Applied Statistics and Probability for Engineers

occurred. This plot effectively displays the overall variability in the compressive strength

data and simultaneously shows the variability in these measurements over time. The general

impression is that compressive strength varies around the mean value of 162.67, and there

is no strong obvious pattern in this variability over time.

The digidot plot in Fig. 6-18 tells a different story. This plot summarizes 30 observations

on concentration of the output product from a chemical process, where the observations are

recorded at one-hour time intervals. This plot indicates that during the first 20 hours of oper-

ation this process produced concentrations generally above 85 grams per liter, but that

following sample 20, something may have occurred in the process that results in lower con-

centrations. If this variability in output product concentration can be reduced, operation of this

process can be improved.

EXERCISES FOR SECTION 6-6

6-6 TIME SEQUENCE PLOTS 211

6-57. The College of Engineering and Applied Science at

Arizona State University had a VAX computer system.

Response times for 20 consecutive jobs were recorded and are

as follows: (read across)

Figure 6-18 A digi-

dot plot of chemical

process concentration

readings, observed

hourly.

Leaf Stem Time series plot

9e

9s

9f

9t

9z

8e

8s

8f

8t

8z

8

6

45

2333

0010000

99998

66677

45

23

1

(b) Specifications on product viscosity are at 48 2. What

conclusions can you make about process performance?

6-59. The pull-off force for a connector is measured in a

laboratory test. Data for 40 test specimens follow (read down,

5.3 then left to right).

5.0

9.5

10.1

5.8

6.2

5.9

7.2

10.0

12.2

8.5

4.7

11.2

7.3

6.4

12.4

3.9

8.1

9.2

10.5

Construct and interpret a time series plot of these data.

6-58. The following data are the viscosity measurements

for a chemical product observed hourly (read down, then left

to right).

47.9

47.9

48.6

48.0

48.4

48.1

48.0

48.6

48.8

48.1

48.3

47.2

48.9

48.6

48.0

47.5

48.6

48.0

47.9

48.3

48.5

48.1

48.0

48.3

43.2

43.0

43.5

43.1

43.0

42.9

43.6

43.3

43.0

42.8

43.1

43.2

43.6

43.2

43.5

43.0

(a) Construct and interpret either a digidot plot or a separate

stem-and-leaf and time series plot of these data.

241

258

237

210

194

225

248

203

195

249

220

194

245

209

201

195

255

245

235

220

249

251

238

210

198

199

183

213

236

245

209

212

185

187

218

190

175

178

175

190

(a) Construct a time series plot of the data.

(b) Construct and interpret either a digidot plot or a stem-and-

leaf plot of the data.

6-60. In their book Time Series Analysis, Forecasting, and

Control(Prentice Hall, 1994), G. E. P. Box, G. M. Jenkins,

and G. C. Reinsel present chemical process concentration

readings made every two hours. Some of these data follow

(read down, then left to right).

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