Module1.doc

16/01/2013 Blackboard Learn Learning Objectives By the end of this module, you will be able to 1. Understand how data are collected. 2. Identify the types and measurement scales of data. 3. Recognize the need to classify data 4. Deal with sensitive responses. What is a Data Set? Data is a collection of numbers and/or attributes of an entity. A data set is a collection of data. Example1: A set of stude nts‟ lifestyle data. The table below shows the data collected from 10 students. The students responded to the five questions on the survey form about the student's lifestyle. Do you bring your How much time (in What is How do you How many course s did own lunch to hours) do you spe nd your Class go to you enroll in this seme Stude nt schoo l? studying? Year? schoo l? ste r? 1 Yes 20.3 Freshman Public 3 transport 2 Yes 12.5 Sophomore Drive 5 3 No 10.3 Junior Walk 6 4 Yes 2.5 Junior Drive 4 5 No 0.5 Senior Public 5 transport 6 Yes 7.2 Sophomore Drive 2 public 7 Yes 5.5 Freshman 5 transport 8 No 10.0 Freshman Walk 4 9 No 4.8 Freshman Walk 4 10 Yes 3.2 Freshman Drive 3 The students' responses are called the data describing the students' lifestyle. The responses can be expressed in either numeric (e.g. 20.3,12.5, 10.3, 2.5, etc) or non-numeric (e.g. Yes, No, Freshman, drive, etc.). The numeric values are classified as quantitative data and the non-numeric values are classified as qualitative https://courses.ryerson.ca/webapps/portal/frameset.jsp?tab_tab_group_id=_15_1&url=%2Fwebapps%2Fblack1/11d%2Fexecute%2Flauncher%3Ftype%3DCou… 16/01/2013 Blackboard Learn data. Example2: A set of financial data. Source: http://www.theglobeandmail.com/globe-investor/markets/stocks/ The set of data below showed the latest price listed in the stock exchange and the percent change in price (denoted as % Chg). Company Symbol Late st %Chg Bombardier Inc. BBD.B-T 5.26 -1.31 Manulife Financial MFC-T 19.19 -0.98 New Gold NGD-T 5.70 6.15 Suncor Energy SU-T 34.53 1.98 EnCana Corp. ECA-T 32.67 2.13 Yamana Gold Inc. YRI-T 10.45 2.75 Western Coal WTN-T 6.75 0.90 Talisman Energy TLM-T 17.41 1.34 Lundin Mining LUN-T 5.31 0.95 Osisko Mining OSK-T 9.50 5.44 Example3: A set of tempe rature data: Source: http://www.theweathernetwork.com/statistics/temperature/cl6158350 Tempe rature (°C) in Toronto Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average -4.2 -3.2 1.3 7.6 14.2 19.2 22.2 21.3 17 10.6 4.8 -0.9 Average high -1.1 -0.2 4.6 11.3 18.5 23.5 26.4 25.3 20.7 13.8 7.4 1.8 Average low -7.3 -6.3 -2 3.8 9.9 14.8 17.9 17.3 13.2 7.3 2.2 -3.7 Record maximum daily high 16.1 14.4 26.7 32.2 34.4 36.7 40.6 38.9 37.8 30 23.9 19.9 Jan. Feb. Mar. Apr. May. Jun. Jul. Aug. Sep. Oct. Nov. Dec. Date 25 25 28 22 18 30 08 13 02 07 01 03 1967 1976 1946 1842 1962 1964 1936 1918 1953 1963 1950 1982 Record minimum daily low -32.8 -31.7 -26.7 -15 -3.9 -2.2 3.9 4.4 -2.2 -8.9 -20.6 -30 Jan. Feb. Mar. Apr. May. Jun. Jul. Aug. Sep. Oct. Nov. Dec. Date 10 05 03 01 06 10 12 18 22 31 30 29 1859 1855 1868 1923 1854 1842 1843 1855 1842 1844 1875 1933 Data Collection https://courses.ryerson.ca/webapps/portal/frameset.jsp?tab_tab_group_id=_15_1&url=%2Fwebapps%2Fblack2/11d%2Fexecute%2Flauncher%3Ftype%3DCou… 16/01/2013 Blackboard Learn As you can see from the examples above that data come in many forms. How do you collect the data? Data may be collected from two primary sources, namely primary or secondary. A. Primary Data: Data collected from the primary source is known as primary data. The primary data involves raw data (or original data) that are collected directly from respondents (or participants of a survey) using various instruments such as interviews, surveys (or questionnaires), observations and laboratory experiments. B. Second ary Data: Data collected from secondary source is known as secondary data. The secondary data are data that have been collected by another party. The first hand use of the data is called primary data. When primary data is used, it becomes secondary data. Secondary data is also recognized as “recycled” data. Examples of secondary sources are databases from Statistics Canada (http://www.statcan.gc.ca/), CANSIM (Statistics Canada time-series), GDSourcing (Government Data Sourcing) and etc. Why do you need data? You need data to make inform decision. Data help you make better decision. Thisexampleisusedtoillustratethatdataisneededtomakebetterdecision. Suppose you are the Customer Service manager of a retail company and recently you have received frequent complaints about your products and services. Because of the intense competition, you do not want to lose your customers to your competitors. In order to improve your customer service, you must know what your customer like and dislike about your company products and services. What kind of data should you collect to improve your service quality? Classification of Data You can classify data into two types, as shown in Figure 1: 1. Quantitative data (also known as numerical data) 2. Qualitative data (also known as categorical data) https://courses.ryerson.ca/webapps/portal/frameset.jsp?tab_tab_group_id=_15_1&url=%2Fwebapps%2Fblackboard%2Fexe3/11%2Flauncher%3Ftype%3DCou… 16/01/2013 Blackboard Learn Quantitative data Quantitative data is either discrete or continuous. Quantitative data consist of values that can be expressed numerically and can be discrete or continuous. Discrete numerical data are whole numbers (often determined by counting) and continuous numerical data are real numbers (often determined by measuring). EXAMPLE: Using the set of students‟ lifestyle data in Example 1, the answers (or responses) to question “How much time (in hours) do you spend studying?” is classified as quantitative CONTINUOUS data. QUANTITATIVE CONTINUOUS data How much time(in hours) do you spe nd studying? 20.3 12.5 10.3 2.5 0.5 7.2 5.5 10.0 https://courses.ryerson.ca/webapps/portal/frameset.jsp?tab_tab_group_id=_15_1&url=%2Fwebapps%2Fblackboard%2Fex4/11e%2Flauncher%3Ftype%3DCou… 16/01/2013 Blackboard Learn 4.8 3.2 The answers (or responses) to question “How many courses did you enroll in this semester?” is classified as quantitative DISCRETE data. QUANTITATIVE DISCRETE data How many course s did you enroll in this semeste r? 3 5 6 4 5 2 5 4 4 3 Qualitative data Qualitative data consist of data values that describe the characteristic or feature of the item. Therefore the data values are non-numeric in nature. For example, a study asking your opinion of the instructor teaching as excellent, good, fair, poor. “Excellent”, “good”, “fair” and “poor” are non-numeric values. EXAMPLE: Using the set of students‟ lifestyle data in Example 1, the answers to questions “Do you bring your own lunch to school?”, “What is your Class Year?” and “How do you go to school?” are classified as qualitative data. These response s are QUALITATIVE data Do you bring your own lunch What is your How do you go to schoo l? Class Year? to school? Yes Freshman Public transport Yes Sophomore Drive No Junior Walk Yes Junior Drive https://courses.ryerson.ca/webapps/portal/frameset.jsp?tab_tab_group_id=_15_1&url=%2Fwebapps%2Fblackbo5/112Fexecute%2Flauncher%3Ftype%3DCou… 16/01/2013 Blackboard Learn No Senior Public transport Yes Sophomore Drive Yes Freshm