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Describing Data Charts and Graphs. Lecture Objectives You should be able to: 1.Define Basic Terms 2.Recognize Types of Data and Data Scales 3.Draw appropriate.

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Presentation on theme: "Describing Data Charts and Graphs. Lecture Objectives You should be able to: 1.Define Basic Terms 2.Recognize Types of Data and Data Scales 3.Draw appropriate."— Presentation transcript:

1 Describing Data Charts and Graphs

2 Lecture Objectives You should be able to: 1.Define Basic Terms 2.Recognize Types of Data and Data Scales 3.Draw appropriate graphs based on type of data and type of analysis desired. 4.Interpret the graphs

3 Basic Terms 1.Data, Information, and Knowledge 2.Populations and Samples 3.Variables and Observations Types of Data: 1.Categorical and Numerical 2.Cross Sectional and Time Ordered

4 Data, Information, and Knowledge Data Information Processing Analysis Reports Application Meaning Relevance Knowledge

5 Populations and Samples Sample: Subset of collection Described by Statistics Population: Collection of all possible entities of interest Described by Parameters Statistical Inference Art and science of using samples to make conclusions about populations.

6 Variables and Observations Entity Height (inches) Weight (pounds) Age (years) Sex (Category) Person 1 Person 2 Person 3 * 67 61 72 * 170 120 220 * 33 38 62 * Male Female Male * OBSERVATIONSOBSERVATIONS VARIABLES Measurement

7 Types of Data: Categorical and Numerical CategoricalNumerical

8 Data Scales Data are generally classified into four types: 1. Nominal – Categorical data 2. Ordinal – shows ranks, intervals may vary 3. Interval – intervals are constant, arbitrary 0 4. Ratio – Numeric data with a real 0 value. Ordinal, Interval and Ratio scales are all Numeric data.

9 Types of Data: Time Series and Cross-sectional Population Month(Millions) 190056 191058 192060 193065 194076 195084 196095 1970120 1970 PopulationGDPGender Country(Millions)$ BillionRatio USA1605750.998 China8001551.105 India600 Nigeria100 Japan120 Canada30 Variable(s) over time Variable(s) at one point in time across multiple entities (countries in this case)

10 Numeric Data (Interval or Ratio): Frequency Tables A Frequency Table showing a classification of the AGE of attendees at an event. Relative ClassFrequency Percent 10 to 2030.1515 20 to 3060.3030 30 to 4050.2525 40 to 5040.2020 50 to 6020.1010 201.00100

11 Frequency Histograms A graphical display of distribution of frequencies

12 Developing Frequency Tables and Histograms 1.Sort Raw Data in Ascending Order: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 2.Find Range: 58 - 12 = 46 3.Select Number of Classes: 5 (usually between 5 and 15) 4.Compute Class Interval (width): 10 (range/classes = 46/5 then round up) 5.Determine Class Boundaries (limits): 10, 20, 30, 40, 50 6.Compute Class Midpoints: 15, 25, 35, 45, 55 7.Count Observations & Assign to Classes

13 Categorical Data: Bar Charts ObsAgeGenderStateSalary 125MFL25 228FSC36 331MGA44 435FGA38 536MSC56 638FFL68 742MSC79 851FFL64 955MGA88 1061FFL71 1162MGA92 1265FSC54 StateFreq FL3 SC5 GA4

14 Categorical Data: Pie Charts StateFreq FL3 SC5 GA4

15 Numeric Data by Category FM FL66.0025.00 GA70.0074.67 SC53.6767.50

16 Bivariate Numerical Data Scatter Plot

17 Two variables, different units Source: http://www.epa.gov/ttn/chief/trends/trends06/nationaltier 1upto2006basedon2002finalv2.1.xls YearCONox 1990154,18825,527 1991147,12825,180 1992140,89525,261 1993135,90225,356 1994133,55825,350 1995126,77824,955 1996128,85924,786 1997117,91124,706 1998115,38024,347 1999114,54122,843 2000114,46522,599 2001106,26321,546 2002109,23521,277 2003107,06220,476 2004104,89219,564 2005102,72118,947 2006100,55218,226

18 Chapter Summary Categorization: Bar, Pie charts Distribution: Stem and Leaf, Histogram, Box Plot Relationships: Scatter Plots, Line Charts Multivariate: Spider Plots, Maps, Bubble Charts


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