Use this data set to answer the questions. For efficiency, set the problem up in Excel so that you enter the numbers only once. When reporting your numeric answers, omits the units. Remember to use the correct number of significant figures to report your answers.

Label Value

1 95.86 g

2 80.81 g

3 106.51 g

4 98.28 g

5 86.46 g

Now, are the measurements accurate? "Error" is the difference between the measured value and the true value. Error quantifies the accuracy of our measurements. Equation 1.4 gives the positive or negative percent error for any single one measurement.

Calculate the absolute errors for each measurement and then determine the average percent error for the dataset. The true value is 96.51 g.

Next, we want to know if any measurement an outlier? That is, is any measurement so unlikely that we should not use it in our calculations? For this we use Dixon's Q Test. Q is called a "rejection quotient". Table 1.1 in the Lab Manual shows the critical values for Q for 90% level of confidence in the measurement.

We'll go through the procedure one step at a time.

Step 1: Arrange the measurements in order from lowest value to highest value and determine the "Range" of the values: Range = Highest value lowest value.

Step 2: Calculate the "Gaps" between the most extreme values (lowest and highest values) and their next closest measurements, and pick the largest value.

Gap = highest value - second highest, or

Gap = lowest - second lowest.

Step 3: Calculate Q_data = Gap/Range.

Step 4: Look at Table 1.1 and find the critical rejection quotient for 5 measurements.

What is Q_critical?