A) Temperature (B) Electric charge (C) M
4. Zero error of an instrument introduces
KA) systematic error (B) random error (C)
5. 3.310 x 10has significant figures
(A) 6 (B) 4 (C) 2 (D) 1
Section
Answers
Answer:
a is the correct answer from all the options given follow in key. Thank u..
Answer:
Explanation:
Random Errors
Random errors in experimental measurements are caused by unknown and unpredictable changes in the experiment. These changes may occur in the measuring instruments or in the environmental conditions.
Examples of causes of random errors are:
electronic noise in the circuit of an electrical instrument,
irregular changes in the heat loss rate from a solar collector due to changes in the wind.
Random errors often have a Gaussian normal distribution (see Fig. 2). In such cases statistical methods may be used to analyze the data. The mean m of a number of measurements of the same quantity is the best estimate of that quantity, and the standard deviation s of the measurements shows the accuracy of the estimate. The standard error of the estimate m is s/sqrt(n), where n is the number of measurements.
Fig. 2.
Fig. 2. The Gaussian normal distribution. m = mean of measurements. s = standard deviation of measurements. 68% of the measurements lie in the interval m - s < x < m + s; 95% lie within m - 2s < x < m + 2s; and 99.7% lie within m - 3s < x < m + 3s.
The precision of a measurement is how close a number of measurements of the same quantity agree with each other. The precision is limited by the random errors. It may usually be determined by repeating the measurements.
Systematic Errors
Systematic errors in experimental observations usually come from the measuring instruments. They may occur because:
there is something wrong with the instrument or its data handling system, or