Statistika - Penyajian Data dalam Bentuk Diagram
Daftar Isi
Sebelum memasuki materi, perlu kita ketahui tentang istilah data tunggal. Daftar bilangan yang mempunyai satuan sama di sebut data tunggal, misal : cm, rupiah, tahun dan sebagainya. Data tunggal dapat dinyatakan dalam bentuk daftar bilangan atau dalam bentuk tabel distibusi frekuensi.
![Daftar bilangan yang mempunyai satuan sama di sebut data tunggal Statistika - Penyajian Data dalam Bentuk Diagram](data:image/png;base64,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)
![Daftar bilangan yang mempunyai satuan sama di sebut data tunggal Statistika - Penyajian Data dalam Bentuk Diagram](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAXIAAAD4CAIAAAB+GvpUAAAeH0lEQVR4nO2dW3QUx52H51Ev86hHvN7Z2HGixCa7ybGdyNxkDAjdRkiCaS6DuIiLhbgJZIiFsaURho4hxtk43iwYMHIjg53GIdbajmM78dkkQ+J2wCTOZbPR2XBOyJmT5PAwRw+c0/tQUC6qL9PTU33/faceoNVdXd3T9c2/qnqqUseOHRsDAABBHDt2LDU2NqYDAIAgxsbGoBUAgEigFQCAYKAVAIBgoBUAgGCgFQCAYKAVAIBgoBUAgGCgFQCAYKAVAIBgoBUAgGCgFXCTcrnc2NioKEr4868qK3Znr68REPzQiiRJKYZisejp6XxGkqTh4WHy71KplE6n6X+dQw4M9nEPuVbYWxQerYThgwshPmmF1jRVVQMxiyzLuVzuxo0bwnNmr06SJHdncfh0encVejVVzl0xoJXk4LdWyOfq4vu8RnzQiizLmUxmenpa+CkoSdaK66zQCPKfYLTCfsakZUQrJNk4OTmZTqdpXCPLMteGsjn2vffeo38qFovsnqlUitQH8iXDbiHFc3gi49WpqlpfXz81NUW3Wx2oaVpdXR09CzmKe9yNxXN+FaY3gSuzzd0jZWBbc+w9YbMlJ71+/brx87IpGJe/6YXTT43N1soODrMy1YrzJ5DCPSFchtxfWf9ycY2qquSMVo9ipAmgEcRWJLqdfgBkO1tFNU2bMWOGscZWPJZ+cvrtX7DlcjmbzZJ92A/b+Ym4qzPWXqsDrU7HPfqmxXN4FTY3wcndUxTF/p4Yi8F9XvYF4/K3dwGXrdEOzrMy7uP8CaRYPSFW94rdoqrq1q1bC4UCfWyICq0+60jjd5ct/bS4z6BUKmUyGeP3tn7r653b4uRYul23jdslSaKPhcMTcYfv3LmzsbGRzd/qQKNK2JjI9JGixXN4FTY3wcndO3r0KKmNVjdfN9OKTWXgCsbl78QFxj1dZ2VjAZsnkL113N3gMrT5qyzLk5OTM2fOnJ6eZj9603sVdfyOVihcW8CqOcDtTPJxeCx9sHRDhSQ9xxR6iMMTGa+O+6qxOtBJtGJTPCdXYXMTnNx5Y+TF3RPdgVZsCsblX4tWXGRltIDDJ9DqbnA7m94rEpXk8/np6WlJkorFoqZpDQ0NJIS0+qwjTZBaMUbXuu23H/2Tw2OttEI+e/o4Gr8iKp7I9OrYQS6rA9mGtFWVsCmek6twohX7u2fsJ9INX7w2WqlYMDb/WrTiIiv7NovxRFbQfUx35s7S0NBw9erVvr6+GzduqKo6PDxMXGNzr6JOYFqxGhJyohWHx3JaoV0M7PNkGuRXPJHV1cmybNpzRFFV1bQVY/W4c8VzchUVteLk7hlHtaz+aqqVigVjc6Cj8jQGca6VarOy6VsxPZEVzrVC/j04OEg90t3dff/99xu/fkwfxYgSmFb020PZ1K2ueOPnxEaJ3Jek/bFsjaJhAsmB9tjncrkDBw6QQ5yfyOrqyM6mYzds5zEb9Jr2rZgWz+FVVNSKw7tHqui5c+eM94QtBhkJMna+VCwYVQAbwZHxl6q0UlVW3IEOn0CbR5Hd2fT5oXeD/aDZp8jqs440eHnfV7gowDhMA0AMgFZ8hetz9eENOgD8B1rxlYpNKgBiALQCABAMtAIAEAy0AgAQDLQCABAMtAIAEAy0AgAQDLQSPE7eFq92T58JbcFAIEArweOnVrifEVr9Lqba6YftCyZJkun0JSCuQCvB46dW2F8t6da/HjCdectFweiPdKCVRAGtBI/PjSD6Y3yb6cis5gmttmDkR4AXL16sOL8EiBPQSvCwdZKbmZV7x9/018lWP5m1ab+Q3yKNjIzYzDXHrVLC/gKYndHW9JfBHE6mrQFxAloJHlonaQXmujyM083q1czIa4T6yKrThJtEhvNaipmtigQ+0ApggVaCxzgzq4tpVm1m5DXiRCumU4cYC0CneoZWAAVaCR7jzKwOp1l1OCOvEeICm2kZaLTCrdMIrQAnQCvBY5yZ1ck0q85n5OUysVpThcVqJMh0djVoBXBAK8FjnJn173//e8VpVp3PyGvcWHHw2H7FOHYRIoez1UMriQJaCR7TmVnJHLH206w6n5GXwjV8uNdYKNz0w/QothuIbbVZaYWbuNfJm3UgBkAroArwkj5wArQCqgBaAU6AVkAVQCvACdAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgBAMNAKAEAw0AoAQDDQCgCCKZVKM2fOnJ6eNv1ruVzO5/NWfxVekr6+vhs3bvhwLhZoBcSc9iffMU10h3K53NjYWF9fPzU1xW3MZDLO67+maTNmzJiamrLXiqqqw8PD5N+yLKdSqVQqlcvlaOU33ciWKnWLYrFYKpXS6XQqlaJ5aprW29tLD5QkqVgsOrwEUUArIOY40Uo2m92wYYOiKHSjqqobNmywsYMN9lqh9ZyGEkQW5OymG7misvqTZVlRFBoBGU/NWsw3oBUQcxxq5fz58w0NDbRCSpI0OTlJqihbV2kswAYOVBPc/iSUYIOFUqmUyWRYL9DTcQYx3VhRK8bYRNM09rr8AVoBMcehVqampmidJO64du2ajVaMUQCnlatXr3JO0S0CGVPXmG5kXUYaaLQRpCgKUQx3+fahk0dAKyDmONeKqqqkO4OECcboQ2e0omlaXV0daxYuSOE6awimsYPDUIVDlmW280XTtEKhQEpFLENLZRofeQq0AmKOc62QGvjhhx8a2zJGrZBjVVW1agRNTEwYe3yNsYMsy8a+D9ONHFSCbLYk4GILiWgFAPE414p+axSGVGlWE/QLX5IkboCGNj2MGjLagYsdJEky6sN0oxG6G1t+ohV2XBl9KwAEAFst6SCxfvv3PB30nZycJDWWbqEhiVErpqM5bA8OabCww8nGjdevX29sbCSHkOCIG35mu1To4bRPByNBAMSfaut5ja0YvLcCQPypVhOyLLv2QiAdKzq0AgAQDrQCABAMtAIAEAy0AgAQDLRSNZf++g+axj+eImnoR5esUvPET5onftLy7++27X+7bf/be0/8wjQp7/0Pmy7/6W8kBX25AFQNtGIOaw1OEO4S1Yq7xKkHxgFhBlr51CC1u8M7rdgbh+om6HsJgK4nUyvEI55KxE+t2IgGEQ0IhERoJRCPBKgVY4JlgJ/EViu0XROUR0KlFSgG+EmstEKjksAlEmatGBUT9OcG4kYctBJ4Aye6WoFigBdEWCuhDUwiqhX4BYgielqJlk2iqBX4BdRIZLQSUZtEWivwC3BH2LUStgGdZGqF9UvQTwSIAOHVStTDk1hqhcoFfgE2hFErMRNK/LTC+iXohwWEkXBpJR7tneRoBXIBpoRFK+MfTwVe86EVyAUIIXitXPrrPwKv89AK5AIEEqRWYtmHknCtQC5AD0oriRJKArXShtGiZBOAVmLfjQKtsHLx89ECIcFXrSQwSEm4ViCXZOKfVpIZpEAriTJLuVzO5/P+rCLIrt8eNvzQSpKDFGiFTZf/N4C5o97raDVN5K+lUimdTqdux8nipOwi8BRufWVJkurr6+k+dDV4uio7hSwCzxWAlo3mqWlab28vPTaQ9ZWd4LlWEh6kQCtc8j9ssdcKpdoV102h9ZwYYXJyMpPJEK3Q4IIYRFEU9sByuZzNZjlJybKsKAqNgIwLKgspsxd4qxUEKdBK4GZxpxVN0+rq6kjsQLaTWp3NZkk0YazkpVKJSsRqC0GSJBdaMcYmmqY1NDT4v3J7RTzUCpwCrVilvSd+4cUjZ0qN0Qqt8CQAoTow1UpF0VhtZBtBmUyGZEIbQYqiEMVwZTOeMSR4ohV0pkArTpI/XS2utSJJEtvZwdVhY5U2xg6mBjGGKhyyLHOdL5qmFQoFGkCxajONhgJHvFYS8jI+tBIVs7jTiqqqpG6TOMKJVpxEK7IsV+wNoafmsiWNILbXNinRCpwCrYTNLK61Qv5LYgSHWrHvW5EkyUkPK7sb2+dCtMKOKyeibwVOgVbCaRYncFqhnR2ZTCabzTrRis6MBHEDxrlc7uLFi7QPmI4x01BIVVXuTyRDtkuFNoJox238R4LgFGgl6mapnWrreY2tmPi/txJ4vQ15glbsk59jQ95RrSZkWXbthdB2rOiitIJ33qAVmAVQBGgFToFWRKWE/HQo9tSqFXSpQCtiUzw6WRJOrVoJvLpGJUErDhOaQjGgJq2g+QOteJHQFIo6NWkl8LoaoQStVJXQFIo07rWCUAVacZE2DZ4gqbBhlKSTyzfS9E5bC0kf7t0j/FkHvuFeK4FX1GileGuFyqKiL5wn4c868A2XWkGokhCt2PvChSycpz8qL3vxxAMfcKmVwGtp5FLYtGL0RY3BhRfJiyce+IAbrVy6hndVwquVSPjCYfrb5UsePffAU9xoBS2gQLQSJ184TOi4jShutBJ4FY1istFKAn0BrcQbaMXztPT5t5Y+/1b/s8fgCxfJo+ceeErVWkHHihOJrCuc3z54ZvvgmX1rXiRJfubxF95cdup499nRzsDraoQSuleiSNVaQcdKRYOYJqIVms6OdsIv0EpcgVY8kUhFrcAvDtMfXx737ukHHgGtWBpk6fNvEYO4kIhzrcAv0Er8gFZqDUNEaQV+gVZiQ+K04o9EatEK65cLG9sDr9jQCqiWOGslKIOI0grrl8CrN7QCnFO1Vl768HeB+yL8EhGrFZKSOTj9/ndf8O7pBx4RyfdWvOhSDb9Wktn5Aq1Ekaq1ov35GsKQYLWSKL9c+ulPvXv6gUe40crC0z+ERMKgldj75WTT3OhqxXR5sHK5nM/nha8Zxi7MHAaC1EpcDeK/VuLql8L9X/FBK9x6yXTNY9PdnC9CaKoVbjVVSZLq6+vp2u9cSbhzlUqldDqdSqVoDpqm9fb2EpuEauHU6rXyf3+Z953vQSLh1ArrlxgMTrfceUftj/h3386ZJrpDuVzOZrO0blshRCu08hNHTE5OZjIZVis2JSHLvNN4h8s/VMu8u/kF85znJuwDlih2qcZMK6xfArdD5LTC1lgSEVy/fp3GEZlMZnp6mo0sisWipml1dXXkv6R6G7VSKpVYiRi3VKUVLjzRNK2hoSEkSzK71Mq876gIQyKhFZKiODhduP8rvmmFa3oYtXLjxg0uWrGKDqgaTLViLxq2JERebM60EaQoClEM99fwrPTuTitn5jw3AYlESCtR9EvLnXeEJ1oxaoWEJ1xHiZWb6CFcQGGMXyiyLOdyOdNeWE3TCoUCjY+IX2yy8h83Wtn26o/mPDexe8W3Aq+rEUoh0QpNIe/cJaHKnmU9tT/iHmmFoKoqkYiqqsQCdDcX0QqXs6lWaCakEUSLF/lohWhloOfg3vx/BF5do5LCppWQ+4WEKgFqhdZ2SZJo9TYdbSHtEdomIkGElVbs+1ZYJEkyNrLYopLC0KHlyPetEK2sXf/sjtzhwKtrVFJotRJCv5BQJUCt6LouyzJpzkxOTtJXQkhsQno96A5cD24mk8lms6Za0RkxcR06xFwkf3YLdy1slwptBJEMIz8SRLWCgCVOWmH9EuDgNHWKKK2ECu8qf7TfW9Fv18pAz8HAa2wkUoS0EqxfqFNa7rxj/Mhhj577oPCoByRUHSu6O62c+PnHrFbQFIqrVkjyc/CIDVViqZWEIEArAz0HMSoUY6345hfOKdBKdHGnlctznptYuusFqhV0siRBKzR50blrdAq0El3caEX78zWjVrZ0H9wDsyRDK8L9crJprtEpLXfeEd2fLycckVqBWZKmFSF+sXIKtBJd3Gtl8ehJo1b6uw7uWQWzJE4rrF+qGjyycQq0El3caeUvJlrpuakVmCXJWqnKL/ZOEfKDIBAIbrSi67q9Vvq7Du5ajrGhRGuF9YvzPlpoJR641Mq219611wrMAq2wiRucduIUaCW6CNPKgEEr/V1P71r+XOD1OSQp4Vqh6exo5+OdDzhxSvze3E8OLrVC3ogz0cptZnm6v+vp7cueCbxKhyFBKy+8uWzk+OLuvpkLG/7JiVbw0kp0cakVMhjkRCv9XU8/uuQAwhZopf+ph2Y1Z2Y1ZxxqBcNA0cWlVnRdr0orMEvCtdLdN5M4xblWhD/rwDfca2Xba++yPwtiX13htdJ14NElBzYvGdvcOTYoJVQuidUKafhQpzjUClpAkca9VrQ/X3Ohlc2dY4PS0cArObQSiFBIQsdK7HGvFV3X3WllU7awKVsYzCVLLknTCu1JcacVsU858JmatPLGKx8418qjt2tlU7awsWN0Z2LkkhytWAUpzrWCUCXq1KQVXddttULNYqmVjR2jW7rlnblnA6/20IoPQnGoFYHPNwiEWrXCBizutLKxY3RD+8iWrkM7ct8MvPJDK54KxYlWEKrEgFq1ouv60f0vV6eVToNWOkY2tD/V1/7U+vYn4yqXuGqlKqHMas7Mm/3PCFVijwCt/P7KlECtrG97cl3b/u3L4iaX+GmlWqE40QpClXggQCv6raZQ1VrJsloZYbWyrm3/2tYnti87MrTy+cCNAK3UbhMnWoFTYoMYrei6fnT/y5W0cqBaraxt3be2dd/mzrFtSyM/uX8MtFKjUCpqpfaHEIQEYVr5/ZUp49wI3Pv77rSytnV4TcvwmpbHty19ZtvSqP5wMbpaEWITmuZ/5U6EKrFHmFZ0XX/jlQ+caGWztVb6bLWypuXx3pav9y7++taeZ7b2RMwvkdOKWJvYawVOiRkitaLr+huvfCBKK+ustdK7eG/v4r2rm/ds7fnG1p5vBK6MOGnFI5vYaCW6TqlxLcFyuZzP50UtRUjXeBeSW40I1oqu6z+Y+MChVjZV1soT9lpZ3bxndfNjq5sf29ojb+2RA3dHRLUycnyx1zax0ooPTtm/7pRpojtwq6zTtdMr4lArJH/jAsnsesx0oXh2RXe60nt9fT1Zeb5UKqXT6VQqRQ/UNK23t5ccEp5lmMVrRb/NLD5pJb9oKL9oaNWi3asW7R7oOTTQfShwj4RfK0Ql/tjEVCuPLfVj/jcnWslms6TeaprW0NDgMIKoUSvUAjTQIHsSr2maNmPGDFIqWZaJbmRZVhSFhjlcAbxbN75aPNGKruvPPvGy51pZbK6VlYt2rVy4a8XCwXXtT2zpPtTfHYrF58OgFRqV+KwSNtFZEXxr+1SrFfLlr2laXV0dCRZoXWXjmmKxSGs1CSKII2iIkclkpqen2UPIFpJVqVTKZDLkpCySJBGtyLJMz0t35rTChSdVOdFTvNKKfjNmcaSVjZ9q5alPtdJWq1ZWLBxcsWDn8gU7pQU7pEd29Hcd7F/ydFATdwellZHji/ufeqi770vdfV8KSiVGrfjZn1JjI4iVDhcOEK1cvXqVOoVtktCdTaMV00iHdQ0xCLedNoIURWF3sMkzEDzUis6YRZxWHjfXSrOVVgapVqRHtufmb8/N377s4W1rWh4nRXp0yQF/ZpbyRyskHukfmdWzgXjkM7Oa/4VJodCKz320VUUrbNwhSRJ1DbVGXV0dG0Sk02na8aEzoQrbUWKqFdPIgoYquoVW2MMLhQINqcieVhGQ/3irFf2WWUynXHGslX3CtbLs4W1LH966tGmgp2mgp2lLT1P/6uY9mzoLmzoLmzpHd3ow0ZQXWhk90TJ6omWgMDu3+d+WbfrXuW13zWm9a07LZ2a3fGZWM03h0sqpF45497CZUpVW9Fv1WVVVKykQd9BG0MTEBG3dmPZuOIxW2FaPbmgEsTvT/5JGEA2RkhKtEH4w8UFVWlkfhFa65/V3z3u0a97mrnmbu+ZuWjJ3U+fcjZ1zNq5cuHtjdmRjx8iGjpGduWddz+HgTitjp1rHTrUWTrYWTrZsPzhnxbYvL9/65eUDX57f9dn5Sz77cOfdD2fvbsrePa/jrnntd4VfK9qlAGa9rkorVAFUECQi4KRA1EOrMVUA28/KYhyj4SILSZI4H5l22XKlJdnSHt9E9K1wXDjzE4NWCtVqZU21WllYq1Y652zMzt6Qnb2hY1Zfx6y+9lnr2x9a3/7QurbGdW2Na6VHdkjzd0jzt+fmb1/ftn992xPr255Y17pv3c03bm6+d7O2dfjre3Y8Pd42dKRp6EjT7iNNu4807TrctOtw065nmnY907TrG01rdj+wZtcDvbvuXz14f8uKL7SsaFi8vKFZ+nyz9PlFuc8vWva5hUs/t6DnngU99zzS/dnbtNIRAa0MDOV8eMZMcde3QjdmMplsNkukQIeBSXhCtcKO4LDtIGoKspHtstUZ17Ddw+wYM3c6chTbOKIH0t7imI8EmXLhzI8D0cpyz7TS+rU1rV9b0/q13pavrm756urFX803P7iq+cFVix5cuejBlQsfXLHggRULHlj+yANSW/v87r6ZXX33da2/b8m6+zrX3de55r7smnuzvfd2rL63PX9ve/6Lbau+2LryC60rvxAzrRw//U1/HrBoIdwCMX9vxYbfXp765r7TpjM59X06N0J4tdIBrVQZpATS8IkEYrtCwtOxovuvFcKFMz8OQis7oquVhZW0Mjd8WkGQkliC0Yqu67+9/KcLZ37MaoWbycmgFfbVFWgl1FpBkJJwAtMK4fvK+6610guthFIrEAoIWCuE7yvvV9AK/6KtH1pZEk6tdFOt3B02raDVAwih0Arh+8r70EpEtYJWD2AJkVYI55X3oJVatDLbX61AKMBI6LRCOP/yuzVqZeVtWtlpoRViluhrpT0ArUAowIqQaoVwfvxdF1pZ5UYrW7rn9XfP6+8iZgleKw2h1crAUA59KMCeUGuFcH78R+r4O060kvdfK421aqUjOlpBeAIcEgGtUNTxd26fcuVTrayGVlitLBasFQgFVEWUtEJQx99Rx9+BVnzQCmwC3BE9rVDU8R9+7/QPa9LKw9AKbALEE2GtUL53+u0DQy8YtLKrOq00MVqZ514riyOrFWITCAXUThy0Qnnt9FuvnX5r1aLdEdHKvS608oiVVtrcaGVgKIfYBAgnVlqh/PrSH1576a1XX3pTpFZmh0YrXbVqBYEJ8JR4aoXl17/6w6un3jx36r8SqZWbQqFRCVQCfCD+WuE4e2ry7MnJJ3c8t6yyVjZFWisDQ9LAUE679DPt0s+CvusgWSROKyxXPvr92ZNvvHLyjVdOvhF1rWzbu3zb3uUvjh+FR0DgJForRq589LuJExcmTlw48+KF4W2HPddKb1VaIZOt3DO4b8XOfSt2Dq84eeboR5d//tHlnwd92wC4DWjFEZe13yovvq4cf105fn7vFnnvlkN7+w95p5XHRvOPjeaHRvNDI/nT5751+uy3Ll0p/upK8VdXYBAQAaAVMVz65SeXfvmbW+nXJL30n6+e+i5J58aVU6+8/vzE69+eOP/tM+e//fEnFy9/cvHyJ8XLnxQv/+ZmCvoiABADtAIAEAy0AgAQDLQCABAMtAIAEAy0AoBIRK0uWC6X8/m8wDUPyfLvQnKrCLQCYs7ic/9tmugO5XI5m81OTU3ZZKJp2owZM+z3IdhrxXk+7ArNdI13uuo7XUC+vr6e5FYqldLpNLuevKZpvb29VCV+rtAMrYCYI0QrzhEVrVALlEqlQ4cO6bpeLpcbGxsVRWHdJMsycY0sy4qi0BjHWAzhK8nbAK2AmONCK5qm1dXVkXCAVEVaS8k/RkZGyF+N3/90T2MmzvMplUqZTIYzHd0oyzKbId3IasUYm2ia1tDQ4M/a79AKiDm1RCv0T6wO0um0oig6EymwhxjDBDZ/h/lwmdBGEDEFMQjdk2iFNoIURWF3sCmYd0ArIOa404okSalbFItFLsoglZN2XtBqrygKuwOXiW6IVrh86NlNIwvSCBoeHjbVCntsoVCgsZLNnt4BrYCY40IrqqqS8IHU5IpaYU9HdzBmojvWilVkQfI8cOCAsVXF/Zc0gticEa0AIAx3WiH1lnznu9YKl4lejVZoZKGqKo04JEkaHh427bLlLoRohR1XRt8KAP5Bogm2tUK3ZDKZbDbrTivGTHTHWtGZkSC2eNQgtNmVyWTYLhgqINoIoh23GAkCIOkItwDeWwEg6YjtCvGzY0WHVgAAwoFWAACCgVYAAIKBVgAAgoFWAACCgVYAAIKBVgAAgoFWAACCgVYAAIKBVgAAgoFWAACCgVYAAIIZGxtLHT58eAwAAARx+PDh/wc39hE6az8eFwAAAABJRU5ErkJggg==)
Gambar : diagram lingkaran menunjukkan perbandingan dan persentase data satu dan yang lainnya.
Contoh :
Data berat badan 10 orang dalam kg :
41, 43, 45, 47, 52, 44, 50, 53, 46, 47
Contoh2 :
Catatan: data seperti pada contoh ini sering di sebut data tunggal berbobot.
Satu data tunggal dapat di sajikan dalam bentuk diagram
1. Penyajian data dalam bentuk diagram
a. Diagram batang
Dalam penyajian data dengan diagram batang, data di sajikan dalam bentuk batang yang berbentuk persegi panjang yang di gambarkan vertikal atau horizontal dengan lebar sama.
Contoh :
b. Diagram garis
Diagram garis di gunakan untuk menyajikan data yang menunjukkan perkembangan suatu data dari waktu ke waktu.
Contoh :
Hasil panen padi nasional Indonesia senantiasa berubah dari tahun ke tahun. Hasil panen dari tahun 2005 – 2010 di sajikan dalam diagram berikut.
c. Diagram lingkaran
Diagram lingkarang di gunakan untuk menunjukkan perbandingan antar item data dengan cara membagi lingkaran dalam juring-juring lingkaran dengan sudut pusat yang sesuai dengan perbandingan tersebut.
Contoh:
Daftar jumlah siswa kelas X Rpl 1 yang mengambil pelajaran ekstrakurikuller musik adalah 9 orang, tari 5 orang, Futsal 6 orang, basket 8 orang dan ekstrakurikuller lainnya 12 orang.
Jumlah seluruh siswa = 9 + 5 + 6 + 8 + 12 = 40
Perbandingan dan persentase untuk masing-masing pelajaran adalah sebagai berikut.
Musik : 9/40 = 22,5 % ; Tari : 5/40 = 12,5% ; Futsal: 6/40 = 15%; Basket 8/40 = 20%; dan lain-lain 12/40 = 30%.
Gambar : diagram lingkaran menunjukkan perbandingan dan persentase data satu dan yang lainnya.
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