[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-571682-105":53,"doc-detail-571682-en":127},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":120,"head_meta":122,"extra_data":124,"updated_unix":126},105,"en","statistics-at-a-glance-cheat-sheet","STATISTICS AT A GLANCE - cheat sheet","","Descriptive and summary statistics explain how to quantify and visually characterize data sets. The guide outlines three main components: center (mean, median, mode), spread or dispersion (standard deviation, variance, min, max, range, IQR), and shape (symmetric bell-shaped vs skewed left/negative or right/positive). It distinguishes categorical data (nominal, ordinal, with no natural ordering for nominal) from quantitative data, and links nominal vs ordinal to appropriate measures. It also matches data types to charts such as bar charts for blood type and histograms for blood pressure.",{"@graph":63,"@context":119},[64,80,102],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":51,"@type":70,"position":76},"https://docshare.wps.com/template/general/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/statistics-at-a-glance-cheat-sheet/571682/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/statistics-at-a-glance-cheat-sheet/571682.png","ImageObject",442,249,{"name":88,"@type":89},"How to eat","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-23","2026-10-13",true,{"@type":98,"interactionType":99,"userInteractionCount":101},"InteractionCounter",{"@type":100},"ViewAction",7,{"@type":103,"mainEntity":104},"FAQPage",[105,111,115],{"name":106,"@type":107,"acceptedAnswer":108},"What are the three main parts of descriptive and summary statistics?","Question",{"text":109,"@type":110},"They are center (typical value such as mean, median, mode), spread/dispersion (such as standard deviation, variance, min, max, range, IQR), and shape (symmetric bell-shaped vs skewed left/negative or right/positive).","Answer",{"name":112,"@type":107,"acceptedAnswer":113},"How are categorical data and quantitative data different?",{"text":114,"@type":110},"Categorical data fit defined groups and are divided into nominal or ordinal types, while quantitative data are numeric measurements. The guide also notes that nominal groups have no natural ordering, unlike ordinal groups that have a natural order.",{"name":116,"@type":107,"acceptedAnswer":117},"When are bar charts and histograms appropriate?",{"text":118,"@type":110},"Bar charts are used for categorical group examples like blood type. Histograms are used for continuous or measurement data examples such as blood pressure classification.","https://schema.org",{"og:url":78,"og:type":121,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":123,"canonical":78},"index,follow",{"doc_id":125,"site_id":56},571682,1792012877,{"code":4,"msg":5,"data":128},{"doc_id":125,"user_id":129,"nickname":88,"user_avatar":130,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":61,"doc_content":131,"file_id":132,"file_url":133,"file_type":134,"file_size":135,"view_count":101,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":73,"language":136,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":61,"update_tm":140,"read_time":9},962093541613,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","| DESCRIPTIVE/SUMMARY STATISTICS\u003Cbr>Discipline of quantitatively describing the main features of a collection of data  Numerical and graphical summaries used to characterize a dataset |  |  |  |\n| --- | --- | --- | --- |\n| The three main measures are | | CENTER SPREAD\u003Cbr>SHAPE | measure of central tendency---the typical or average value--- (mean, median, mode)\u003Cbr>measure of dispersion or variability of the data--- (standard deviation, variance, min, max, range) symmetric or skewed data--- (bell-shaped, normal curve, left/negative skewed, right/positive skewed) |\n\nThe tools used for describing a collection of data are dependent on the nature of the data ----- Two main data types:  \nCATEGORICAL DATA (aka… qualitative) or  QUANTITATIVE DATA (aka... numeric or measurement)  \nCategorical Data Fit into Defined Groups ----- Two types of categorical data:  \nNOMINAL DATA or  ORDINAL DATA (aka…ranked data)  \nGROUPS HAVE NO NATURAL ORDERING Examples: gender, race, blood type, eye color, political affiliation, country of residence  \n\n| Measures of Center:\u003Cbr>MODE = category w/ largest count |\n| --- |\n| Measures of Spread – not germane with nominal data |\n| Shape – not germane with nominal data |\n\nO A B AB  \nBar Chart / Bar Graph for Blood Type  \nGROUPS HAVE A NATURAL ORDERING  \nExamples: satisfaction level (Likert scale), educational level, shirt size, medical condition (good, fair, serious, critical)  \n\n| Measures of Center:\u003Cbr>MEDIAN = category containing middle value MODE = category with largest count |  |  |\n| --- | --- | --- |\n|  | Measures of Spread\u003Cbr>| MIN = minimum category MAX = maximum category RANGE = min cat. to max cat.\u003Cbr>IQR = middle 50 percent of the data |\n| Shape – seldom used (can be problematic due to possible unequal or unquantifiable changes/differences in magnitude among/between categories) |  |  |\n\nHistogram for Blood Pressure Classification  \nContinuous-data that have an infinite number of real values and there are no spaces/gaps between values (rounded to a specified precision) EXAMPLES: BP, temperature, BMI, height, weight, blood serum level  \nDiscrete-data that have a finite number of values within a given interval and there are spaces/gaps between values (typically counts)  \nEXAMPLES: test score, pages in a book, population of a country, \\# of trees in a forest  \n\n| Measures of Center |  |  |  | | MEAN = arithmetic average MEDIAN = middle value MODE = most numerous value |\n| --- | --- | --- | --- | --- | --- |\n| Measures\u003Cbr>of\u003Cbr>Spread | |  | STANDARD DEV = average distance from center VARIANCE = (Standard deviation)2\u003Cbr>MIN = minimum value\u003Cbr>MAX = maximum value RANGE = maximum - minimum |  |  |\n| Shape\u003Cbr>|  | SYMMETRIC – bell-shaped? if yes, is it normal? SKEWED – left/negative right/positive |  |  |  |\n\n(Mean > Median > Mode) (Mean \u003C Median \u003C Mode)  \nNo Skew / Symmetric  \n(Mean = Median = Mode)","cbCailZh1wjM1EVW","https://ap.wps.com/l/cbCailZh1wjM1EVW","pdf",383207,"English","# Descriptive and Summary Statistics\n## Center, Spread, Shape\n## Data Types and Matching Measures\n## Chart Types for Data","[{\"question\":\"What are the three main parts of descriptive and summary statistics?\",\"answer\":\"They are center (typical value such as mean, median, mode), spread/dispersion (such as standard deviation, variance, min, max, range, IQR), and shape (symmetric bell-shaped vs skewed left/negative or right/positive).\"},{\"question\":\"How are categorical data and quantitative data different?\",\"answer\":\"Categorical data fit defined groups and are divided into nominal or ordinal types, while quantitative data are numeric measurements. The guide also notes that nominal groups have no natural ordering, unlike ordinal groups that have a natural order.\"},{\"question\":\"When are bar charts and histograms appropriate?\",\"answer\":\"Bar charts are used for categorical group examples like blood type. Histograms are used for continuous or measurement data examples such as blood pressure classification.\"}]","STATISTICS AT A GLANCE - cheat sheet | PDF",1791923099]