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STATISTIC FOR COMPUTING (CSNB293). MODULE 1 GRAPHICAL DATA REPRESENTATION. Variables. A variable is a characteristic that may changes under different circumstances Examples: Hair color – varies between individuals White blood cell count – varies between individuals
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STATISTIC FOR COMPUTING (CSNB293) MODULE 1 GRAPHICAL DATA REPRESENTATION
Variables • A variableis a characteristic that may changes under different circumstances • Examples: • Hair color – varies between individuals • White blood cell count – varies between individuals • Class schedule – varies between courses • Time to failure of a computer component – varies between different computers • Transmission error rate – varies between different types of transmission cables, length of cable segment
Basic Statistics Terminologies • An experimental unit The individual or object on which a variable is measured. • A measurement The results when a variable is actually measured on an experimental unit • A population a set of entities concerning which statistical inferences are to be drawn • A sample A sub-set of entities drawn from the overall population
Graphical Data Representations • Data can be represented using graphs / charts. • The choice of graph / chart is very much dependent on the nature of data. • A single variable measured for different population segments can be graphed using a pie or bar chart. • A histogram can be used to illustrate several variables measured for different population segment. • A single variable measured over time is called a time series. It can be graphed using a line or bar chart.
Bar Chart Vs. Pie Chart Bar Chart Pie Chart
Histogram Histogram
Line Chart CONSUMER PRICE INDEX Line Chart
Line Chart Vs. Bar Chart LINE CHART BARCHART
4 5 6 7 Dotplots • Plots the measurements as points on a horizontal axis, stacking the points that duplicate existing points. • Example: The set 4, 5, 5, 7, 6
Stem and Leaf Plots • Divide each measurement into two parts: the stem and the leaf. • List the stems in a column, with a vertical line to their right. • For each measurement, record the leaf portion in the same row as its matching stem. • Order the leaves from lowest to highest in each stem. • Provide a key to your coding
4 0 5 6 0 5 5 5 8 8 7 0 0 0 0 0 0 4 5 5 8 9 0 5 4 0 5 6 5 8 0 8 5 5 7 0 0 0 5 0 4 0 5 0 8 9 0 5 Reorder Example of Stem and Leaf Plots The prices ($) of 18 brands of walking shoes: 90 70 70 70 75 70 65 68 60 74 70 95 75 70 68 65 40 65
Interpreting Graphs: Location & Spread Where is the data centered on the horizontal axis, and how does it spread out from the center?
Mound shaped and symmetric(mirror images) Skewed right: a few unusually large measurements Skewed left: a few unusually small measurements Bimodal: two local peaks Interpreting Graphs: Shapes
No Outliers Outlier Interpreting Graphs: Outliers • Are there any strange or unusual measurements that stand out in the data set?
Example of Interpreting Graphs: Outliers • A quality control process measures the diameter of a gear being made by a machine (cm). The technician records 15 diameters, but inadvertently makes a typing mistake on the second entry. 1.991 1.891 1.991 1.988 1.993 1.989 1.990 1.988 1.988 1.993 1.991 1.989 1.989 1.993 1.990 1.994
STATISTIC FOR COMPUTING(CSNB293) GRAPHICAL DATA REPRESENTATION --END--