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Published byJessie Hoster Modified over 3 years ago

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**Experimental Errors Kesalahan dalam pengukuran Sumber kesalahan**

Rambatan kesalahan Errors → noise in measured values

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**Can you hit the bull's-eye?**

Three shooters with three arrows each to shoot. How do they compare? Both accurate and precise Precise but not accurate Neither accurate nor precise

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**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?

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**Can all errors be controlled?**

What are some possible things that can be done to minimize errors?

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**Types of (experimental) Errors**

Systematic Error 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.

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**Types of (experimental) Errors**

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

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**Types of (experimental) Errors**

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

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**Types of (experimental) Errors**

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

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**Example: Sources of Error sampling preparation analysis Representative**

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

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**Example: Quantization → Random error**

1 13 1 14

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**Quantization error Timer resolution → quantization error**

Repeated measurements X ± Δ Completely unpredictable

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A Model of Errors Error Measured value Probability -E x – E +E x + E

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**A Model of Errors Error 1 Error 2 Measured value Probability -E x – 2E**

+E x x + 2E

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A Model of Errors

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**Systematic errors → accuracy**

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

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**Most accurate and precise**

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

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**Two students analyzing two different CaCO3 antacid tablets**

True value Student 1 Student 2 Label value 500 mg 750 mg Mean 463 mg 761 mg Std. dev. 20 mg 28 mg Which student has the more accurate results? Which student has the greater precision?

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**How are we going to address these questions?**

quantity Student 1 Student 2 % Relative standard deviation asses the precision %Error asses the accuracy

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**calibration marks + one more place**

Always remember to… Make all measurements carefully and check your results or readings a second time. 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

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**Kandungan rhodamin dalam sampel Metode Spektrofotometri**

Metode ESI Metode Spektrofotometri Ulangan 1 2 3 Saos A 0.11 0.25 0.15 0.10 0.17 Saos B 0.22 0.34 0.32 0.38 Berapakah konsentrasi rhodamin pada saos A dan B yang terukur dengan metode ESI dan spektrofotometri? 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? Apa saja sumber systematic dan random errors dalam pengukuran tersebut?

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