ChE253K Spring09 Lecture11.2

ChE253K Spring09 Lecture11.2 - Midterm #1 Wednesday (March...

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1 ChE 253K Lecture 11 Midterm #1 Wednesday (March 4) in class Coverage: Lectures 1 – 10 and HW 1 – 5 References & Tools: Your calculator Four pages of notes #2 Pencils Scantron Required tables, e.g. t α , will be provided
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2 ChE 253K Lecture 11 ChE 253K Applied Statistics Lecture 11 – Review for Midterm #1
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4 ChE 253K Lecture 11 ChE 253K Applied Statistics Lecture 01 -- Course Description
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5 ChE 253K Lecture 11 Studies: Gathering Data Enumerative: Entire Population Analytical: Sample of Population Valid: Representative Unbiased: Random or Systematic Observational: Passive Experimental: Active Identify (hopefully) all factors Vary select & fix other factors
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6 ChE 253K Lecture 11 Data Types & Qualities Categorical: M, Tu, W, . .. Ordinal: 1 st 2 nd 3 rd ... Numerical (Continuous) Validity Accuracy Precision Resolution
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7 ChE 253K Lecture 11 Exploring 1-D Data with Plots Lecture 02 -- Descriptive Statistics
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8 ChE 253K Lecture 11 1-D Data Model: X = Mean ± SD × NormalRandom Assumptions Plots ?? Stable location and spread unControl Chart Random and uncorrelated Lag Plot X(i) vs. X(i-1) Single, clear center Standard shape Histogram Normal distribution Normal Probability Paper Plot 0 10 20 30 40 50 0 20 40 60 80 Sequence easurements 0 10 20 30 40 50 0 10 20 30 40 50 X(i-1) X(i) 0 5 10 15 20 25 30 <9 11 15 19 21 27 31 Interval Midpoint Frequenc
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9 ChE 253K Lecture 11 Questions: WWWWHY Who? Best person for answers What? Quantity and units Where? Location and sampling When? Changing conditions How? Method and accuracy Why? Question to answer
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10 ChE 253K Lecture 11 (un)Control Chart Stable or trending center & spread? Outliers? A Run Plot plus: Center Line: Mean Spread Lines: Mean ± 2 Std Deviations unControl Chart 0 100 200 300 0 25 50 75 100 Sequence Measurement
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11 ChE 253K Lecture 11 Lag Plots Random or auto-correlated? Plot x(i) vs. x(i–1) Shaped Correlated Shapeless Random Lag Plot 0 100 200 300 0 100 200 300 X(i-1) X(i)
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12 ChE 253K Lecture 11 Strength Of Sequence Dependence Strength of the x(i)-to-x(i - 1) auto-correlation Zero Middling Strong Sources: www,itl.nist.gov
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13 ChE 253K Lecture 11 Histogram Centered distribution? Shape of distribution? Divide data range into 10 equal & exclusive intervals Count data points in each interval = Abs. Frequency Make a bar chart 1 200 9 181-199 12 160-179 33 140-159 24 120-139 12 100-119 2 = 99 Freq Interval 0 5 10 15 20 25 30 35 40 110 130 150 170 190 >200 Weight Range Frequency
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14 ChE 253K Lecture 11 How To Set Class Intervals Divide the entire data range into 5 to 15 class intervals of equal width. Preferably, chose round numbers for interval widths, midpoints (class marks), or endpoints (boundaries). Generally, give intervals one open (< or >) and one closed (≤ or ≥) boundary, e.g., 5≤x(i)<10 or [5,10) (Thereby, interval boundaries do not overlap, and all data fall into one and only one interval or “bin.”) The upper-most and lower-most intervals can have one open-ended boundary, e.g., x(i)≤5.
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15 ChE 253K Lecture 11 Frequency Table Of Weight Data Class Interval Frequency Absolute
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ChE253K Spring09 Lecture11.2 - Midterm #1 Wednesday (March...

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