Accuracy versus precision; the target analogy High accuracy, but low precision Accuracy describes the closeness of arrows to the bull’s eye at the target center. Arrows that strike closer to the bull’s eye are considered more accurate. The closer a system's measurements to the accepted value, the more accurate the system is considered to be. High precision, but low accuracy •Precision depends upon the equipment used for a measurement and upon the care with which it is made. The way in which a measurement is written down implies something about the expected precision! •“25.000 g” implies a careful measurement made with good equipment. •Repeated measurements would seldom vary from this one by more than ±0.001 g. This measurement is highly repeatable, so it is precise. Accuracy is the degree of truthfulness while precision is the degree of reproducibility.

Significant figures More info. about Sig. Figs. • Significant figures are the digits in a measurement that are known to be precise (will not vary with repeated measurements). Significant figures are a way of maintaining the precision of a measured value throughout a calculation. 35.004 35.003 35.005 A measurement such as 35.004 g contains 5 significant figures because repeated measurements might give the results shown at right. The 3, 5 and zeros are significant because they do not vary. The 4 is significant because it only changes a little. Practice Sheets - online

(5 sig figs) ALL zeroes which are SIMULTANEOUSLY to the right of the decimal point AND at the end of the number are ALWAYS significant.

Three basic rules for determining how many significant figures are in a number: 1. Non-zero digits are always significant. 523.7 has ____ significant figures 2. Any zeros between two significant digits are significant. 23.07 has ____ significant figures 3. A final zero or trailing zeros in the decimal portion ONLY are significant. 3.200 has ____ significant figures 200 has ____ significant figures 2.00 x 102 has ____ significant figures

Error The difference between the experimental value and the accepted value is called the error. % error = | experimental value – accepted value| x 100% accepted value Note: An acceptable error range depends on the application. For example, a 5-10% error range on political polling is commonly accepted as reasonable. A similar rate for surgical error would be appalling and targets tend to be in the 0.1-1% range.

Homework 10, 13, 14, 15 on page 72