1. Using the summary statistics and visual inspection of the histogram, describe the late baggage rates during the study period. Answer these questions: What is a typical value? How spread out are the data? What is the shape of the distribution? Are there outliers?
2. Using the 4 simple run chart rules from the Perla, Provost and Murray paper, summarize the results. Specifically, is there any evidence of non-random patterns in the data? And if so, what are they? [There are 25 observations and 22 runs about the median.]
3. Using the information from the run chart and the Minitab output that shows late baggage rates by shift, what should the improvement team consider as some next steps in planning their improvement project?

Section 3. Rates of late luggage delivery. A regional airline company wants to reduce the number of checked bags that do not arrive at the passenger's final destination on the same flight. As a first step in planning an improvement project, the improvement team collects data from a major hub over the course of 26 days. They track the count of late bags for each of two shifts per day. Since the number of checked bags per shift can vary, they report the rate as the number of late bags per 1,000 checked bags. Here are the summary statistics and histogram of the rates of late bags during the baseline data collection period: Statistics Variable N N* Mean SE Mean StDev Minimum Q1 Median Q3 Maximum Rate 25 0 3.888 0.262 1.310 1.800 3.050 3.800 4.750 7.500 Histogram of Rate Frequency RateHere is the run chart: Run Chart of Rate 5 Rate Wwwww 2 10 12 14 16 18 20 22 24 Observation Since the improvement team is collecting daft for each of two shifts per day, they decide to examine rates by shift using this dot plot and set of statistics by shift: Statistics Variable ShiftTime N N* Mean SE Mean StDev Minimum Q1 Median Q3 Maximum Rate 13 0 2.992 0.196 0.706 1.800 2.200 3.200 3.500 3.900 12 4.858 0.320 1.107 3.000 4.225 4.750 5.150 7.500 Shift Time 1 2 2.4 3.2 4.0 4.8 5.6 6.4 7.2 Rate