{"id":16521,"date":"2019-10-03T17:08:45","date_gmt":"2019-10-03T17:08:45","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/wm-developmentalemporium\/chapter\/interpreting-the-y-intercept-and-making-predictions\/"},"modified":"2024-04-30T23:14:46","modified_gmt":"2024-04-30T23:14:46","slug":"interpreting-the-y-intercept-and-making-predictions","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/wm-developmentalemporium\/chapter\/interpreting-the-y-intercept-and-making-predictions\/","title":{"raw":"Interpreting the y-Intercept and Making Predictions","rendered":"Interpreting the y-Intercept and Making Predictions"},"content":{"raw":"<div class=\"bcc-box bcc-highlight\">\r\n<h3>Learning Outcomes<\/h3>\r\n<ul>\r\n \t<li>Interpret the characteristics of a linear equation and use that equation to make predictions<\/li>\r\n<\/ul>\r\n<\/div>\r\n<h2>Interpret the <em>y<\/em>-intercept of a linear equation<\/h2>\r\nEarlier in this module, we learned how to write the equation of a line given the slope and [latex]y[\/latex]-intercept. \u00a0Often, when the line in question represents a set of data or observations, the [latex]y[\/latex]-intercept can be interpreted as a starting point. \u00a0We will continue to use the examples for house value in Mississippi and Hawaii and high school smokers to interpret the meaning of the [latex]y[\/latex]-intercept in those equations.\r\n<div class=\"textbox exercises\">\r\n<h3>Example<\/h3>\r\n<strong>Recall the equations and data for house value:<\/strong>\r\n\r\nLinear equations describing the change in median home values between [latex]1950[\/latex] and [latex]2000[\/latex] in Mississippi and Hawaii are as follows:\r\n\r\n<strong>Hawaii:\u00a0<\/strong> [latex]y = 3966x+74,400[\/latex]\r\n\r\n<strong>Mississippi:\u00a0\u00a0<\/strong>[latex]y = 924x+25,200[\/latex]\r\n\r\nThe equations are based on the following dataset.\r\n\r\n[latex]x[\/latex] = the number of years since [latex]1950[\/latex], and y = the median value of a house in the given state.\r\n<table id=\"Table_04_02_03\" summary=\"This table shows three rows and three columns. The first column is labeled: \u201cYear\u201d, the second: \u201cMississippi\u201d and the third: \u201cHawaii\u201d. The two year entries are: \u201c1950\u201d and \u201c2000\u201d. The two Mississippi entries are: \u201c$25,200\u201d and \u201c$71,400\u201d. The two Hawaii entries are: \u201c$74,400\u201d and \u201c$272,700\u201d.\">\r\n<thead>\r\n<tr>\r\n<th scope=\"col\">Year (x)<\/th>\r\n<th scope=\"col\">Mississippi House Value (y)<\/th>\r\n<th scope=\"col\">Hawaii House Value (y)<\/th>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr>\r\n<td>[latex]0[\/latex]<\/td>\r\n<td>[latex]$25,200[\/latex]<\/td>\r\n<td>[latex]$74,400[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>[latex]50[\/latex]<\/td>\r\n<td>[latex]$71,400[\/latex]<\/td>\r\n<td>[latex]$272,700[\/latex]<strong>\u00a0<\/strong><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nAnd the equations and data for high school smokers:\r\n\r\nA linear equation describing the change in the number of high school students who smoke, in\u00a0a group of [latex]100[\/latex], between [latex]2011[\/latex] and [latex]2015[\/latex] is given as:\r\n<p style=\"text-align: center;\">\u00a0[latex]y = -1.75x+16[\/latex]<\/p>\r\nAnd is based on the data from this table, provided by the Centers for Disease Control.\r\n\r\n[latex]x[\/latex] = the number of years since [latex]2011[\/latex], and [latex]y[\/latex] = the number of high school smokers per [latex]100[\/latex] students.\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>Year<\/td>\r\n<td>Number of \u00a0High School Students Smoking\u00a0Cigarettes (per 100)<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>[latex]0[\/latex]<\/td>\r\n<td>[latex]16[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>[latex]4[\/latex]<\/td>\r\n<td>[latex]9[\/latex]<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nAlso recall that the equation of a line in slope-intercept form is as follows:\r\n<p style=\"text-align: center;\">[latex]y = mx + b[\/latex]<\/p>\r\n<p style=\"text-align: center;\">[latex]\\begin{array}{l}\\,\\,\\,\\,\\,m\\,\\,\\,\\,=\\,\\,\\,\\text{slope}\\\\(x,y)=\\,\\,\\,\\text{a point on the line}\\\\\\,\\,\\,\\,\\,\\,\\,b\\,\\,\\,\\,=\\,\\,\\,\\text{the y value of the y-intercept}\\end{array}[\/latex]<\/p>\r\n\r\n<\/div>\r\n&nbsp;\r\n<p style=\"text-align: left;\">The examples that follow show how to interpret the y-intercept of the equations used to model house value and the number of high school smokers. Additionally, you will see how to use the equations to make predictions about house value and the number of smokers in future years.<\/p>\r\n\r\n<div class=\"textbox exercises\">\r\n<h3>Example<\/h3>\r\nInterpret the y-intercepts of the equations that represent the change in house value for Hawaii and Mississippi.\r\n\r\n<strong>Hawaii:\u00a0<\/strong> [latex]y = 3966x+74,400[\/latex]\r\n\r\n<strong>Mississippi:\u00a0\u00a0<\/strong>[latex]y = 924x+25,200[\/latex]\r\n\r\nThe y-intercept of a two-variable linear equation can be found by substituting [latex]0[\/latex] in for [latex]x[\/latex].\r\n<h4>Hawaii<\/h4>\r\n<p style=\"text-align: center;\">[latex]y = 3966x+74,400\\\\y = 3966(0)+74,400\\\\y = 74,400[\/latex]<\/p>\r\nThe [latex]y[\/latex]-intercept is a point, so we write it as (0, 74,400). \u00a0Remember that [latex]y[\/latex]-values represent dollars and [latex]x[\/latex] values represent years. \u00a0When the year is [latex]0[\/latex]\u2014in this case [latex]0[\/latex]\u00a0because that is the first date we have in the dataset\u2014the price of a house in Hawaii was [latex]$74,400[\/latex].\u00a0 (Remember that [latex]x[\/latex] represents the number of years since [latex]1950[\/latex], so if [latex]x=0[\/latex] the year is [latex]1950[\/latex].)\r\n<h4>Mississippi<\/h4>\r\n<p style=\"text-align: center;\">[latex]y = 924x+25,200\\\\y = 924(0)+25,200\\\\y = 25,200[\/latex]<\/p>\r\nThe [latex]y[\/latex]-intercept is [latex](0, 25,200)[\/latex]. \u00a0This means that in [latex]1950[\/latex] the value of a house in Mississippi was [latex]$25,200[\/latex].\r\n\r\n<\/div>\r\n<h2 class=\"yt watch-title-container\"><\/h2>\r\n<div class=\"textbox exercises\">\r\n<h3>Example<\/h3>\r\nInterpret the [latex]y[\/latex]-intercept of the equation that represents the change in the number of high school students who smoke out of [latex]100[\/latex].\r\n\r\nSubstitute [latex]0[\/latex] in for [latex]x[\/latex].\r\n<p style=\"text-align: center;\">[latex]y = -1.75x+16\\\\y = -1.75(0)+16\\\\y = 16[\/latex]<\/p>\r\nThe [latex]y[\/latex]-intercept is [latex](0,16)[\/latex]. \u00a0The data starts at [latex]2011[\/latex], so we represent that year as [latex]0[\/latex]. We can interpret the [latex]y[\/latex]-intercept as follows:\r\n\r\nIn the year [latex]2011[\/latex], [latex]16[\/latex] out of every [latex]100[\/latex] high school students smoked.\r\n\r\n<\/div>\r\n<p class=\"yt watch-title-container\"><span id=\"eow-title\" class=\"watch-title\" dir=\"ltr\" title=\"Interpret the Meaning of the y-intercept Given a Linear Equation\">In the following video you will see an example of how to interpret the [latex]y[\/latex]- intercept given a linear equation that represents a set of data.<\/span><\/p>\r\nhttps:\/\/youtu.be\/Yhtl28DRqfU\r\n<h2>Use a linear equation to make a prediction<\/h2>\r\nAnother useful outcome we gain from writing equations from data is the ability to make predictions about what may happen in the future. We will continue our analysis of the house price and high school smokers. In the following examples you will be shown how to predict future outcomes based on the linear equations that model current behavior.\r\n<div class=\"textbox exercises\">\r\n<h3>Example<\/h3>\r\nUse the equations for house value in Hawaii and Mississippi to predict house value in\u00a0[latex]2035[\/latex].\r\n\r\nWe are asked to find house value, y, when the year, [latex]x[\/latex], is [latex]2035[\/latex]. Since the equations we have represent house value increase since [latex]1950[\/latex], we have to be careful. We can't just plug in [latex]2035[\/latex] for [latex]x[\/latex], because [latex]x[\/latex] represents the years since [latex]1950[\/latex].\r\n\r\nHow many years are between [latex]1950[\/latex] and [latex]2035[\/latex]? [latex]2035 - 1950 = 85[\/latex]\r\n\r\nThis is our [latex]x[\/latex]-value.\r\n\r\nFor Hawaii:\r\n<p style=\"text-align: center;\">[latex]y = 3966x+74,400\\\\y = 3966(85)+74,400\\\\y = 337110+74,400 = 411,510[\/latex]<\/p>\r\nHoly cow! The average price for a house in Hawaii in [latex]2035[\/latex] is predicted to be [latex]$411,510[\/latex] according to this model. See if you can find the current average value of a house in Hawaii. Does the model measure up?\r\n\r\nFor Mississippi:\r\n<p style=\"text-align: center;\">[latex]y = 924x+25,200\\\\y = 924(85)+25,200\\\\y = 78540+25,200 = 103,740[\/latex]<\/p>\r\nThe average price for a home in Mississippi in [latex]2035[\/latex] is predicted to be [latex]$103,740[\/latex] according to the model.\u00a0See if you can find the current average value of a house in Mississippi. Does the model measure up?\r\n\r\n<\/div>\r\nIn the following video, you will see the example of how to make a prediction with the home value data.\r\n\r\nhttps:\/\/youtu.be\/Bw9XjDAl-K0\r\n<div class=\"textbox key-takeaways\">\r\n<h3>Try It<\/h3>\r\n[ohm_question]188447[\/ohm_question]\r\n\r\n<\/div>\r\n&nbsp;\r\n<div class=\"textbox exercises\">\r\n<h3>Example<\/h3>\r\nUse the equation for the number of high school smokers per [latex]100[\/latex] to predict the year when there will be [latex]0[\/latex] smokers per [latex]100[\/latex].\r\n<p style=\"text-align: center;\">[latex]y = -1.75x+16[\/latex]<\/p>\r\nThis question takes a little more thinking. \u00a0In terms of [latex]x[\/latex] and [latex]y[\/latex], what does it mean to have [latex]0[\/latex] smokers? \u00a0Since y represents the number of smokers and [latex]x[\/latex] represent the year, we are being asked when [latex]y[\/latex] will be [latex]0[\/latex].\r\n\r\nSubstitute [latex]0[\/latex] for [latex]y[\/latex].\r\n<p style=\"text-align: center;\">[latex]y = -1.75x+16[\/latex]<\/p>\r\n<p style=\"text-align: center;\">[latex]0 = -1.75x+16[\/latex]<\/p>\r\n<p style=\"text-align: center;\">[latex]-16 = -1.75x[\/latex]<\/p>\r\n<p style=\"text-align: center;\">[latex]\\frac{-16}{-1.75} = x[\/latex]<\/p>\r\n<p style=\"text-align: center;\">[latex]x = 9.14[\/latex] years<\/p>\r\nAgain, like the last example, [latex]x[\/latex] is representing the number of years since the start of the data\u2014which was [latex]2011[\/latex], based on the table:\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>Year<\/td>\r\n<td>Number of \u00a0High School Students Smoking\u00a0Cigarettes (per 100)<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>[latex]0[\/latex]<\/td>\r\n<td>[latex]16[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>[latex]4[\/latex]<\/td>\r\n<td>[latex]9[\/latex]<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nSo we are predicting that there will be no smokers in high school by [latex]2011+9.14=2020[\/latex]. How accurate do you think this model is? Do you think there will ever be [latex]0[\/latex] smokers in high school?\r\n\r\n<\/div>\r\nThe following video gives a thorough explanation of making a prediction given a linear equation.\r\n\r\nhttps:\/\/youtu.be\/5W0qq8saxO0\r\n\r\n&nbsp;\r\n<h2>Bringing it Together<\/h2>\r\nThe last example we will show will include all of the concepts that we have been building up throughout this module. \u00a0We will interpret a word problem, write a linear equation from it, graph the equation, interpret the [latex]y[\/latex]-intercept and make a prediction. Hopefully this example will help you to make\u00a0connections between the concepts we have presented.\r\n<div class=\"textbox exercises\">\r\n<h3>Example<\/h3>\r\nIt costs [latex]$600[\/latex] to purchase an iphone, plus [latex]$55[\/latex] per month for unlimited use and data.\r\n\r\nWrite a linear equation that represents the cost, [latex]y[\/latex], \u00a0of owning and using the\u00a0iPhone for [latex]x[\/latex] amount of months. When you have written your equation, answer the following questions:\r\n<ol>\r\n \t<li>What is the total cost you\u2019ve paid after\u00a0owning and using your phone for [latex]24[\/latex] months?<\/li>\r\n \t<li>If you have spent\u00a0[latex]$2,580[\/latex] since you purchased your phone, how many months have you used your phone?<\/li>\r\n<\/ol>\r\n[caption id=\"attachment_4649\" align=\"alignnone\" width=\"206\"]<img class=\" wp-image-4649\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/117\/2016\/06\/07175121\/Screen-Shot-2016-06-07-at-10.50.43-AM-300x220.png\" alt=\"5 iPhones laying next to each other\" width=\"206\" height=\"151\" \/> iPhone[\/caption]\r\n\r\n[reveal-answer q=\"282349\"]Show Solution[\/reveal-answer]\r\n[hidden-answer a=\"282349\"][\/hidden-answer]\r\n\r\n<strong>Read and Understand:<\/strong>\u00a0We need to write a linear equation that represents the cost of owning and using an iPhone for any number of months. \u00a0We are to use [latex]y[\/latex] to represent cost, and [latex]x[\/latex] to represent the number of months we have used the phone.\r\n\r\n<strong>Define and Translate:\u00a0<\/strong>We will use the slope-intercept form of a line, [latex]y=mx+b[\/latex], because we are given a starting cost and a monthly cost for use. \u00a0We will need to find the slope and the [latex]y[\/latex]-intercept.\r\n\r\nSlope: in this case we don't know two points, but we are given a rate in dollars for monthly use of the phone. \u00a0Our units are dollars per month because slope is [latex]\\frac{\\Delta{y}}{\\Delta{x}}[\/latex], and [latex]y[\/latex] is in dollars and [latex]x[\/latex] is in months. The slope will be [latex]\\frac{55\\text{ dollars }}{1\\text{ month }}[\/latex]:\u00a0 [latex]m=\\frac{55}{1}=55[\/latex]\r\n\r\n[latex]Y[\/latex]-Intercept: the [latex]y[\/latex]-intercept is defined as a point [latex]\\left(0,b\\right)[\/latex]. \u00a0We want to know how much money we have spent, [latex]y[\/latex], after [latex]0[\/latex] months. \u00a0We haven't paid for service yet, but we have paid [latex]$600[\/latex] for the phone. The [latex]y[\/latex]-intercept in this case is called an initial cost. [latex]b=600[\/latex]\r\n\r\n<strong>Write and Solve:\u00a0<\/strong>Substitute the slope and intercept you defined into the slope-intercept equation.\r\n<p style=\"text-align: center;\">[latex]\\begin{array}{c}y=mx+b\\\\y=55x+600\\end{array}[\/latex]<\/p>\r\n<p style=\"text-align: left;\">Now we will answer the following questions:<\/p>\r\n\r\n<ol>\r\n \t<li>What is the total cost you\u2019ve paid after\u00a0owning and using your phone for [latex]24[\/latex] months?<\/li>\r\n<\/ol>\r\nSince [latex]x[\/latex] represents the number of months you have used the phone, we can substitute [latex]x=24[\/latex] into our equation.\r\n<p style=\"text-align: center;\">[latex]\\begin{array}{c}y=55x+600\\\\y=55\\left(24\\right)+600\\\\y=1320+600\\\\y=1920\\end{array}[\/latex]<\/p>\r\n<p style=\"text-align: left;\">[latex]Y[\/latex] represents the cost after [latex]x[\/latex] number of months, so in this scenario, after [latex]24[\/latex] months, you have spent [latex]$1920[\/latex] to own and use an iPhone.<\/p>\r\n\r\n<ol>\r\n \t<li>If you have spent\u00a0[latex]$2,580[\/latex] since you purchased your phone, how many months have you used your phone?<\/li>\r\n<\/ol>\r\nWe know that [latex]y[\/latex] represents cost, and we are given a cost and asked to find the number of months related to having spent that much. We will substitute [latex]y=$2,580[\/latex] into the equation, then use what we know about solving linear equations to isolate [latex]x[\/latex]:\r\n<p style=\"text-align: center;\">\u00a0[latex]\\begin{array}{l}\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,y=55x+600\\\\\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,2580=55x+600\\\\\\text{ subtract 600 from each side}\\,\\,\\,\\,\\,\\,\\,\\underline{-600}\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\underline{-600}\\\\\\text{}\\\\\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,1980=55x\\\\\\text{}\\\\\\text{ divide each side by 55 }\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\frac{1980}{55}=\\frac{55x}{55}\\\\\\text{}\\\\\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,36=x\\end{array}[\/latex]<\/p>\r\n<p style=\"text-align: left;\">If you have spent [latex]$2,580[\/latex] then you have been using your iPhone for [latex]36[\/latex] months, or [latex]3[\/latex] years.<\/p>\r\n\r\n<\/div>","rendered":"<div class=\"bcc-box bcc-highlight\">\n<h3>Learning Outcomes<\/h3>\n<ul>\n<li>Interpret the characteristics of a linear equation and use that equation to make predictions<\/li>\n<\/ul>\n<\/div>\n<h2>Interpret the <em>y<\/em>-intercept of a linear equation<\/h2>\n<p>Earlier in this module, we learned how to write the equation of a line given the slope and [latex]y[\/latex]-intercept. \u00a0Often, when the line in question represents a set of data or observations, the [latex]y[\/latex]-intercept can be interpreted as a starting point. \u00a0We will continue to use the examples for house value in Mississippi and Hawaii and high school smokers to interpret the meaning of the [latex]y[\/latex]-intercept in those equations.<\/p>\n<div class=\"textbox exercises\">\n<h3>Example<\/h3>\n<p><strong>Recall the equations and data for house value:<\/strong><\/p>\n<p>Linear equations describing the change in median home values between [latex]1950[\/latex] and [latex]2000[\/latex] in Mississippi and Hawaii are as follows:<\/p>\n<p><strong>Hawaii:\u00a0<\/strong> [latex]y = 3966x+74,400[\/latex]<\/p>\n<p><strong>Mississippi:\u00a0\u00a0<\/strong>[latex]y = 924x+25,200[\/latex]<\/p>\n<p>The equations are based on the following dataset.<\/p>\n<p>[latex]x[\/latex] = the number of years since [latex]1950[\/latex], and y = the median value of a house in the given state.<\/p>\n<table id=\"Table_04_02_03\" summary=\"This table shows three rows and three columns. The first column is labeled: \u201cYear\u201d, the second: \u201cMississippi\u201d and the third: \u201cHawaii\u201d. The two year entries are: \u201c1950\u201d and \u201c2000\u201d. The two Mississippi entries are: \u201c$25,200\u201d and \u201c$71,400\u201d. The two Hawaii entries are: \u201c$74,400\u201d and \u201c$272,700\u201d.\">\n<thead>\n<tr>\n<th scope=\"col\">Year (x)<\/th>\n<th scope=\"col\">Mississippi House Value (y)<\/th>\n<th scope=\"col\">Hawaii House Value (y)<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>[latex]0[\/latex]<\/td>\n<td>[latex]$25,200[\/latex]<\/td>\n<td>[latex]$74,400[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>[latex]50[\/latex]<\/td>\n<td>[latex]$71,400[\/latex]<\/td>\n<td>[latex]$272,700[\/latex]<strong>\u00a0<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>And the equations and data for high school smokers:<\/p>\n<p>A linear equation describing the change in the number of high school students who smoke, in\u00a0a group of [latex]100[\/latex], between [latex]2011[\/latex] and [latex]2015[\/latex] is given as:<\/p>\n<p style=\"text-align: center;\">\u00a0[latex]y = -1.75x+16[\/latex]<\/p>\n<p>And is based on the data from this table, provided by the Centers for Disease Control.<\/p>\n<p>[latex]x[\/latex] = the number of years since [latex]2011[\/latex], and [latex]y[\/latex] = the number of high school smokers per [latex]100[\/latex] students.<\/p>\n<table>\n<tbody>\n<tr>\n<td>Year<\/td>\n<td>Number of \u00a0High School Students Smoking\u00a0Cigarettes (per 100)<\/td>\n<\/tr>\n<tr>\n<td>[latex]0[\/latex]<\/td>\n<td>[latex]16[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>[latex]4[\/latex]<\/td>\n<td>[latex]9[\/latex]<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Also recall that the equation of a line in slope-intercept form is as follows:<\/p>\n<p style=\"text-align: center;\">[latex]y = mx + b[\/latex]<\/p>\n<p style=\"text-align: center;\">[latex]\\begin{array}{l}\\,\\,\\,\\,\\,m\\,\\,\\,\\,=\\,\\,\\,\\text{slope}\\\\(x,y)=\\,\\,\\,\\text{a point on the line}\\\\\\,\\,\\,\\,\\,\\,\\,b\\,\\,\\,\\,=\\,\\,\\,\\text{the y value of the y-intercept}\\end{array}[\/latex]<\/p>\n<\/div>\n<p>&nbsp;<\/p>\n<p style=\"text-align: left;\">The examples that follow show how to interpret the y-intercept of the equations used to model house value and the number of high school smokers. Additionally, you will see how to use the equations to make predictions about house value and the number of smokers in future years.<\/p>\n<div class=\"textbox exercises\">\n<h3>Example<\/h3>\n<p>Interpret the y-intercepts of the equations that represent the change in house value for Hawaii and Mississippi.<\/p>\n<p><strong>Hawaii:\u00a0<\/strong> [latex]y = 3966x+74,400[\/latex]<\/p>\n<p><strong>Mississippi:\u00a0\u00a0<\/strong>[latex]y = 924x+25,200[\/latex]<\/p>\n<p>The y-intercept of a two-variable linear equation can be found by substituting [latex]0[\/latex] in for [latex]x[\/latex].<\/p>\n<h4>Hawaii<\/h4>\n<p style=\"text-align: center;\">[latex]y = 3966x+74,400\\\\y = 3966(0)+74,400\\\\y = 74,400[\/latex]<\/p>\n<p>The [latex]y[\/latex]-intercept is a point, so we write it as (0, 74,400). \u00a0Remember that [latex]y[\/latex]-values represent dollars and [latex]x[\/latex] values represent years. \u00a0When the year is [latex]0[\/latex]\u2014in this case [latex]0[\/latex]\u00a0because that is the first date we have in the dataset\u2014the price of a house in Hawaii was [latex]$74,400[\/latex].\u00a0 (Remember that [latex]x[\/latex] represents the number of years since [latex]1950[\/latex], so if [latex]x=0[\/latex] the year is [latex]1950[\/latex].)<\/p>\n<h4>Mississippi<\/h4>\n<p style=\"text-align: center;\">[latex]y = 924x+25,200\\\\y = 924(0)+25,200\\\\y = 25,200[\/latex]<\/p>\n<p>The [latex]y[\/latex]-intercept is [latex](0, 25,200)[\/latex]. \u00a0This means that in [latex]1950[\/latex] the value of a house in Mississippi was [latex]$25,200[\/latex].<\/p>\n<\/div>\n<h2 class=\"yt watch-title-container\"><\/h2>\n<div class=\"textbox exercises\">\n<h3>Example<\/h3>\n<p>Interpret the [latex]y[\/latex]-intercept of the equation that represents the change in the number of high school students who smoke out of [latex]100[\/latex].<\/p>\n<p>Substitute [latex]0[\/latex] in for [latex]x[\/latex].<\/p>\n<p style=\"text-align: center;\">[latex]y = -1.75x+16\\\\y = -1.75(0)+16\\\\y = 16[\/latex]<\/p>\n<p>The [latex]y[\/latex]-intercept is [latex](0,16)[\/latex]. \u00a0The data starts at [latex]2011[\/latex], so we represent that year as [latex]0[\/latex]. We can interpret the [latex]y[\/latex]-intercept as follows:<\/p>\n<p>In the year [latex]2011[\/latex], [latex]16[\/latex] out of every [latex]100[\/latex] high school students smoked.<\/p>\n<\/div>\n<p class=\"yt watch-title-container\"><span id=\"eow-title\" class=\"watch-title\" dir=\"ltr\" title=\"Interpret the Meaning of the y-intercept Given a Linear Equation\">In the following video you will see an example of how to interpret the [latex]y[\/latex]&#8211; intercept given a linear equation that represents a set of data.<\/span><\/p>\n<p><iframe loading=\"lazy\" id=\"oembed-1\" title=\"Interpret the Meaning of the y-intercept Given a Linear Equation\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/Yhtl28DRqfU?feature=oembed&#38;rel=0\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<h2>Use a linear equation to make a prediction<\/h2>\n<p>Another useful outcome we gain from writing equations from data is the ability to make predictions about what may happen in the future. We will continue our analysis of the house price and high school smokers. In the following examples you will be shown how to predict future outcomes based on the linear equations that model current behavior.<\/p>\n<div class=\"textbox exercises\">\n<h3>Example<\/h3>\n<p>Use the equations for house value in Hawaii and Mississippi to predict house value in\u00a0[latex]2035[\/latex].<\/p>\n<p>We are asked to find house value, y, when the year, [latex]x[\/latex], is [latex]2035[\/latex]. Since the equations we have represent house value increase since [latex]1950[\/latex], we have to be careful. We can&#8217;t just plug in [latex]2035[\/latex] for [latex]x[\/latex], because [latex]x[\/latex] represents the years since [latex]1950[\/latex].<\/p>\n<p>How many years are between [latex]1950[\/latex] and [latex]2035[\/latex]? [latex]2035 - 1950 = 85[\/latex]<\/p>\n<p>This is our [latex]x[\/latex]-value.<\/p>\n<p>For Hawaii:<\/p>\n<p style=\"text-align: center;\">[latex]y = 3966x+74,400\\\\y = 3966(85)+74,400\\\\y = 337110+74,400 = 411,510[\/latex]<\/p>\n<p>Holy cow! The average price for a house in Hawaii in [latex]2035[\/latex] is predicted to be [latex]$411,510[\/latex] according to this model. See if you can find the current average value of a house in Hawaii. Does the model measure up?<\/p>\n<p>For Mississippi:<\/p>\n<p style=\"text-align: center;\">[latex]y = 924x+25,200\\\\y = 924(85)+25,200\\\\y = 78540+25,200 = 103,740[\/latex]<\/p>\n<p>The average price for a home in Mississippi in [latex]2035[\/latex] is predicted to be [latex]$103,740[\/latex] according to the model.\u00a0See if you can find the current average value of a house in Mississippi. Does the model measure up?<\/p>\n<\/div>\n<p>In the following video, you will see the example of how to make a prediction with the home value data.<\/p>\n<p><iframe loading=\"lazy\" id=\"oembed-2\" title=\"Make a Prediction Using a Linear Equation - Home Value\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/Bw9XjDAl-K0?feature=oembed&#38;rel=0\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<div class=\"textbox key-takeaways\">\n<h3>Try It<\/h3>\n<p><iframe loading=\"lazy\" id=\"ohm188447\" class=\"resizable\" src=\"https:\/\/ohm.lumenlearning.com\/multiembedq.php?id=188447&theme=oea&iframe_resize_id=ohm188447&show_question_numbers\" width=\"100%\" height=\"150\"><\/iframe><\/p>\n<\/div>\n<p>&nbsp;<\/p>\n<div class=\"textbox exercises\">\n<h3>Example<\/h3>\n<p>Use the equation for the number of high school smokers per [latex]100[\/latex] to predict the year when there will be [latex]0[\/latex] smokers per [latex]100[\/latex].<\/p>\n<p style=\"text-align: center;\">[latex]y = -1.75x+16[\/latex]<\/p>\n<p>This question takes a little more thinking. \u00a0In terms of [latex]x[\/latex] and [latex]y[\/latex], what does it mean to have [latex]0[\/latex] smokers? \u00a0Since y represents the number of smokers and [latex]x[\/latex] represent the year, we are being asked when [latex]y[\/latex] will be [latex]0[\/latex].<\/p>\n<p>Substitute [latex]0[\/latex] for [latex]y[\/latex].<\/p>\n<p style=\"text-align: center;\">[latex]y = -1.75x+16[\/latex]<\/p>\n<p style=\"text-align: center;\">[latex]0 = -1.75x+16[\/latex]<\/p>\n<p style=\"text-align: center;\">[latex]-16 = -1.75x[\/latex]<\/p>\n<p style=\"text-align: center;\">[latex]\\frac{-16}{-1.75} = x[\/latex]<\/p>\n<p style=\"text-align: center;\">[latex]x = 9.14[\/latex] years<\/p>\n<p>Again, like the last example, [latex]x[\/latex] is representing the number of years since the start of the data\u2014which was [latex]2011[\/latex], based on the table:<\/p>\n<table>\n<tbody>\n<tr>\n<td>Year<\/td>\n<td>Number of \u00a0High School Students Smoking\u00a0Cigarettes (per 100)<\/td>\n<\/tr>\n<tr>\n<td>[latex]0[\/latex]<\/td>\n<td>[latex]16[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>[latex]4[\/latex]<\/td>\n<td>[latex]9[\/latex]<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>So we are predicting that there will be no smokers in high school by [latex]2011+9.14=2020[\/latex]. How accurate do you think this model is? Do you think there will ever be [latex]0[\/latex] smokers in high school?<\/p>\n<\/div>\n<p>The following video gives a thorough explanation of making a prediction given a linear equation.<\/p>\n<p><iframe loading=\"lazy\" id=\"oembed-3\" title=\"Make a Prediction Using a Linear Equation (Horizontal Intercept) - Smokers\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/5W0qq8saxO0?feature=oembed&#38;rel=0\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p>&nbsp;<\/p>\n<h2>Bringing it Together<\/h2>\n<p>The last example we will show will include all of the concepts that we have been building up throughout this module. \u00a0We will interpret a word problem, write a linear equation from it, graph the equation, interpret the [latex]y[\/latex]-intercept and make a prediction. Hopefully this example will help you to make\u00a0connections between the concepts we have presented.<\/p>\n<div class=\"textbox exercises\">\n<h3>Example<\/h3>\n<p>It costs [latex]$600[\/latex] to purchase an iphone, plus [latex]$55[\/latex] per month for unlimited use and data.<\/p>\n<p>Write a linear equation that represents the cost, [latex]y[\/latex], \u00a0of owning and using the\u00a0iPhone for [latex]x[\/latex] amount of months. When you have written your equation, answer the following questions:<\/p>\n<ol>\n<li>What is the total cost you\u2019ve paid after\u00a0owning and using your phone for [latex]24[\/latex] months?<\/li>\n<li>If you have spent\u00a0[latex]$2,580[\/latex] since you purchased your phone, how many months have you used your phone?<\/li>\n<\/ol>\n<div id=\"attachment_4649\" style=\"width: 216px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-4649\" class=\"wp-image-4649\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/117\/2016\/06\/07175121\/Screen-Shot-2016-06-07-at-10.50.43-AM-300x220.png\" alt=\"5 iPhones laying next to each other\" width=\"206\" height=\"151\" \/><\/p>\n<p id=\"caption-attachment-4649\" class=\"wp-caption-text\">iPhone<\/p>\n<\/div>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q282349\">Show Solution<\/span><\/p>\n<div id=\"q282349\" class=\"hidden-answer\" style=\"display: none\"><\/div>\n<\/div>\n<p><strong>Read and Understand:<\/strong>\u00a0We need to write a linear equation that represents the cost of owning and using an iPhone for any number of months. \u00a0We are to use [latex]y[\/latex] to represent cost, and [latex]x[\/latex] to represent the number of months we have used the phone.<\/p>\n<p><strong>Define and Translate:\u00a0<\/strong>We will use the slope-intercept form of a line, [latex]y=mx+b[\/latex], because we are given a starting cost and a monthly cost for use. \u00a0We will need to find the slope and the [latex]y[\/latex]-intercept.<\/p>\n<p>Slope: in this case we don&#8217;t know two points, but we are given a rate in dollars for monthly use of the phone. \u00a0Our units are dollars per month because slope is [latex]\\frac{\\Delta{y}}{\\Delta{x}}[\/latex], and [latex]y[\/latex] is in dollars and [latex]x[\/latex] is in months. The slope will be [latex]\\frac{55\\text{ dollars }}{1\\text{ month }}[\/latex]:\u00a0 [latex]m=\\frac{55}{1}=55[\/latex]<\/p>\n<p>[latex]Y[\/latex]-Intercept: the [latex]y[\/latex]-intercept is defined as a point [latex]\\left(0,b\\right)[\/latex]. \u00a0We want to know how much money we have spent, [latex]y[\/latex], after [latex]0[\/latex] months. \u00a0We haven&#8217;t paid for service yet, but we have paid [latex]$600[\/latex] for the phone. The [latex]y[\/latex]-intercept in this case is called an initial cost. [latex]b=600[\/latex]<\/p>\n<p><strong>Write and Solve:\u00a0<\/strong>Substitute the slope and intercept you defined into the slope-intercept equation.<\/p>\n<p style=\"text-align: center;\">[latex]\\begin{array}{c}y=mx+b\\\\y=55x+600\\end{array}[\/latex]<\/p>\n<p style=\"text-align: left;\">Now we will answer the following questions:<\/p>\n<ol>\n<li>What is the total cost you\u2019ve paid after\u00a0owning and using your phone for [latex]24[\/latex] months?<\/li>\n<\/ol>\n<p>Since [latex]x[\/latex] represents the number of months you have used the phone, we can substitute [latex]x=24[\/latex] into our equation.<\/p>\n<p style=\"text-align: center;\">[latex]\\begin{array}{c}y=55x+600\\\\y=55\\left(24\\right)+600\\\\y=1320+600\\\\y=1920\\end{array}[\/latex]<\/p>\n<p style=\"text-align: left;\">[latex]Y[\/latex] represents the cost after [latex]x[\/latex] number of months, so in this scenario, after [latex]24[\/latex] months, you have spent [latex]$1920[\/latex] to own and use an iPhone.<\/p>\n<ol>\n<li>If you have spent\u00a0[latex]$2,580[\/latex] since you purchased your phone, how many months have you used your phone?<\/li>\n<\/ol>\n<p>We know that [latex]y[\/latex] represents cost, and we are given a cost and asked to find the number of months related to having spent that much. We will substitute [latex]y=$2,580[\/latex] into the equation, then use what we know about solving linear equations to isolate [latex]x[\/latex]:<\/p>\n<p style=\"text-align: center;\">\u00a0[latex]\\begin{array}{l}\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,y=55x+600\\\\\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,2580=55x+600\\\\\\text{ subtract 600 from each side}\\,\\,\\,\\,\\,\\,\\,\\underline{-600}\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\underline{-600}\\\\\\text{}\\\\\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,1980=55x\\\\\\text{}\\\\\\text{ divide each side by 55 }\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\frac{1980}{55}=\\frac{55x}{55}\\\\\\text{}\\\\\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,36=x\\end{array}[\/latex]<\/p>\n<p style=\"text-align: left;\">If you have spent [latex]$2,580[\/latex] then you have been using your iPhone for [latex]36[\/latex] months, or [latex]3[\/latex] years.<\/p>\n<\/div>\n\n\t\t\t <section class=\"citations-section\" role=\"contentinfo\">\n\t\t\t <h3>Candela Citations<\/h3>\n\t\t\t\t\t <div>\n\t\t\t\t\t\t <div id=\"citation-list-16521\">\n\t\t\t\t\t\t\t <div class=\"licensing\"><div class=\"license-attribution-dropdown-subheading\">CC licensed content, Shared previously<\/div><ul class=\"citation-list\"><li>Interpret the Meaning of the y-intercept Given a Linear Equation. <strong>Authored by<\/strong>: Mathispower4u. <strong>Located at<\/strong>: <a target=\"_blank\" href=\"https:\/\/youtu.be\/Yhtl28DRqfU\">https:\/\/youtu.be\/Yhtl28DRqfU<\/a>. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em><\/li><li>Make a Prediction Using a Linear Equation - Home Value. <strong>Authored by<\/strong>: Mathispower4u. <strong>Located at<\/strong>: <a target=\"_blank\" href=\"https:\/\/youtu.be\/Bw9XjDAl-K0\">https:\/\/youtu.be\/Bw9XjDAl-K0<\/a>. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em><\/li><li>Make a Prediction Using a Linear Equation (Horizontal Intercept) - Smokers. <strong>Authored by<\/strong>: Mathispower4u. <strong>Located at<\/strong>: <a target=\"_blank\" href=\"https:\/\/youtu.be\/5W0qq8saxO0\">https:\/\/youtu.be\/5W0qq8saxO0<\/a>. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em><\/li><\/ul><div class=\"license-attribution-dropdown-subheading\">Public domain content<\/div><ul class=\"citation-list\"><li>Historical Census of Housing Tables Home Values. <strong>Authored by<\/strong>: United States Census Bureau. <strong>Provided by<\/strong>: U.S. Dept. of Housing. <strong>Located at<\/strong>: <a target=\"_blank\" href=\"https:\/\/www.census.gov\/hhes\/www\/housing\/census\/historic\/values.html\">https:\/\/www.census.gov\/hhes\/www\/housing\/census\/historic\/values.html<\/a>. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/about\/pdm\">Public Domain: No Known Copyright<\/a><\/em><\/li><li>Youth and Tobacco Use. <strong>Authored by<\/strong>: Centers for Disease Control and Prevention. <strong>Provided by<\/strong>: U.S. Department of Health and Human Services. <strong>Located at<\/strong>: <a target=\"_blank\" href=\"http:\/\/www.cdc.gov\/tobacco\/data_statistics\/fact_sheets\/youth_data\/tobacco_use\/index.htm\">http:\/\/www.cdc.gov\/tobacco\/data_statistics\/fact_sheets\/youth_data\/tobacco_use\/index.htm<\/a>. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/about\/pdm\">Public Domain: No Known Copyright<\/a><\/em><\/li><\/ul><\/div>\n\t\t\t\t\t\t <\/div>\n\t\t\t\t\t <\/div>\n\t\t\t <\/section>","protected":false},"author":169554,"menu_order":29,"template":"","meta":{"_candela_citation":"[{\"type\":\"pd\",\"description\":\"Historical Census of Housing Tables Home Values\",\"author\":\"United States Census Bureau\",\"organization\":\"U.S. Dept. of Housing\",\"url\":\"https:\/\/www.census.gov\/hhes\/www\/housing\/census\/historic\/values.html\",\"project\":\"\",\"license\":\"pd\",\"license_terms\":\"\"},{\"type\":\"pd\",\"description\":\"Youth and Tobacco Use\",\"author\":\"Centers for Disease Control and Prevention\",\"organization\":\"U.S. Department of Health and Human Services\",\"url\":\"http:\/\/www.cdc.gov\/tobacco\/data_statistics\/fact_sheets\/youth_data\/tobacco_use\/index.htm\",\"project\":\"\",\"license\":\"pd\",\"license_terms\":\"\"},{\"type\":\"cc\",\"description\":\"Interpret the Meaning of the y-intercept Given a Linear Equation\",\"author\":\"Mathispower4u\",\"organization\":\"\",\"url\":\"https:\/\/youtu.be\/Yhtl28DRqfU\",\"project\":\"\",\"license\":\"cc-by\",\"license_terms\":\"\"},{\"type\":\"cc\",\"description\":\"Make a Prediction Using a Linear Equation - 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