<?xml version="1.0" encoding="UTF-8"?>
<quiz>
 <!-- categoryid: 555 -->
 <question type="category"><category><text>Normal Probability Distributions/Normal Approximations to Binomial Distributions</text></category></question>
 
 <!-- resourceid-resourcedataid: 5573-4988 -->
 <question type="multianswerwiris">
    <name>
      <text>Question 17</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p><span style="font-size: medium;"><strong>Heights of Trees</strong></span></p>
<p><span style="font-size: medium;"><img style="float: right; border-width: 1px; border-color: black; border-style: solid; margin: 5px;" src="@@PLUGINFILE@@/Question%2017.jpeg" alt="" width="260" height="194" />The heights of fully grown sugar maple trees are normally distributed, with a mean of #m feet and a standard deviation of #sd feet.  Random samples of size #n are drawn from the population and the mean of each sample is determined.</span></p>
<ol>
<li><span style="font-size: medium;">What is the mean of the sampling distribution? {#1}<br /><br /></span></li>
<li><span style="font-size: medium;">What is the standard error of the mean? {#2}<br /></span></li>
</ol>]]></text>
<file name="Question 17.jpeg" encoding="base64">/9j/4AAQSkZJRgABAQAAAQABAAD/2wCEAAkGBhQSERQUExQWFBUWGBwaFxgYGBsYGBgdFxoYHBgbHBoYICYhGBwjGxgaIS8iIycpLCwsGiAyNTAqNSYrLSkBCQoKDgwOGg8PGiwlHyQtLCwvLCwsLCwsLCwsLSwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLP/AABEIAMIBBAMBIgACEQEDEQH/xAAbAAABBQEBAAAAAAAAAAAAAAAEAAIDBQYBB//EAEQQAAECBQIEAwYEBQIEBAcAAAECEQADEiExBEEFIlFhE3GBBjJCkaGxI8HR8AcUUnLhgvEVU2KyFjNDYxckNFSDkqL/xAAaAQACAwEBAAAAAAAAAAAAAAABAwIEBQAG/8QAMREAAgIBAwIDCAICAgMAAAAAAAECEQMSITEEQRMiUQVhcYGRoeHwFLHB0WLxI0JS/9oADAMBAAIRAxEAPwDf8P8ADQvlBLPd394vdncOGvgvaLjxukU2m1xppFIbcB8WUGwT+9jBmm1JWXYNuxHLggEdbkeneEezM2KeNKN/P/BPrcWRtyfYKVNJhpWY60caNjYybY1o40PaE0GwDGhND2jjR1nDWhNDmhNBsIxoTQ5oTR1nUMaE0PaONHWdQxoTQ9oTQbOoY0caJ5YEOmJeBq3DpBWhNEjRwiJWCiOE0OaE0EBGtAIIOCGPrGC9r5qdMuUjSBQnMpIlgqKEJUPeAKgmWQ9mFyrdmj0AiMNr+DleoXMSpSz4lMxUuSk+EwwnxSQAAxUQFElRw1q/URlKNQ5/r4Gh0ElGdye3p2fxKib7STAk6eYsrWv3QtL0jl95cz3EEpd2U7uGDGBOKoC0pVNWlIUkDkSzlKmTWkNu9zflxgwzV8EmrmuRNSUgHxZ4EsCUgAB1ORU5Ty3tc3sBJ05HhqloQqYpJqM53UWqSogKwFEgDAjznVLIqTbpbI9NgjjlvDnvQAvQpc+66Uu91JOwSzXN3F2DdYjUjmPKQkb5DebDvkCLI6hBWJYqKiaVFKQAFdsmkbk3sfOBtXKSCocqkgsSDUFdb4Id4p63w0WkveKTOACqVUkZOAp2sGuTd/SCZWkUsO7EqLtchI+Jh5wHLsMsOm9/TEHaaeUXSpsEsdmBDtt28xCZeqJWPRrFJUEKCkm1IyQxcABrOTsGLmJ+K8PXLnGWukFJYhIcPZsgWIKW+0AI16KwpfM5wQWGb4z2xfeCPHDKuznJw4+IEF7O3TPSINV2OW72Ndw/VTzLBl6KXOTgL5Q5FlBiSQygYUVE3XLBaXOEsDIC1BJLkkgA2BcerwoSljreJB45Pfb7/wCzTyJtU4gpUA4u4YNlrObDzZ8NGr0stADpNjcO93bba5aMbpONTVkFCFFCFqD0hhe4YnPOQSXwOttXw0eIgKez2FnDZwLP22jV9lZtObwtK77qv2v34ZPX4/8Ax3J0g5oTRDrZpSkUkAkgB/2bdf1iZGLt6Fx8949TqV0eceNqGoTQmhzQmg2LGNCaHhMJo6w0RtCaHtCpg2cMaOND2hNHWcMaOND2il9pNWuQEzkkUpLLBPw3JYNc2f0fq4lNRTbG4cTyzUF3LciORluJ+0SVSxcB1EADmCndvqnfqLZEV+l9pFKVUFOQghLqJDAjIwtXfqWMV59XjjXvNHH7KyyTbNy0KI9HNCkgu/8Am/5xM0Wk7MucHCTixscIh7RxoJEY0Joe0caDYBjRymJGjjR1nFP7TSQuQUFvxFJRdNRNRYU9FbuXAZ9owep4ASUS0mYopSitbBApY1BAUwUAVPcjJsbkej8Y1apUlS0IrUG5agl3LWKrPfePPuP6rVISmYssJwNIAQTKBSpZT4gOxD1Neki2Yr58WOa1ZOF6fv5NPosuSPlhRnFcIRLkGbLWKbHm5Qsk0mhTczLZvd5bu1zVolFQUoGkDZiFG5bJYWAOLP2iyk6Fc5JmgiYJT+IQoKWgKu5CrseoffvEuj4PNnLUhAxTUC6Vh1BLhPY5uOsYE14kksUKv7/U9DF6E3kndfYAVMAHMoknLJFuhU198mHzR4fulLsBSLAj9b53iHxVy1LlKZM1JumxHk4OR1xviDJelrFUsKJ3p3YsT3ANn7xTyKUHUixs1sQK09SWUPTf6d4eAegDhgFEMf13jsmcS4UGewI+9/8AMcFRL+8cOB+W0Kt8MknW6LCRxqcEgJlS2AADITsO+8cipVPKVKAUc3sSxYdLYaFA/jxe9L7kNZsPZ+aV8vilDGsAAEqL2yCRdgSCCw849M4UmyhSxfmN3J7v+pjzX2alLqLUlEyxBpAU74y5HN2fpGyla8ypSkyiXTsoAkW2dnAbp5Zs3oZeH1DyS4UX8Sl18PEx6IhWs1gXNZAIVLJFSgoJOyk3sLtzB8QfKnUy9gofI32bbyxGYma8LSSHBBvWFWJIB953DixJ3iWWsqYkjlegAsXJAuAGpa/+0P6X2i/EnKrvf049fkIn0ieOMeyNSZ4pCnscd4kEZuYsqmpIKqWwDcE727fveL3RzAwSNh+Vz9vr0jZ6brY5rXH+TNz9FoVxCCIcf9v384GTqHLP5Ebg3fybfvCKyCz4Jd+l8fPHaL1FWOJhChDWjoVcAZaFVZ4AqUGjjQmh0UfGfaaXKUUBSaw1VTgIqCmLsxuk2cQbBDHLJLTFHfa+cpGkmqQzgDOwcOcHGXa0YLh3GVLRQ6+ZQJEwEkum/MtRNJBUxsf7bCNFxb22KFB5Ylmm1SgRcl8W5WSWLRjp+oT4qloSULUUlFyqtwQpKnslrE09dmYUery+Vxi91yvieo9l9K4RrJHndMl189SZSikgqCqRm34hNSgoADzFnbrEPC+NkzAFAnlCWZnKQUub+thvjMEpWotXzHcU8rLvbtzO3eB9AoLWUzAs0Apl0uC1Q5SU/CzZOwN3LYym51G+D0WhRTbVnpXC9SlCEuKQQOtyXNg2G3PaLaqwOX/OPNdHxpfiIl1BRyzhVlmzmo+rYY7BxutVr6FS0kuacD4iz4A6AlyQI9FgzeJtVUeN9odFommuXbLFoTRxc4BupiGdqwACLu1sG/nvbEPutzKjhlKqRM0JockveOtBsS1WwxoE1WooPXD9s3vb0jn82qpm6t09dxdv1tFJqZylzqq2SoslJtjlVnDqJv5Rm9d18enhtya3SdE5SuVVRZ6rU1ApCDNSoCoMCkAu+SAfQ2jLe1XFwZapmnCFqKVg+JUUolodKlJAcodbBg1dO7RZalaljwklSQ12JdQPKpvN2bsIyHGuHCYqvT+IDIYlSTLRTQAFeISCtgQ6QQoqJVYvEMHtFZZNL0/a2/stvooxSf78wjimknS9KmQBKQrlVMkSUgqcBaioupIZw1IBwSCSQBidVxmYmgBKUMlNkrLhg6VAIUBuVB3y7lzGo4drkJWAuY6/DJqCF/iFVZU1RPgkvmkPgsyYouO8NkVS5smYqYVh5iBK8HwyhIDJBJdRId7vcuSbxzZouVrZ8Frp8dRqQ06eUAFy0lRpLmYuoqWol1H4QcC3TJMPlTAlaJiawSACU2pLZRzPkA7fS46JCVgFiUDFTAqNshzYY7Q9MxSSQTT5thwfyjHyNyk2+TQSSVGnno/mpfIgSlS3dRIJWVXdS2Yk3z0YNvRcV0czTLVLmClaiUkBQJ5QKi4NrEX7wVwDi0pNfjoqSLAMaz0KVAsA7uCHa46RcaPjEtSTWD+IZqKSokpC0OVJfyFwesItxb1IhW9R4MzLqIsDa1/13s0KLyX7OJmAKQpYThyCX6nlsL7QoS80PUZRoeBqEmTKFLTHKVpZgSPjJ2UAlm+7RbT9Vyl8sP6U5Frs3U36fOh9n+LomUoJV+GpSkh2BuAC2RZ7Xz8rjWrdQKWZRDFQ7kl7VP8ALeKE01k35EzjvVEYmFRCVBqgRZyCeYq/6aeUZLkNB8mYlLIpACuapKuXAe96QWGP9wQkrIUyVJTYLsFEEqLNnc2P3g1SwlikFQd6RcjZx0uQbB2A3huHN4WRR/a7/UhkVo6HyQwd3JIAJFrMWtf5RNI1Jdkm5e9OxazE9e2IEWsLUUkuEpsol8gCkdwz+RhgS5FSgbWvkehsnHQc0PneLInB7c+8WlqW5ay+JdewCsi7VXGMv9nvD5mqUk0lwVG4LF+XIzewPfpAstFyQwJsdn7Yv23MdnTS4Uu7pblB2BGXbBjb6T2hJKsnNr8leWKN7Is5WpSVg1XDhiR3L2G4B+URaXidcwJAcAZ6kh9/3c9IptVrgD4dNL2dTBRyLqOcXZ/1N4UFIRU6SC5w7WLXbI/fa7Hq5ZMqxx+ZCXTRUHJ/I0SHZzbta3yjzn2x0pM2cqUpCqUlcwBZKgCAkOlId3dks1y55jTt0cVlzEL5wkAXU4bzBNjHl3EdZOkTlICSVGtKUlj4oUpnUwALA2epsXDmLebLGMHfcV7P6afit8NdvcVGpUVo/ElqSpagpE0glZA95gHCnS5I2VtdwHxmUUrSUlVJwSwD9ux8uly8FkoWFJSkTWBppSRQ5JYKZL3YvbJF3ET6haZkk86UqGbgtS1gfJ+hJMYEsr7nsIY9LTofo9SqZLQmslTgFaQCUggEgnNgerAhswNMWlDpKnIIpAOUqLhgQGKUh3G5ifhetCeVJUlIAcJdlqDguQQ1yQ1xjJDlk81+7LUkqSxJKVWCmLO7GpQDm+4MR2Q2LerdbBXD9eUrQUBIKbCo8psDcFnLgPcB+zxrODcbrKphpFuROSMsE2LAUiw6DFnxaJprAF0pSLFWN3AaxsbdwY1mkHgadRWtKErSGqsXchIFyxBDgb56mLGCeWmoP3/ModfixvlbvYs5uqWFKTMUGsoMp3BBybkWG527wedVypSXqTtkE4LU9AXeMLw3ip8Q+5fLgkCzdAygQGwPz0EjiFQe6TSxNmvb5A2e7tFf+U8cnO3vtT3/AH3FDJ0rVKv8Gx0OprSP3j9m8P1GsQgErUEgbqsL4uYynBePkFMskDIIVchmpDuCXerN4ufaHi3hGSkUVLJssHDZt3OOrRv4eqhkx67+PxPP5+ilHOo1zwVGrnzTMJNiFbgXQ7WtkX6j8hJ06pRK9gxOzgskltier7ejdTxYqICg6g5vY82Lj3Qw27dYESnnoKjgtu2Ce73xHjeryzc5QcnV3vyekw4kop1XwI/aPilIlS5aiJqiGI940jCbggks5YjMV8iamdOQqY58INOHiJQnl5UGpRKVqKid23fAi2WkUqSXwRZRSTnCtnAIt3io4x7Lp8BArMtasAF5bO5cs701AHJ77Dpc0YNJ/vcM8SewHrOIoUua0kyzNFSkhNSUAquWSkOgcxd3vk3TEPF5MqYmWJAYSwEqUxSpgo3Lq5klJScOOoeAdXqly1OzKCVSVnqkikpY9g0ReJzJSr/1VgLIsRVyuNgwD36Rf3e67nLHXBHqdCuSkKVYKUQlwyi13ockOCDc4I6w3h8xyVLmy5V/iPMbPZIyLtnrFlMvJXKlkGShylJDUqJS5BNyOWzt76odw3T6dIQiYE85qM0BQUlkkpS5skKUyf8AUO0cpp/EhJPkPlezktXhKmEqlrQVAySlJSokhBWCCOZjZ3DH0D0Xs9O09QSl/EBBIUKWvZ7lJy1gRfvAk7iE1XiokSwAo1rCQCnlvb+mkJDtsi8LhHGZ1K0TUqKZoCErCjVyviogEgnJ6FzvEZKbjtx6HRTjLdmhn8clFh4K+VITaeoY/tSzh29IUUapC0khEta07G5PkSAxPl/mFCPD9BmlfrZp+CaCWV8xEtYJC0G/WmlTFndJcHYg7QYZ4SlIlIJSffBSAQM1XyDhmz9IuGaqXMKJviNMUCDUCq1I5cBi5BcWJMHydcoVbMQUpxk818M6eg2zvSmm5bi43yyfS66sKJqdgpnDGl33zj6ecOkT0rUFnyBwb3NhnGT1NrRTpmVKSgOSsf0sxAa7Dm97NtzFnwuUU2Jamyjv8IJuXfeIyUl5mtzpRik2OnmkpAJCSz1NgMQCAMEF3y4HZ2aSW3LbBLhs3FnsXbIHSOrlVKssCoEm5YG7Ox2/XMTzXSU4LliQWAFqXa3+4tEHlcmkuSKVKiafKJsFkFvlax69IH/mQAQFVXpJc5ta/MDvbr5xLptQSCGAAzk5zgPgg+sR6WWcWoLOwHMcA9n69oEcjiCuzIpz0qVS5CaR33TfJY5Jii1uvWXljLsXwbcoIdi4uPKNLO0oAUorADP0Tv2w4/2d4x5mgKmUmsFQJJDJBJez3TjLixPnGhik5eZljAk3wXn/ABaTp9MoTEgzFDAJSwKgMkgMOlWwjJannQtallSi9ASyWa9TK62dID3IYZh/tJLXNS6QVCWQVEJcjopVu7PjJgHh3EPESpFkKJdLcouQCnPxE2d2PnGn4sp40vQfDGozbT3fI7gmnBSpS1MpJfmIukO4Znzm9hntDqdZUMWpGOgtvvytdxc2xEGpmqQSpJcWu1iNmU3QQ0adRQSFWayWvZ6g2bHdr9oXW9s0Yc+YP0WjUJZUliAalJ/qBxZLtkWtYkQBpNUUub1Vd8ObM+Hvv9Iu9FLSQRK5WFguwNnUCVJFQBBBBBwcxWollACpgs6gEgAv6ZYkDOw7h+1cpk4O3uWujnqK/GmoCipgkB0jo5ABKmtYi+9nifj+uKpstpopMtiHAUhqS5ALhWcgAgAgXgOUCqWosxF04ZyXYuVAC3+zwNp0qUslmUfeexcP0v29T0tKOaUYteoqWGMpa/Q0OhSmXLcoSSBZVN3OHe/dsNHNNq1Ncg0gsHASMtgkpb02sYqOIz6UuGNRIDlgSLuB/bY+exhS5xKUpUXK1WSAHSGBBbHxGKLg936iZY//AGZtPZnh5WtCrKpIUTuyr2IbdvrDvafXomTkJmSx+GGUip1Mp2NCbjCb9xDtBxFGnkELKlLSE2AUDZg5s1u7u0VGvnKmT0qmKRzMAoO5BsPR7+Q7GLkZwj0qxLeU2399jI0SydR4kuIrb8A+o4f4b0TnSSWsQUtdLl7jOOnyI4WVKNdeRe2e4t07RBxLQVDw00hbkWINTEAMcjOO94B4RxFyJaUFSUkhaipIsHcJSblWLdzGVPG3FruuS/quNmi1mlVNSooUylBqlAEAf1EWuMejd4yXEeJ1kMCqlAQsof8AEKTStySSACzOwvGq0Os/BdNmpISSkEkqp2xg2yPOMj7a8QPiBMpVQNlDlpSQLhTXq+WHAgdHF63BoTwA8Tn8wJShIYUpBBo/qAAw5N3yz2gGRMJVcBIY3Z3YFsY/zAvjPS7McX+3Vj94JSpt2b+q7xrOOlUQthGncg0gFwxuW+Qy3QvE8makJpUSCX5gAwGwA9BkwH/M0A7K6HPyiz4dxAhBR4SFleSQ6kMzUqcX+mYVNOuAX2CtLIloNZZSSTy3GR13F27vEmr1OnKUVIlpSDygVOKviUXuL4xaKpPEFIDcrC5Bc4LjrvEmsnIKgHvZiRSbjDOcG2YR4crt38g+UgHFtThCihIsAlSkpLWqABGcx2JDw6YcKQBtkn1bBd7QoZqh7hdfEu+Hy1UplywlBUCAtThqWX7xcJct5FtovZ6lIlJMtKywpmOqpy5IAewDVG3Q9Im4epC5TBSSmpgAgJUQwse4AJy9IOwiXANQqQAyim6SxL4bcHHW4e0ZuTJb44Ocq2K3RyJgmJWQAkt8RrBZgBhhzXpFwdwYtkyS7hqhdyBcte9mJJJdnZnhs6lgtA5UhyzBIYikJIY2HdrA2aHaCYVkglKQ4cnmUMi5tUC+bWAtmIznq54OttWP8MO4pWp+a5JBZyWAwfyvAcxTTXpFhY3cuBYNlmy+2dzKmQpIpctU+L7sXJtuds46tOmQC39RBJACSwIBZzfo5694i3GgpU+R2nmueiQGD9XLXF/M4tB6aTZbCwycvgsPX6QBJlVn3gU2F7WTcHorYkjt1vb6CSkgKeoZPT65Fop5pUrI5JJEE6WyVs9VPQ7Dq2cf4jH8Q4d4ICiqsreol+l3Ni31zeNrqZb4ApubBg5NyxOGvGI9qeIsspZQISHBL5IPugkEgg3yekXeildxiM6eTsE4ZxALeWeVABKSKiocpqNSBdzb1sDFCqQpGpFJpAXZmsLsz7bXzHJ8gEhJBSLuSS4YG1vl6tEun0UqaspKyEJAFyKyAb0gEvYlrfa+7BVuWoVdNHeLCpSpiTy1XKbAF7OBg375ERrmKV4ZJBAINyolm5hcMQeoB90sYh4iFoWU00JakO5qSlQIOOqU7DGzmJzLNP4dJCUip2SQU8hLlVzzA9qjZg5mlsXY9i0/mmJJ5anJ+HBNw9hc/MdbQCicSTUshhytYBgGNs3t88PEEnVlQmOQ5fe1rqwL2bf6GBpNUw0JwXFgws59BC1HdlnSki4QCJaXIUJh5ebcZNi4BZts2eOIQCSCaC5cDa7qHYWA+e0dWpctKEsklBsXBqDhyLNm3qPUfTTzWRSTubOxsLsMX+sLrkK3ZNqxzEIVgHl2D2+bkdYr065KQpRNwxlBNgkuX5RZ2J8gbQbMlI98MC5e5Ys3Ts+GZrZtUaeQPECVEJSckO9ru2x/SGQSorZEaYaiaJSkzEkApBNJJBCmIZV2GPPyifxCyKvdZQSsKSo2wHT+b2FoqjxdcpbFSpqUt4dSrU3yn4S1nZ7dGaQazxCBS3W4D9SzsIrzg+exWSDNQRWEpCg7EEEh3tYkud9+sG8P9n1zCozuVJLpCXSWDB+XJ7HdyG2q1pqLXLmw3GQwfO8W/DZq5aACVdiVXS7OAFbG4ivNyUfK9yGRNrY7PlHSB0qlqol0ipISo2sagXe4cMbG18Z3VcZQJQCSVKoY+GmhIUXqNSuYgEJItcuSTtf8WmlSAlJMwqHMLJKgTcVHA+v1in4nwDTyaaVqmAtz/C+9hk9tm9IbgktnPn4ftFeSa2Rm1TFrBqIBtcOVG2LDl3v2MOlzyEmtIL+4Bn/qJU9sAAMQX23LmTVMySyR8ItlndQ957Z/KIV2uX7t9hGhrXoJeyCtFoZs+WpUtMxaJCSqgIJCXLcoAcl8s4FW1zA3iGU5Vym9ibg+XW30g/hq6PdUUmxN3CgUghXRw4BDOC+LtwaZEwgTAHJJdQCSSdgo3Pr6NCpTV01sGN7kGjmKmIcJBDsolTG/3F+sG6aaUJB5Spip3YggbEsPnn7yf8Fk1USp00ArKaKQyaSygVKUQSGOwFvWIdfwpUl5KUeKlICwpRS6kquCkVF1WNkuzQpuMnS/fqdQ5M5IfJck2UTm+0KIpekmKDy9LNUMGlBIBGQ/UR2IaV+tHfQ3fs7KSlNFipQNSSKrbKAUGA2qxtkwRNRTiYgJYBQIDqKAAEuoi3Lnv2grR6agJUAXIJNIPUkgFV8nfIBttEWu0zKRMSEA1AcyeRFiHJABSXtuehjH16pOnsIk7lYxSVLlGgkzAzpUXIfq4FyO24itExUqaArJCiKSUJDvYA4IPn27DaDipmCcC2XJQbhSibPuBs74zmHmXWVEPL6MXS6sEucsc7QxQcG4stQ434L/AIaozLqqUpSSxJAwNncNhujeh4mWmgPSAM9uvoesB+CEoSVLWFkgKAVekEmwFtxft6wToJIZdWSBSbh3y526MejwjJ5W5WLrlhqpIJAcAW7ggG2/Y27w3V6wpSGIVe252Z9z6QyZpwkJUsHmDYcPfFvIeTw3R8OdRUyEk8wBNrggeWCT3EV9uZPYh5Vu+wps/mQFTQkkPSQDbuAXAfchr9YxXtoZdaFBRJm2PMDyhyDy9iGvjyMF8e4GuXSJqvEWp/xKiZaTckMQSkAPbDN0MUGt4YqWoIWkcoJDFJBOxBcdrZA842ekxQi1NSG4Y6pKmV0oBLonTCkoUxpUFLUblwRUlrFz1Ih000FrkXBBcE2pANJGHBbzBGYj1alJmJCyzNZrN1xcd7wTqpIlIlzUuq4BBSKSRV1d/duGOT5Rr/AuQena7JDxL8dHNNTLpAFSjU1JIZrAVElPp3h02WmUuZLmBLqIUgkgrD4uFFnCrk3Ni7CKzS8WJWsEIAUpwWZiTm1yACRb5WDaHU6olCkpXW+aXNaQ2D5gkf6upjpbbMs45N01/oHNKwVIKZaRYlxck3BTZ3S5tAej0lS1YCg1IZgu+CbEEjBGQDiLZU1JliYUg2BIIAGAlJYYYBVJOW2aANNNouwYD3g1/Mbm++zwu9h0XJrfYfUVqEtTigG9xUo3dgLXBz2Foh1WkUFlANKmqa9QPf8Aptt02BggMPxDYqAarBKblQe5FhcPmwMN1a0KmWSAqzk8r5+bi/ywYinTD5ismcgUFZDsH5tnBGG3PW9y0BpVzOM/T67bRNxRxMUlmpYG3TOLAXtszRFI0tRCRd7ZGGN93FgHsz/OwltZXy5Etix8Ws2YPch3D4s+Pt5RJLUkMb1DO4cH6+UQI0RQtSZiFBne55DgHlsbhvUYg1MspFkmlQuo2JIIfJcByNg8V5qivr7B6dUkpSrK1F6Ug4bpdm3ZrGOo4knxH8FAcMklwEhQTfo3LnvEmm4kFVEgkIBLJAu7gVKOD/p+8Us7i82ZMoVKAqUFOFBrpd3xgk+aiIRHG5X/ALIymk6aNQrhswynSohYICnLNhrZI5izdcRm9alIJrNR3Ybvd2Fr7bRZaGfS6VhDki6DUCk4Cqi1hfbGbtAnGBLUpCkpACySQVBgzWuktSWsbWs0DHFqVMFumQEy0yypIJLZKRSl/Iu7Pt5s8Ucqe4DKKqlMMfRuwJvE1aVEqJaonkBBSkffq7mGaCQgqFKwU7OQGcsRcbYaNBQUbKb1zrcLlziqW9JNJBSkC6mOC1z136Fo0fAtTWJaFSkTJilAIWpPiLQUupTgEuopD7MwN2jKonS0y5gpUVOzuCG2YBi9iHfHnDZupC1BSJZkpSzD4idj2L9evyhPApLfgV4leU3HE9fKMlZKUhRmpKKAErW4dRURhLdQz3HSKufqkIQrwzeYCVCkmkklIckirluO5+Wc0/EKiUupQJBJJtYZ6PfJvmLCUohNTh+irsH7EXbrFXwPD5H6kXulnFaQfESnYBTPbraFGZUtS7pdIuwSaRk7Qoi+n/5fY7xX2R6sOMSzMCA9QWApJcLAKa3SGdwpr/XEE6fXpALVcwPMpmVVS4OWJcC97xBxdLqlLqCEVOCSVJJZgE25bEMxu+IsAEpJZTVuCC7F2GTgW67Y3jBbVJxT/JTTT5K3ScHQJgIQg5epIYA4AwatgbwHr+GumYZJIVcEG5yS7ncWYeXra6grBUSiySxUqwKqsAsHL7YuY5r1LCXlJCQHVQopZQF3flbLbD5Q+LmmtQ5T3szmg4asrcs5pBUX5Lhy79bdsPvF1o9Ipa7msCzJuABcdmbfvEOh0SVpAVM5getiGFg/vXI3+0EAzJRDBNIwKqQS7dOXG3RhiIZJuTraxs5lnLQPDKV1EHJ6N0GBfztHESUg8iQGG97MzgNa3TrAOvmKWtNKS17KbLubm3TzbtEsnWrlpYoJ5qXcWJy5LWs2126xU0OtuX2K7VKwmZpyQLXGSR/h7v8ASMF7X+Ehc1VbqWkFIuAkppHKym7nqUXZ77Kdx+UULUV1JQz0qJmEktZLAlILYd726+W8T414y1F1FgzqY9dwzi5b88xqezcWSM22qQzFOrbZXpm1lPiqNLGnKvoCLer/AEa60vFUrAlzF1JsllSwlKgFEkU4BYJYhi7C4jPCdLoIWlQPwrRkedRpbOxMRzeKChPMlRSGAShicmpRPvKu3cAR6Pw21sWMXV4rqa+ZPNkMtVLln5Wsz2JJb7APtFrppiqDMmAuD0YqCiGKlE2D2t/mKzhuoTMmIBqIUpicKI3uQQBv2g3imhUCkUNSCHCuU9CCqwe9rE9IhJdmacMkVvF7DZ0tIJpU53Ia57Hfe/3iw8MolutRA+JFISU2NQZTHazf9TYvnJ7FO4NsYI3w0dGsUrJJVuo+8fXy+cDRsNeRt0GfzjlQQpVNgkA3NLBOz5Yt5wXpdV4aApChUvlISUnZiSmnIfci5Gbw6bwehImgqCGBNqSwYAgEvl8G3o0QS0+LNC0pKi5KrAOAbOAKQSLMIjs1sG75I+L6GiVLXuolKr/02ZnN7G+8E8L9njMpKJlMzKgQQkYsS1iCQ6bkghhEWp1kmZNShbCWlLBSXUSojfNYCiemC3UxT+IqvQQlKXApFLsQxUxuSwNyfqYl5qopZJJvY0GilTanXNTNp+EuhIODc2Iset8C8SL0alzApC5QckUmrdLOkJJfHrfLNGXRxVRcFTk5DuCepG5F9ocdaGuxSwsbgkAsSDnyhDxSvcS2nwy6EpZlrIdT8qnDJASxBG1mYWeKcymPNbrt9ohm65TM6iNgPdz8hDDOOLOc+n7Pzhig0QU2m0ixkcTodSXB2UDl9vr9TEGsUlSKkrAIyFFrAJcAH3rrG5J6dRJFiAVUpti35W84IXwiWsBQUoTbYpUljbYghz1cgDB2koxjKyEpzcaRXnhykEVJmAL9w0UuXsS55UAXJuxaxgfUcPCFe/U+Sl3cu+c+feLscQTQELX4aUkczVHJpLC5Ick+e5aMxN1gUsuc3e/54MWsblOynkWPHWp7lyVgqJYD1fP5nLQ7xrkpfOVdLtvnEVmmuWrSHw5YDza8WEmo0IKEsHTUAHXkmog3x9GiE41yGM9S8pGvUsNlrJfluzWsMZv6CC9HrFKupNIDsD9CYHTowkuWLC5fHZohnzDUwCm8i77RFqM9l9QeZO2WE6eX/wAwo5L0trpCj1cwoTcVsdTZ6jI4qZsuYhTlPMyaCKEgcoAYFsOzbl2sLHT8RRKQhU4plGYCyAy6RdgoM4AYWu1gTiAdQNQpaJksLcBiFo52UpwhRUWUM3FxvmJOJaGSoJUEJFAblXSqkFyWwoAhaSLx51xhLy1Sfo+GLUKW4FxHi6paqipRlk73SamUxCkuR71iHbfrEjVS5swKlSSmaoDmKyWqsUAKelqU2Ty33OHaabJQSmdTTQ5a6aSkkMLczdj5mKyR/LyZx8Sd+GCD4gUwU6eUuOoG2WG0OUdmop8dr3+g9JI0uj0JCKiQThTH3aviYgFIGCB0Z+nZGglqIeaUmxIHuElwLFg5AP1MVeh1kmudKTqFGXYoFVlJIdRqU7hypsAtBWo4dJVLE/xFLBCiVE1DJOQDZ3itOEk6d/T/AGDvuHo4xpwtQrKagA55Qpn90DGPrBsviMilYqFJUUkHdkvdnuyXBVc2baKKXpNGu3jJBCjWmocpS6DWDdqiB5kNkRn+L8b0WhTL8NK53/McusOlTuJnxBYAIUBTzbs04dHHLLStV/vcVkqu+wb7Xa3RyJAVJQhS5/MSoqEykgMvrSelt2Yho84mzHFaDksQBtnD81gPnFrxHVyJsz8EMlg6jypU6RzutRKCVVBjYBIId4qablSgSgcgUn3X5gku101knZ8R6PpcPhxp237yLk0qRJOlFQCqhZgq722ZwAAGxlz3gR0mwG5d7+kWa+BK/CdTVFnNgliA4AN/qC7wRrOHJkugziWaqlFkhKmLzHZJ5hYhzyg5h6muB8dEXb3YFLJQZawRc1AuGBcNd2Dcp2aLfScfQtK5c1iklLZdnuX5gkjLkH1ilHDJXjpRLCvD8ElzZRaYpNd2D7AFti2Ik1ssLN5dLWJSsqClUpdVJDgBKC+17MzR0scXyy3j62T4gKbLSuayGp22bBJuw7ekSeChAFd+YAlCh36jNif2IClqAAYnyDBxkPe7eUOkTVKBLh7pFSQxcXAfKmO18YiOll3+RFK3yXyeLI8BaFcoSm0ykLUol2uWIBBYEbbxSabULkqetgQHoIJY92NJ9Hv3g6XpQqVQlRD3PiOlDCwIKUhRNSrOCHgnQcGkrTLJrlkhlcil7k1PYJ5AcA5iK0QRTy9U5cbGb1OrGbjrbfZt/neC5epV4ASEpISoGp2LK2L5tjyPdyZyZcoTUzA3IooZgSFlkFzhxghmy2xAShdIZKkKXSFODSrmT4bEuSq4d1Ni9yBYUVJFGfUyU7vsSTV81YZLi++c+m33MNWe2Nv0cxpNH7B2WpRrZqdqWpqSsEgBVxgkM+S4jk7gsoI5ZSlELZ1WSkuaXBuoDDEhyLku8V/Fx3SYdbldFCElIpUCAC2M2D32+sN1SiQkgBwwJ7WAH0875izPDFkJSgEkWdTlQpFLY5U2OAMXxas1+lVLJ9xSk/0F2d8u3+PUROLTewHxuckL5wkuAosMluotl/pbzibXaeWVcqhTbBqAOTekAs+D6FoCOpWiXUoEEUqYMQHIarqCHx+rRSVoWoJUbEudi/m+PtDVjfIp5ork5qzQzKCle9cvYFmYJsS7upgw2eKzUywHcUqdykhmfAA6EEHaLadxkylPKskgEOAp2BSl0qAcM1iSBbMUkyeVLKrIJNmslOzDoAPtFrHGkZ2fJqZ3SaqhdVNXQHrFj/xT8RLuWflslKSTi7O1xeAjJUhQL02BByzgkY8ogCKjuX/OJOEZO2QhklBUjScK1UxaajRckkXdgB7ods9YI0Mxc1ZXS4FhzABgSAWG/vG7bRmkyJiADhK3S79c/aDtPyGyrMzpHc3LZycxVnhW7Vbl7FnlJJO9uTWqnoSwIct5j7WhRRy1zlB0pKhgEIKsdwIUUf43vLnir0PQtJxujlTUVqFc1PwcswHlBG4cbXBsYz/tTqp8ympNKULUtAZgCouRdqiLc4AJvZhBM/xJI8dXxBiXBBywt3MCD2o8UEGV4ga5Azbbtb6QjHj0y1xjZT1NKir1OtWZY2KgGuXO1+h/QxTamapcxKWTyJyEiq4JZRyd89fJrLXcWKiQmWUkMLO7jdvTaHcJkzZkvWTqCUIlgrJYBN7BiHVuwDd7WjSxRpXVEJZWVuknBJnVOaQhvnv0At8u8WPs1xRfjBlKRU907Am9twSR1d4pdLOeYtTJAtYkDAswJc42/SC9JxAy5gmCxQoKDEO6SFDzYgQzJBNNNEI5ZXd+odN4sk6haQ9DMksUGqzFQKnSxcMCMDygHiOpUhRDG5JJVc8xJJJ3cue7xJxDjKFEmVJCFFiovv0Hr9oqNTOUtRKstBhC3dUGWV1Vm24VxrTpl+HMuTyjcVC6VqAp5XYEC7AZIiPjx082X4UqX4UxE0XKeQ1kEvMUagbdxsBGQl6hQINJLRbazi6J0sBcqlYUmlQ//pz6C3b5K8HTPUr+o559UK/wa/hCkrEupHuv2AASokBhfp1B7xq+HrlCUSZaSxPRybuXsCbOM4yWv5vw7jcwTUlMqtgAaRUS4cW3JD/MxqNL7TTFlJ/lZolhnFL3drti7GM/PgnaaW3xJ+ImUk7hyZuvm+AklIly5qkKUylFZSVgkqIFi7EjGMQefZaualNRSgBiVMbud3INy3l52fwniaBxPWliykykpaWs2CA7sl04ypouNTxtCXJStqv+XM77U9oOWWWMkorsv6DizyS+pT+0HDRLkkqN3WsYv4cpyDS11UY2sWYRTexUtU8KARYzMPcBkOk4qJTYFuXmOWiy9oOOy1ypiFGbVQtKEGVMF1oIAunr1iu9i+NafTSFI1ClJUqYVJFKyKSlKSRSDcqSR/phsVk8B7PV8CL6h61fBu5XC5cpKqUqu6QFFSzSQSSkkhiFEux63LXl0SzJkJuhRoCVFJCVKKmyoXDZDDaM3qvb3TBISCpbHFKwejXTb5xSav25UpkolMlLAlRUV2Ocfd4oLpM8+U+e4Xli3Zb+1WjTL0mooYlSWUQACwpABIAr9SezRNx3VJTppdJCgVSCXu7TJRx5vgDeMlx/2lRNkrSHqUAGuB9r2AzAHEOJBaEtOuKOVl2Yhy5AFm2jRx9PNxjr7O/6EzyLU/h/s9BHGApYKlC5VZ7AEFgXPUkeQMBp4wKV8wYF0hmDBXU7s20Yg6hKlVfzLF/6F3udhj/McmTEKUxn5yfDV/2wF0SX/Q2Oarr+y6m+0zzTQySQxZZYgK9HftfcNAfHEoGndB5gtBdXvGzN3F3a9u0AyOE6dTPrG/8AwzDSXxyuX9PWOa3h0ildGr8SkFgZakVHYAEvfuLRcjihFqr+jEvJOUWn/YdJCTpZ5Ukv4SGJXlQrJLE9BgWscvA0+cgpUshmFgDUQ46sN75e7bQlcM0v8oCNWVTmKjLEmZS5Sn8OshnBHvO14FmaWTQll5ByhQbDgFi5GH2hiS9/Iq3L049R+jlpqZKQSQAx7hzuwvZz+giSYqUwWyQVJduowzC23nDpOg04SXmPkkPSbPYunfPXbe4s3QyRcK6YBPXv+2jtm+41alGvKPm6gLXLKqQEpQkpZV2CgQwH36iBp+oCg1kstZYBmcuOjt9IOmzZfhcizyrlr9xI910mxVze8/p3sPqdNKZSyqYVlRJdKAnm3ACty+LROLQmUW32BVTi4TW4fy27i0MXriPdsQXfOw/OH+HL7n0/z5RBqkAEMCPRokqbBNSjG0y/0c2WpAKlsegTCincDFv32jkIeFN9y0pyrlG7T/DTXf8ALlJs71h8PekZ+kEp/hzqyGUJQIJYqml85LINz3Oxj0ZaARlz0v8AXtEa6sOelxsXP6xgP2lP0QnXRgT/AArnlgZkhIYOUqmLJO9iAB9I0HBPYTwdLqpC5qT/ADFqkjAS2Kr3+jjO9rPE1R+FI2L775wSfqYo+KeISoK1ASc2mAB93AHR4nHrcku4HNUVsr+D6SR/86lnv+Gz7WdWfntaGaj+EAONag/3I+eMOXgTUT54T/8AUhWw/EAttf8AOBZ/F9S1pw8nS9m+eItLNnlxJfvyBrQd/wDBuaSR/NSe2em/Qd4D1H8H9QPdmSVY/wDUL9/gYfP5xCn2o1Yd5hI8gRjsOj/KJf8AxbqRmakAXcpO4wzXt23tE9fVLuv35Hak+wOf4W6prBDj/wBxLEYcbxCv+F+rT/yb/wDup87jyg//AMbahyagof2quPkBSfKBl+2k8EuUqBN03TjOzp+UTWTqvcBtA6v4Yatj/wCUQN/ETT9d+3aIj/DTU9ZAIdwZyAbZgqd7SeIkhSAB/ep3FTEWD5+0VJ1TuAMg2Ictl7mHRnn719Pyd5e5YJ/hlPu8zTBsvN/xHFfwy1A+OQfKan5Xa7feK6RSVBmT05R8QYB/X6Q5ejcu0u/Yg2sWBck+XzxEtWX/AOvt+QrT6BR/h3qrAIlk9pqSfIgq6EYHSHT/AGP1y0oCkAplilH4koMHKj8XUnMV503MAoJDgNcb+R7xKpCmYrTm4fBFmYH/ABB1ZPVfT8hWn0OTPY3VAP4Rb++WS++FdTEMz2Z1A/8ATPzH3xEkyQ6QxSA7evqO4iJ2bLte2XJJNtuoxElKfqvp+QWgSZwaaMy1tn3T+nWGK0K05BHmL9rZg+osTZ7Piw233iNaySG7N+z3hinIi6XAF/KqIwfrDf5M922NJaClIO1/3a2B1t1hwK2uLP1LX9YlqIXYIvTK+WDiGGQc42vBsxJUBtmwJbAcgbXER0uX/X6s5+UHUdQIyurerY2v5YhFJbMFKJ3GIjKFfLt+7wdRGiEAj4m2sf0h/jqCqiaizc4qszfE+1hElagGBt5AHeGpcX/QQbO3EviMwqepznA+zRJN4pNOSnsRLQFbYVS+0Rr1SjkksG9Onl2jn8wQLfb/ABaOr3HW/UadXMJqKiT1Of8AMMnLKjzK+bw8zH2+g/SGGb2HygoDtrdkiZxAsR35f1hQk65Qsyf/ANE/pCgb+h1+89TR/EA3eWEvccxL7NZPUi9hYw6T7fTZhNUsEiwPNjYuLs3beMXMVUkpqKr5cpAFmJB5QCS/WJEaxIHKKVsBUDf+7H76Rjfw8XoTUjYr9uWUPEllILe6p7k9wLd77RIr2ylkt4anJNLqDgJc3ZgMRhlAAFSXZyfeFSQ4ZwGy+R8hEUlQc1EjYMLglvhcWPTo7XgfwMPZHal3Nx/x+QUupJDhr1FxluVIJBfINrXEVf8AP6IoKDUlYFlIQbefOKgz7dM7ZuaqlRClKOAQOnRnsRhtoU7VJOHAwkZAD4fPrDI9Mo8Ng1o1uk1eipZQV6gAKa17OfU2gMydCslRmqpSGQCgpAZrOggh+p9IoJa0lFgHcuovYNYXLN84X8sLFgQpOQWHfO+bf7RJYa4kztQbqdOgAkTQbClrOxsCSHLAnaBjozzcqqgAXCgrNrgD6gnyhkmoj8MFNiTuwLPdnA7XewiESiywKlGzlINJvvvfYbmHRTXc6/U7QopLgABrAYBHvMLlgPi69yYjPMQ5BHS2B0/e8TeMtKQkFQIJfmuMf03GN37QpKQosEup2USXdyzh2b/V19InuR3ZHqF1Pcqck3PVo7LmkhkpDs5Z3sCHfZgT3h0kJSQ7HNyH6gcvxXA6iJ9PxRUtKghS0u7NgORexyB0fJgO62JX7wQAizNVYJCbncgAC2Nto5LItYh2wz9i7WBcY/SLSVxbUFJdamy66aQ1gGVuSwbO+xh8zVrBpVM5UpLJ5TuXIYDcuzO0DVL0+/4JU2VEyfzMGIewIfo1zfoYSgzuQ+GNTjsbBj8sQcNQbgLSxDBQTnrYc1z2gOlIyyhkMSCTYKAJDt2++YkgbkSEh7/n8/8AENJb8ixvf6Q9RBJZwNgHP3P0jsqS7cpO1t+kEj7ji19jY3cNc4ZPlHJTEnJ6MHfFj0Gbh9oaQX942Zgf3dmGYdLlqJABYnBwPnB2JWdE4AdR55br1EQTNQ+LQVO0zWVUCHsSNth1tvEUqUwUqw2YgkmrpZnAvsekcqC2+AUzI4ldwD52z94IMvqB5t+zCVLAwL+X6xPUgAqkpaxP7y9/yhqZJL2AbJOBBaynZA7EkuO9rP5vDk0uAQ3dyX8g3pEtZ2wGzZH13joEtnVWD0AHe9zeLWTJQpTJ5jthIHcHc+kF6XhWluJ01aL4Q1u7sYW8yXKYaKCSZYZ0LV152c9mTbbLvEw1EhJcyCejlRFs/EHjVDgHDWtqlhTYUwF85HyJZ72h6fYrTqW6ZyJkoAFhNAmF7gsLdmFw3zW+px97X1D4b9xnkcY0/wD9pL9SqFF3qPYSZUfDky1Ic0kz7s5Z+7MfWOQNeJ9/v+Q6X6fYi1o/7R9U3gXQB1ywbg2IOCHweohQojHkUyHTKZyLWP8A2mGpDkvfljkKCK7EuolgSUlg9ZDtfEc1wpWkJsChLtZ3Z3aFCiXYkG8LSPHSNqRb/Q/3vEvDg85D3sc/2mFChTGR4+YHMutb/wBBP1RAQmHmDluj947CicOAPkZLL5vaC9IgHxHDtKUQ+xdN/OFCiXcgc1qQEy2DOly1nuYl4HKBmBwDnIf+mFCgImuTp5l6iq93ve4JAPytDtKokXLsmz3a20KFA7ocgniElPiSQwZlWa28B0gqIIe5z5mOQoDBkIZeH3vf5xcaaSmnThgyvetm6c9YUKBPg6JW8RzM7LYdhew7WEQSEjpChQY8AfJDN+H1h8xPIj/V9CGhQoZ2ARJLs/QRK/K+94UKAwogKjUL9ImPuev5woUc+wV3OyR/5n9ivyjhLSnFjWRboybeVz84UKCggiBcxoOI6dLnlGBsN0peFCiGXlEFwQyCyEgWttChQoagn//Z</file>    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <wirissubquestions>
        <wirissubquestion>
            <![CDATA[{1:SA:=\#m}]]>
        </wirissubquestion>
        <wirissubquestion>
            <![CDATA[{1:SA:=\#se}]]>
        </wirissubquestion>
    </wirissubquestions>
    <wirisquestion>
<![CDATA[<question><wirisCasSession>&lt;session lang=&#34;en&#34; version=&#34;2.0&#34;&#62;&lt;library closed=&#34;false&#34;&#62;&lt;mtext style=&#34;color:#ffc800&#34; xml:lang=&#34;en&#34;&#62;variables&lt;/mtext&#62;&lt;group&#62;&lt;command&#62;&lt;input&#62;&lt;math xmlns=&#34;http://www.w3.org/1998/Math/MathML&#34;&#62;&lt;mi&#62;m&lt;/mi&#62;&lt;mo&#62;=&lt;/mo&#62;&lt;mi&#62;random&lt;/mi&#62;&lt;mo&#62;(&lt;/mo&#62;&lt;mn&#62;86&lt;/mn&#62;&lt;mo&#62;.&lt;/mo&#62;&lt;mn&#62;5&lt;/mn&#62;&lt;mo&#62;.&lt;/mo&#62;&lt;mo&#62;.&lt;/mo&#62;&lt;mn&#62;88&lt;/mn&#62;&lt;mo&#62;.&lt;/mo&#62;&lt;mn&#62;5&lt;/mn&#62;&lt;mo&#62;)&lt;/mo&#62;&lt;/math&#62;&lt;/input&#62;&lt;/command&#62;&lt;command&#62;&lt;input&#62;&lt;math xmlns=&#34;http://www.w3.org/1998/Math/MathML&#34;&#62;&lt;mi&#62;sd&lt;/mi&#62;&lt;mo&#62;=&lt;/mo&#62;&lt;mi&#62;random&lt;/mi&#62;&lt;mo&#62;(&lt;/mo&#62;&lt;mn&#62;5&lt;/mn&#62;&lt;mo&#62;.&lt;/mo&#62;&lt;mn&#62;75&lt;/mn&#62;&lt;mo&#62;.&lt;/mo&#62;&lt;mo&#62;.&lt;/mo&#62;&lt;mn&#62;6&lt;/mn&#62;&lt;mo&#62;.&lt;/mo&#62;&lt;mn&#62;50&lt;/mn&#62;&lt;mo&#62;)&lt;/mo&#62;&lt;/math&#62;&lt;/input&#62;&lt;/command&#62;&lt;command&#62;&lt;input&#62;&lt;math xmlns=&#34;http://www.w3.org/1998/Math/MathML&#34;&#62;&lt;mi&#62;n&lt;/mi&#62;&lt;mo&#62;=&lt;/mo&#62;&lt;mi&#62;random&lt;/mi&#62;&lt;mo&#62;(&lt;/mo&#62;&lt;mn&#62;10&lt;/mn&#62;&lt;mo&#62;.&lt;/mo&#62;&lt;mo&#62;.&lt;/mo&#62;&lt;mn&#62;15&lt;/mn&#62;&lt;mo&#62;)&lt;/mo&#62;&lt;/math&#62;&lt;/input&#62;&lt;/command&#62;&lt;command&#62;&lt;input&#62;&lt;math xmlns=&#34;http://www.w3.org/1998/Math/MathML&#34;&#62;&lt;mi&#62;se&lt;/mi&#62;&lt;mo&#62;=&lt;/mo&#62;&lt;mfrac&#62;&lt;mi&#62;sd&lt;/mi&#62;&lt;msqrt&#62;&lt;mi&#62;n&lt;/mi&#62;&lt;/msqrt&#62;&lt;/mfrac&#62;&lt;/math&#62;&lt;/input&#62;&lt;/command&#62;&lt;/group&#62;&lt;/library&#62;&lt;group&#62;&lt;command&#62;&lt;input&#62;&lt;math xmlns=&#34;http://www.w3.org/1998/Math/MathML&#34;&#62;&lt;mi&#62;se&lt;/mi&#62;&lt;/math&#62;&lt;/input&#62;&lt;output&#62;&lt;math xmlns=&#34;http://www.w3.org/1998/Math/MathML&#34;&#62;&lt;mn&#62;1.5368&lt;/mn&#62;&lt;/math&#62;&lt;/output&#62;&lt;/command&#62;&lt;/group&#62;&lt;group&#62;&lt;command&#62;&lt;input&#62;&lt;math xmlns=&#34;http://www.w3.org/1998/Math/MathML&#34;/&#62;&lt;/input&#62;&lt;/command&#62;&lt;/group&#62;&lt;/session&#62;</wirisCasSession><correctAnswers><correctAnswer></correctAnswer></correctAnswers><options><option name="precision">3</option><option name="implicit_times_operator">false</option><option name="times_operator">&#183;</option><option name="imaginary_unit">i</option></options><localData><data name="casSession"/></localData></question>]]>
    </wirisquestion>
  </question>
 </quiz>
