Statistical Process Control Paper

Statistical Process Control Paper

During the first week of this course a flowchart was compiled of my daily evening routine. The evening routine involved a process that discussed excessive television watching that consumed gobs of time. The main objective for completing a flowchart was to discuss ways that my time may be exercised differently, eliminating possible bottlenecks. Bottlenecks for the daily routine were discussed in week three of the course. Bottlenecks demonstrate potential barriers that affect me at the workplace and at home. A process is no more than the steps and decisions involved in the way work is accomplished (Handbook, 2011). Every day our lives revolve around processes whether we realize it or not. For example, some processes are natural for most people such as getting out of bed, brushing teeth, eating daily, allocating budgets, or assisting individuals. Statistical process control is an application of statistical methods and procedures (such as control charts) to analyze the inherent variability of a process or its outputs to achieve and maintain a state of statistical control, and to improve the process capability (Dictionary, 2011). The statistical control process that involves my evening routine will be discussed and ways to eliminate time that may be wasted. An explanation will be portrayed on control limits with data to support. Also discussed are seasonal factors and confidence intervals.

Control limits
Determining how to set control limits I would to have ample history of the process. The total time it normally takes me in the evening from the time I get home until the time I lay to rest at bedtime is approximately four hours. During that four-hour period and most of the time until I fall asleep the television is on about six hours. I plan on reducing in the evening the total time that I watch television by half. Therefore, the new control limit is three hours and possibly less. Freeing up half the time in the evenings allows my operating time to be more effective. A control chart is a chart used to monitor the quality of a process (Finn, 2011). On average according to Nielson is the rise of TV that is consumed and the history for one year. (TVPC, 2011). Based on the above chart the amount of TV watched in my home is about average. However, listed below is a chart on how much television I consume for a one-month period and how time was controlled and decreased.

Seasonal factors
During week one of the class I collected data how seasons may affect ones regular routine. Some people are depressed by seasons and that may cause more television and food consumed both are unhealthy habits. The average household watches about four hours of TV each day, 28 hours a week. By the age of 65 that person will have watched about nine years of TV that is wasted time. This affects the seasons because watching much TV makes one unhappy and insane. Psychologists found that joyous people socialize, read, and have sex more when less television is watched. A type of depression called seasonal affective disorder affects some people during the winter when they do not get enough sunlight because they are glued to the TV set (Tyrell, 2011). Currently September 5, 2011 is Labor Day how this day may affect some because some individuals have traveled, some have family or friends visiting, and others are celebrating by attending the beaches, or barbequing. The interactions are perfectly fine and normal because it permits time for outdoor activities, exercise, and socializing. Even though Labor Day is not a season it is in the summer a time for fun and relaxation.

Confidence Intervals
Confidence intervals are a statistical range with a specified probability that a given parameter lies within the range (Answers, 2011). Confidence intervals range around measurements to convey and show how precise the measurements are. For example, the population standard deviation of watching television is s = 8.0 given a 95% confidence interval. The 95% confidence interval may be for the mean weekly TV watching by women and men. In this particular study was conducted by women and men who participated in a particular region during a cross-sectional study to determine obesity. Other important measures are height and weight conducted during home interviews and obese people spent more time watching TV and less time active. Obese compared to non-obese in the multivariate analysis: (mean +/- s.d.: 3.6 +/- 1.5 h/day) than non-obese ones (3.0 +/- 1.4 h/day), and less sleeping time (Torres, 2011).

In conclusion, watching television is a good for an individual. TV is good in a way that relaxes many and provides some intellect. The point that I intend to get across that too much television is not healthy. Too much television has numerous effects on different individuals based on the type of shows watched and how much is consumed. For example, if a child growing up watches to many violent shows the chances are they may be violent odds are greater than a child who spends time watching discovery or cartoon channels. My statement may seem judgmental but statistics are factual.

References, (2011), Reference Answers: Confidence Interval, Retrieved September 5, 2011 from
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Handbook, (2011), Basic Process Improvement, Retrieved September 4, 2011 from
Finn, K. (2011), How to Calculate Upper & Lower Control Limits, Retrieved September 4, 2011 from
Torres, V. (2011), Time Spent Watching Television, Sleep Duration and Obesity in Adults Living in Valencia, Spain. Retrieved September 5, 2011 from
TVPC, (2011), TV Viewing Figures Reach all Time High, Retrieved September 4, 2011 from
Tyrell, M, (2011), How to Watch Less TV, Retrieved September 5, 2011 from