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UT Knoxville STAT 201 - Chapter 2

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1Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.Chapter 2 Data “In God We Trust.... all others bring data” - UnknownChapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.2A “Simple” Survey Gender Number of siblings Number of countries ever visited Height Favorite coffee flavor at Starbucks Shoe sizeHow could there be “problems” with responses to this survey?Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.3Class Activity In groups of 2 (or 3), discuss possible “problems” one might have with getting accurate answers to the questions outlined on the previous page. Be prepared to discuss what you and your teammate discussed with the class.Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.4Real Data Can Be “Messy” Different units of measure. Ambiguous questions lead to ambiguous data. Non-response: how will we handle? Seemingly “ridiculous” responses: how will we handle? An important first step in getting meaningful data is carefully planning the data collection activity AND clearly defining the questions.Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.5What Are Data? Data can be numbers, record names, or other labels. Not all data represented by numbers are numerical data (e.g., 1=male, 2=female). Data are useless without their context…Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.6Raw data What does this data tell us? What does it mean?Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.7Data in a context When the data are organized, given labels, and put into a context, the data gain meaning.Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.8The “W’s” To provide context we need the W’s Who What (and in what units) When Where Why (if possible) and Howof the data. Note: the answers to “who” and “what” are essential.Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.92 Types of Variables A categorical (or qualitative) variable is one whose possible values are given by short descriptors Sex (male/female), eye color (blue/brown), favorite food, birth state, flight status, zip codes Can encode as numbers (e.g. female = 1, male = 2) A special kind of categorical variable is ordinaldata (e.g. data where the order is perceived to have worth, but no units, like “Rate your professor on a scale of 1 to 5”, or ranks in the military)Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.102 Types of Variables (Cont.) A quantitative variable is one whose possible values must be numbers, usually with units  Income ($), height (inches), weight (pounds) Ratio of left thumb length to right thumb length (unitless) Common business analytics quantitative variables are profit, net increase, tax rate, days in inventory, priceChapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.11Counts• Statisticians often count things• Counts can be categorical or quantitative:• Categorical• Natural summary of categorical data is the count of each typeChapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.12Counts (Cont.) Quantitative Number of CDs in a collection Number of classes taken this semester Number of items returned to seller Number of …Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.132 Types of Variables (Cont.) Why do we differentiate between the two types?Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.14Identifying Identifiers Identifier variables are categorical variables with exactly one individual in each category and can look like quantitative variable. Examples: Social Security Number, ISBN, FedEx Tracking Number Should these variables be summarized graphically or numerically? What is the purpose of identifier variables?Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.15Class Activity Answer the questions on the next two pages on your own. After you have finished, compare your answers with your teammate(s). If you have any differences in your answers, discuss why you answered the way you did, and try to come to a common answer. Be prepared to discuss any differences you had with the class.Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.16Types of Data Exercises What type of data are these variables?Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.17Types of Data Exercises Gender Number of siblings Number of countries ever visited Height Favorite Starbucks flavor Shoe size What type of data are these variables?Chapter02 Presentation 1213Copyright © 2009 Pearson Education, Inc.18Chapter Exampletransaction numbertype of gas# of gallonspay at pump?inside food sale?type of paymentGas purchase in dollarsDay of week9853 premium 22 y n Visa 85.58 Mon9211 diesel 26 y n Am Exp 110.5 Tues8875 regular 19 y y Visa 70.11 Tues8824 regular 21 y y Visa 77.49 Fri8313 regular 14 y y MasterCard 51.66 Wed7699 premium 22 n n cash 85.8 Wed7645 diesel 45 y y Am Exp 191.25 Sat3145 diesel 38 y n Am Exp 161.5 Sat2588 regular 17 n y Visa 62.73 Sun2499 regular 22 n n cash 81.18 Sat2325 premium 15 y n MasterCard 58.35 Fri2291 diesel 22 y n MasterCard 92.4 Mon2078 regular 14 y y Visa 51.66 Thur1843 regular 35 y n Visa 129.15 Thur2103 regular 25 n y cash 92.25


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UT Knoxville STAT 201 - Chapter 2

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