 979 76.4 16.2 53 14 1 1295 1.543 Caribbean 41 Dominica 41 3,150 94 50.2 14.6 50 162 0.1 0,076 0.084 Caribbean 42 Slovakia 42 3,700 99 51.2 6.8 74 10.7 4.5 5.401 4.705 Eastern Europe 43 Bahrain 43 7,640 85.2 75.1 8.07 53 21.6 0.2 0.691 2.667 Westem Asia 44 FU 44 2,210 91.6 70.3 129 41 217 0.5 0.611 1.31 Oceania 45 Panama 2,990 90.6 68.6 200 04 21.9 1.5 2.857 4.263 Central America 49 107 24.17 42.152 South America For this exercise you will make the following X,Y dot graphs: Y Adult Literacy Birth Rate GNP per Capita Birth Rate Life Expectancy Birth Rate Infant Mortality Birth Rate GNP Per Capita Adult Literacy Independent and Dependent Variables Note that by convention the horizontal (X) axis is the Independent variable. The verti For these graphs you are most interested in positive and negative relationships betw Sull, you should pay attention to which variable is dependent and which is independe To resize and reshape graphs: Click somewhere on the graph to activate it You should see little black markers around the margin of the graph Drag the marker in the middle of a line to make the graph taller or wider 249 D E H J K M d L de mortality copy and paste this directly from the data table I survivorship. The first cell is the total from the d column. The next cellis equal to the cell above it). (the total number who died in that interval) 21 14 9 12 15 13 7 14 K26 B 1 Age Class Age 2 1 0-4.99 3 2 5-9.99 4 310-14.99 5 4 15-19.99 6 5 20-24.99 7 6 25-29.99 8 730-34.99 9 8 35-39.99 10 940-44.99 11 10 45-49.99 11 50-54.99 13 12 55-59.99 14 13 60-64.99 15 14 65-69.99 16 15 70-74.99 16 75-79.99 18 17 80-84.99 19 18 85-89.99 20 19 90-94.99 21 20 95-99.99 22 21 over 100 P3 Total scaling factor 3.731 3.731 3.731 3.781 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 (1000) 1000 922 869 836 791 735 687 660 608 545 504 463 388 306 228 172 112 49 15 0 0 Qe mortality rate / scaling factor you will have to standardize the scale ito (1000) - to compare across groups (populations), which is per 1000 individuals in population blology. TO DO THIS: You need to FIRST calculate a scaling factor for this one in a separate cell (NOT IN THE TABLE). This is going to be - 1000/total from column 1). You will have to caculate the factor Independently for the other three groups. 17 11 11 20 22 21 15 16 17 9 4 12 268 0.078 247 0.057 283 0.039 224 0.054 212 0.071 197 0.066 184 0.038 177 0.079 163 0.104 146 0.075 135 0.081 0.161 104 0.212 82 0.256 61 0.246 46 0.348 30 0.567 13 0.692 4 1.000 0 0.000 0 0.000 2650 round decimals to three places 124 102 9.5 9.1 8.7 8.1 7.6 7.2 6.8 6.1 5.6 5.1 4.5 3.7 2.8 2.1 1.5 0.9 0.3 0.1 0.0 0.0 257.5 240 228.5 21R 204.5 190.5 180.5 170 154.5 140.5 129.5 114 93 71.5 53.5 38 21.5 8.5 2 01 0 2516 1000) column scaling factor L another intermediate number that is necessary to calculate the % alive during a particular period. In - (In+In+1) %= (each L/sum of all L values) 100 0 0 268 whole numbers ONLY express as percents 4 5 6 7 8 9 3. Third, fill in the column headed "q" The letter "q" stands for "mortality rate," and is simply the number of people who died during an age interval, divided by the number of people who were alive at the beginning of that interval. In other words, it is equal to "d" divided by "." This is an interesting statistic because it tells us how safe or dangerous a particular time of life is. The quantity "q" ranges between zero and one. Zero is the safest figure, indicating an age interval in which nobody died. One indicates a deadly age interval, which nobody got out of alive! Represent your quotients as decimals rounded off to three places. 4. Fourth, calculate "l(1000)." This represents the theoretical survivorship we would get if all of us were working with a group of 1000 individuals, instead of working with categories with different numbers of people in them. So it permits us to compare survivorship among our four unequally-sized categories, by pretending that they all included 1000 individuals. To complete this column divide 1000 by your first "l" (which, you may remember, represents the total number of people in your group). Then multiply each subsequent "l" by this quotient. For example, if there were 250 people in your category you would divide 1000 by 250 to get the quotient four. You would then go down the column headed "1" and multiply each figure in that column by four, entering the product in each case in the "(1000) column. Round off each product that you enter in the "(1000)" column to the nearest whole number. Remember that it represents survivorship, and that fractions of people don't survive. THIS WILL BE A DIFFERENT NUMBER FOR EACH DATA SET. M TN TOT P TOR - Using this spreadsheet 1. You can select calls by clicking on the select groups of cells by holding down yo 2. Mostly you will select entire columns. Do this by clicking on the gray letter (such a 3. You can scroll up and down your screen using the scroll bar on the right side of the To make graphs in Excel 1. Select the first column you want by clicking on the letter above it 2. Select the second column by holding down the control key d you are working in while you click on the Inter above the column you want 3. With two columns selected highlighted or outlined) click on the "graphing wizard" OR select the "Insert menu thon "Chart..." 4. Select the "XY scattery chart type, then click 'Next," 5. Then select the top left chart sub-type--a dot graph or scatter plot with NO line. CII 6. On the Data Range dialog box, simply click "Next." 7. Add a title to identify the variables in the graph For the X axis, enter the LEFT-MOST variable you selected in steps 1 and 2 abov For the Yaxis, select the RIGHT-MOST variable from steps 1 and 2 a. Click "Finish. The chart will appear on top of your spreadsheet You can move charts around and resize them by selecting them and dragging we 22 Italy b A B D ET F G H K Country HDi rank GNP Per Capta, Adult Literacy Life Expectancy a infant Mortality Contraptive Use, Birth Rate 1970 Popul 2000 Pop 2050 Pop Region 2 Canada 1 19,170 99 51.7 5.5 73 11.2 21.3 30.764 40.24 North America 3 France 21 24 210 99 732 77 126 50.8 59 363 65.098 Western Europe 4 Norway 3 34 310 99 726 4 76 133 3.9 4.487 5.071 Northern Europe 5 USA 41 2024 99 79.1 7 71 14.5 210.1 275,6 403 687 North America 6 looland 5 27,830 99 70.6 2.6 16.3 02 0.281 0.335 Northem Europe 7 Finland 6 24,280 99 70.9 42 BO 112 4 5.177 4.78 Northam Europe 8 Netherlan 7 24,780 99 76 5 78 12.5 13 15.921 1723 Western Furope 9 Japan 8 32,350 99 75 3.5 59 94 104.3 120 876 100.496 East Asia 10 New Zeal 9 14,800 99 60.5 5.5 69 14.9 28 3.830 4.49 Oceania 11 Sweden 10 25,580 99 474 3.5 78 99 8 8 8.800 9.200 Northern Europe 12 Spain 11 14,100 97.1 71.2 5.B 59 9.19 33.6 39.466 30.709 Southern Europe 13 Belgium 12 25,380 99 75.1 56 79 11.2 9.7 10.246 10 Wontem Europe 14 Austria 13 28,830 99 56.9 4.9 71 10 7.5 8,094 7.881 Westem Europe 15 United Kir 21,410 99 46.3 5.7 82 11.97 556 59.75 64.158 Northern Europe 16 Australia 15 20.640 99 54.4 13 76 13.1 12.5 192 24.9 Oceania 17 Switzerlar 16 39.980 99 722 48 71 11 6.2 7.142 7.356 Western Europe 18 Ireland 17 18.710 99 52.9 62 14.5 3 3.796 4.529 Northern Europe 19 Denmark 18 33 040 99 71.1 4.7 78 12.47 4.9 5.33 6,132 Northem Europe 20 Germany 19 26,570 99 76.7 4.7 75 9.36 77.7 42. 141 73.303 Western Europe 21 Greece 20 11,740 98.7 553 6.68 9.59 8.8 10.596 9.65 Southern Europe 21 20,090 98.1 68.6 5.5 93 538 57.82 41.645 Southern Europe 23 Israel 22 16.180 96 44.5 6 21.6 3 6.227 9.44 Westem Asia 24 Cyprus 23 11,920 94 7.6 13.8 0.6 0.882 1.113 Wasiem Atla 25 Barbados 24 97.4 69.5 14.2 55 14.1 0.2 0.259 0.266 Caribbean 26 Lucemboi 28 45,100 69.3 5 126 03 0.438 0.594 Westem Europe 27 Malta 27 10,100 91 742 5.3 11.9 0.3 0.39 0.432 Southarn Europe 28 Singapore 28 30,170 91.1 68.1 3.2 74 12.8 2.1 4001 10.371 Southeast As a 29 Antigua al 29 8.450 95 76.4 17.1 53 21.9 0.1 0.06a 0.079 Carbbean 30 Korea, Re 30 8,800 772 11 79 13B 31.9 47.275 51.148 East Asia 31 Chile 31 4,990 95.2 75.7 10.5 18.3 9.5 15 211 22.215 South America 32 Bahamas 32 98.2 72 18.4 62 20.7 0:2 0.31 0.485 Caribbean 33 Portugal 33 10,670 89.6 52 5.4 66 9 10.013 8.189 Southern Europe 34 Costa Ric 34 2.770 948 492 12.0 75 21.8 1.7 3.589 7.021 Central America 35 Brunei Da 35 882 76.4 24 25 0.1 0.331 0.704 Southeast Asia 36 Argentina 38 8.030 96.2 66.1 19.15 18.91 24 37.048 54.522 South America 37 Slovenia 37 9.780 76.9 5.2 9 1.7 1.968 1.642 Southern Europe 38 Uruguay 38 6,070 973 49 14.5 183 2.8 3.313 4.231 South America 39 Czech Re 39 5,150 99 78.2 4.5 69 8.8 9.8 10.275 9.306 Eastern Europe 40 Trinidad a 40 4,520 979 76.4 16.2 53 14 1 1295 1.543 Caribbean 41 Dominica 41 3,150 94 50.2 14.6 50 162 0.1 0,076 0.084 Caribbean 42 Slovakia 42 3,700 99 51.2 6.8 74 10.7 4.5 5.401 4.705 Eastern Europe 43 Bahrain 43 7,640 85.2 75.1 8.07 53 21.6 0.2 0.691 2.667 Westem Asia 44 FU 44 2,210 91.6 70.3 129 41 217 0.5 0.611 1.31 Oceania 45 Panama 2,990 90.6 68.6 200 04 21.9 1.5 2.857 4.263 Central America 49 107 24.17 42.152 South America For this exercise you will make the following X,Y dot graphs: Y Adult Literacy Birth Rate GNP per Capita Birth Rate Life Expectancy Birth Rate Infant Mortality Birth Rate GNP Per Capita Adult Literacy Independent and Dependent Variables Note that by convention the horizontal (X) axis is the Independent variable. The verti For these graphs you are most interested in positive and negative relationships betw Sull, you should pay attention to which variable is dependent and which is independe To resize and reshape graphs: Click somewhere on the graph to activate it You should see little black markers around the margin of the graph Drag the marker in the middle of a line to make the graph taller or wider 249 D E H J K M d L de mortality copy and paste this directly from the data table I survivorship. The first cell is the total from the d column. The next cellis equal to the cell above it). (the total number who died in that interval) 21 14 9 12 15 13 7 14 K26 B 1 Age Class Age 2 1 0-4.99 3 2 5-9.99 4 310-14.99 5 4 15-19.99 6 5 20-24.99 7 6 25-29.99 8 730-34.99 9 8 35-39.99 10 940-44.99 11 10 45-49.99 11 50-54.99 13 12 55-59.99 14 13 60-64.99 15 14 65-69.99 16 15 70-74.99 16 75-79.99 18 17 80-84.99 19 18 85-89.99 20 19 90-94.99 21 20 95-99.99 22 21 over 100 P3 Total scaling factor 3.731 3.731 3.731 3.781 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 3.731 (1000) 1000 922 869 836 791 735 687 660 608 545 504 463 388 306 228 172 112 49 15 0 0 Qe mortality rate / scaling factor you will have to standardize the scale ito (1000) - to compare across groups (populations), which is per 1000 individuals in population blology. TO DO THIS: You need to FIRST calculate a scaling factor for this one in a separate cell (NOT IN THE TABLE). This is going to be - 1000/total from column 1). You will have to caculate the factor Independently for the other three groups. 17 11 11 20 22 21 15 16 17 9 4 12 268 0.078 247 0.057 283 0.039 224 0.054 212 0.071 197 0.066 184 0.038 177 0.079 163 0.104 146 0.075 135 0.081 0.161 104 0.212 82 0.256 61 0.246 46 0.348 30 0.567 13 0.692 4 1.000 0 0.000 0 0.000 2650 round decimals to three places 124 102 9.5 9.1 8.7 8.1 7.6 7.2 6.8 6.1 5.6 5.1 4.5 3.7 2.8 2.1 1.5 0.9 0.3 0.1 0.0 0.0 257.5 240 228.5 21R 204.5 190.5 180.5 170 154.5 140.5 129.5 114 93 71.5 53.5 38 21.5 8.5 2 01 0 2516 1000) column scaling factor L another intermediate number that is necessary to calculate the % alive during a particular period. In - (In+In+1) %= (each L/sum of all L values) 100 0 0 268 whole numbers ONLY express as percents 4 5 6 7 8 9 3. Third, fill in the column headed "q" The letter "q" stands for "mortality rate," and is simply the number of people who died during an age interval, divided by the number of people who were alive at the beginning of that interval. In other words, it is equal to "d" divided by "." This is an interesting statistic because it tells us how safe or dangerous a particular time of life is. The quantity "q" ranges between zero and one. Zero is the safest figure, indicating an age interval in which nobody died. One indicates a deadly age interval, which nobody got out of alive! Represent your quotients as decimals rounded off to three places. 4. Fourth, calculate "l(1000)." This represents the theoretical survivorship we would get if all of us were working with a group of 1000 individuals, instead of working with categories with different numbers of people in them. So it permits us to compare survivorship among our four unequally-sized categories, by pretending that they all included 1000 individuals. To complete this column divide 1000 by your first "l" (which, you may remember, represents the total number of people in your group). Then multiply each subsequent "l" by this quotient. For example, if there were 250 people in your category you would divide 1000 by 250 to get the quotient four. You would then go down the column headed "1" and multiply each figure in that column by four, entering the product in each case in the "(1000) column. Round off each product that you enter in the "(1000)" column to the nearest whole number. Remember that it represents survivorship, and that fractions of people don't survive. THIS WILL BE A DIFFERENT NUMBER FOR EACH DATA SET
