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Kesalahan dalam pengukuran Sumber kesalahan Rambatan kesalahan Experimental Errors Errors → noise in measured values.

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Presentation on theme: "Kesalahan dalam pengukuran Sumber kesalahan Rambatan kesalahan Experimental Errors Errors → noise in measured values."— Presentation transcript:

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2 Kesalahan dalam pengukuran Sumber kesalahan Rambatan kesalahan Experimental Errors Errors → noise in measured values

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4 Three shooters with three arrows each to shoot. Can you hit the bull's-eye? Both accurate and precise Precise but not accurate Neither accurate nor precise How do they compare?

5 Measure the diameter of the ball Using a metric stick, determine the diameter of the ball provided. Compare your results with another group. Any problems with your measurement?

6 Can all errors be controlled? Can all errors be controlled? What are some possible things that can be done to minimize errors? What are some possible things that can be done to minimize errors?

7 Types of (experimental) Errors Systematic Error Systematic Error  Result of an experimental “mistake”  Result of an experimental “mistake”  Sometimes called bias due to error in one direction- high or low  Penyebabnya diketahui (known cause)  Operator  Calibration of glassware, sensor, or instrument, etc.

8 Systematic Error Systematic Error  This error can be corrected/ controlled when causes of error are determined, i.e : (a) calibrating all experimental tools and/ (a) calibrating all experimental tools and/ or instruments or instruments (b) controlling skill of experimenter, (b) controlling skill of experimenter, operator etc. operator etc. (c) Cleaning all glassware, bottles, etc (c) Cleaning all glassware, bottles, etc before doing experiments before doing experiments (d) etc… ????? (d) etc… ????? Types of (experimental) Errors

9 Systematic Error Systematic Error  Typically produce constant or proportional nature (slowly varying bias) Constant error influences the intercept. Proportional error influences the slope. y = ax + b

10 Types of (experimental) Errors Random error Random error  Unpredictable, non-deterministic  Unbiased → equal probability of increasing or decreasing measured value Result of Result of  Limitations of measuring tool  Random processes within system  Environmental effect (?), etc Typically cannot be controlled Typically cannot be controlled  Use statistical tools to characterize and quantify Multiple trials help to minimize

11 sampling preparation analysis Representative sample homogeneous vs. heterogeneous Loss Contamination (unwanted addition) Measurement of Analyte Calibration of Instrument or Standard solutions Example:

12 Example: Quantization → Random error

13 Quantization error Timer resolution Timer resolution → quantization error Repeated measurements Repeated measurements X ± Δ Completely unpredictable

14 A Model of Errors ErrorMeasured value Probability -Ex – E½ +Ex + E½

15 A Model of Errors Error 1Error 2Measured value Probability -E x – 2E¼ -E +Ex¼ -Ex¼ +E x + 2E¼

16 A Model of Errors

17 Systematic errors → accuracy Systematic errors → accuracy  How close mean of measured values is to true value Random errors → precision Random errors → precision  Repeatability/reproducibility of measurements Characteristics of tools → resolution Characteristics of tools → resolution  Smallest increment between measured values

18 Graphical methods Scatter plots Scatter plots Most accurate and precise Worst precision Systematic error?

19 Two students analyzing two different CaCO 3 antacid tablets Student 1Student 2 Label value500 mg750 mg Mean463 mg761 mg Std. dev.20 mg28 mg Which student has the more accurate results? Which student has the greater precision? True value

20 quantityStudent 1Student 2 % Relative standard deviation  asses the precision %Error  asses the accuracy How are we going to address these questions?

21 Always remember to… Make all measurements carefully and check your results or readings a second time. Make all measurements carefully and check your results or readings a second time. Read all devices to as many places as possible (significant figures): Read all devices to as many places as possible (significant figures): calibration marks + one more place  A buret, which is calibrated to 0.1 mL, can be read to 0.01 mL.  A thermometer marked every degree can be read to 0.1 degree

22 Kandungan rhodamin dalam sampel Metode ESI Metode Spektrofotometri Ulangan Saos A Saos B Berapakah konsentrasi rhodamin pada saos A dan B yang terukur dengan metode ESI dan spektrofotometri? 2.Berapakah ketelitian dan ketepatan pengukuran rhodamin dengan kedua metode jika konsentrasi rhodamin sebenarnya dalam saos A 0.18 ppm dan saos B 0.24 ppm? 3.Apa saja sumber systematic dan random errors dalam pengukuran tersebut?


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