[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-397504-105":59,"doc-detail-397504-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","math-1309-statistical-literacy-representative-syllabus","MATH 1309 Statistical Literacy - Representative Syllabus","","Representative MATH 1309 syllabus outlines course structure, including sections, Central Time scheduling, and policies governing classroom and online lecture recordings for academic use. It defines course description and required tools: mathematical software and calculators, plus a digital course materials program delivered through Canvas and ALEKS. Student Learning Outcomes cover data collection methods, descriptive statistics, probability and distributions, normal and sampling distributions, confidence intervals and hypothesis testing, and relationships using correlation and regression.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":20,"@type":76,"position":81},"https://docshare.wps.com/document/exam/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/math-1309-statistical-literacy-representative-syllabus/397504/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/math-1309-statistical-literacy-representative-syllabus/397504.png","ImageObject",300,407,{"name":92,"@type":93},"Cart","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-27","2026-09-26",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What topics does MATH 1309 Statistical Literacy cover?","Question",{"text":113,"@type":114},"The course covers data collection, analysis, presentation, and interpretation, including descriptive statistics, probability, relationships between variables and graphs, statistical models, hypothesis testing, inference, estimation, correlation, regression, and confidence intervals.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"Which calculator and technology requirements must students meet?",{"text":118,"@type":114},"Students may use a scientific non-graphing calculator on all assignments and exams, but it must be one of the listed Texas Instruments 30X series models. A web-enabled device is required for attendance check-in, and students use supported browsers such as Firefox or Chrome.",{"name":120,"@type":111,"acceptedAnswer":121},"What are the main Student Learning Outcomes (SLOs)?",{"text":122,"@type":114},"After completion, students can differentiate data collection methods with appropriate statistical terminology, perform descriptive statistics, determine probabilities and distributions for scenarios, apply the normal distribution, justify confidence intervals and hypothesis tests, and analyze relationships via correlation and regression.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},397504,1790949436,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":19,"category_name":20,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},18829141979164,"https://eur-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","Representative MATH 1309 Syllabus  \nInstructor Information  \nThis is an example of a syllabus that is typical for the class. An official syllabus will be provided by the faculty member teaching the specific section of the course for which students have enrolled.  \nCourse Information  \nSection Information  \n[SAMPLE]  \nCourse Description  \nCourse Title: MATH 1309 Statistical Literacy  \nTopics may include collection, analysis, presentation, and interpretation of data. Analysis includes descriptive statistics, probability, relationships between variables and graphs, elementary statistical models, hypothesis testing, inference, estimation, correlation, regression, and confidence intervals. The use of mathematical software and calculators is required.  \nPrerequisites: None  \nTime and Place of Class Meetings  \n[SAMPLE]  \nThis course operates on Central Time. All times listed for class meeting times, exams, and assignment deadlines are in Central Time (CT) .  \nClassroom/Lecture Recording Policy  \nFaculty maintain the academic right to determine whether students are permitted to record classroom and online lectures. Recordings of classroom lectures, if permitted by the instructor or pursuant to an ADA accommodation, may only be used for academic purposes related to the specific course. They may not be used for commercial purposes or shared with non-course participants except in connection with legal proceedings.  \nRecording of classroom and online lectures in this course [is/is not] allowed.  \nStudent Learning Outcomes (SLO)  \nAfter completing the course, you will be able to proficiently:  \n1. differentiate data collection methods and data features accurately and with appropriate statistical terminology.  \n2. execute accurate descriptive statistics using multiple methods.  \n3. determine appropriate probabilities, probability distributions, and combinatorics for realworld scenarios.  \n4. employ the Normal distribution in relevant applications, including sampling distributions.  \n5. justify with statistical accuracy the relevance of using confidence intervals and hypothesis tests as inferential tools.  \n6. examine the nature of the relationship between two quantitative variables, including correlation and regression.  \nCanvas Unit modules contain specific Learning Objectives for each SLO on corresponding Unit Introduction pages.  \nCourse Materials & Technology  \nTextbook Information  \nThis course is participating in a new program to provide digital course materials on or before the first day of class at a reduced cost. The cost for your digital materials will be charged to your UTA student account, and you will have access to the materials through Canvas. Course fees are associated with course registration.  \nDigital Access and eText Bundle (Required Course Materials) : Your course materials included in the $70 course fee contain the e-version of the course text as well as ALEKS course access ( ALEKS Higher-Ed Math with McGraw Hill eText for Essential Statistics, Evergreen Release, 2025, by Navidi and Monk), which is designed to enrich student success by providing instant feedback on your assignments plus on-demand access to personalized learning plans, multimedia lesson helps, and more.  \nFor more information about this program, please see the Course Resources page in your Canvas course and then for further questions, contact your campus bookstore at [uta@bkstr.com](uta@bkstr.com) or 817- 272-2785.  \nTechnology & Equipment Requirements  \nAdditional Materials and Associated Costs for this Course  \n1. One set of 3x5 index cards: A small package of plain, white 3x5 index cards. Prices range from $1 to $3. An index card will be used for attendance/activities at each lecture.  \n2. Scientific Calculator: Students may choose to use a scientific, non-graphing calculator on all assignments, including unit exams and the final exam. If so, it MUST be one of the following models explicitly:  \nTexas Instruments 30X series: TI-30XIIS (recommended), T","cbCaitA8qss5g9i8","https://ap.wps.com/l/cbCaitA8qss5g9i8","pdf",274307,"English","# Course Information\n## Section Information\n# Course Description\n## Topics\n## Prerequisites\n# Time and Place of Class Meetings\n# Classroom/Lecture Recording Policy\n# Student Learning Outcomes (SLO)\n## SLO List\n# Course Materials & Technology\n## Textbook Information\n## Digital Access and eText Bundle\n## Technology & Equipment Requirements\n## Software and System Requirements\n# Assignments & Exams\n## Pre-Lecture Videos\n## Homework and Quizzes","[{\"question\":\"What topics does MATH 1309 Statistical Literacy cover?\",\"answer\":\"The course covers data collection, analysis, presentation, and interpretation, including descriptive statistics, probability, relationships between variables and graphs, statistical models, hypothesis testing, inference, estimation, correlation, regression, and confidence intervals.\"},{\"question\":\"Which calculator and technology requirements must students meet?\",\"answer\":\"Students may use a scientific non-graphing calculator on all assignments and exams, but it must be one of the listed Texas Instruments 30X series models. A web-enabled device is required for attendance check-in, and students use supported browsers such as Firefox or Chrome.\"},{\"question\":\"What are the main Student Learning Outcomes (SLOs)?\",\"answer\":\"After completion, students can differentiate data collection methods with appropriate statistical terminology, perform descriptive statistics, determine probabilities and distributions for scenarios, apply the normal distribution, justify confidence intervals and hypothesis tests, and analyze relationships via correlation and regression.\"}]","MATH 1309 Statistical Literacy - Representative Syllabus | PDF",1790462543,25]