Statistics and Qualitative Analysis - Essay Example

Statistics and Quantitative Analysis To acquire knowledge about (social) peers, I would most probably ask the following in survey: (a) How many hours do you spend surfing the net for the purpose of social networking (as in Facebook or Tweeter) in a week? _____ I don’t have an account on a social network _____ 1 – 5 hours per week _____ 6 – 10 hours per week _____ 11 – 15 hours per week _____ more than 16 hours per week   (b) In your opinion, how many relationships must a person have to be able to say that he or she attains to proper maturity prior to marriage?

Choices: _____ 1 – 4 _____ 5 – 8 _____ 9 – 12 _____ 13 and up For these questions, I suppose it would be appropriate to use the interval level of measurement being the standard survey rating scale for the sake of ranking data and to figure the precise differences between units of measure based on predetermined intervals. Out of the results or answer data gathered, the extent of the person’s sociability may be inferred as the behavioral information obtained through the first question would indicate that internet users with large number of hours to spend on social networking most likely possess several friends to communicate with compared to those with less hours of internet surfing.

Similarly, an inference of whether an individual is mature or immature may be drawn according to the estimates provided in the second question. Sources: Bluman. Elementary Statistics (A Step By Step Approach). 8th edition. “Types of Survey Questions.” Retrieved from http://gk12.harvard.edu/modules/SurveyQuestionTypes.pdf on July 10, 2012. (2) Data Presentations Histograms or bar graphs are widely utilized as ‘quality improvement tools’ by representing data through varying rectangular column heights in which the frequencies projected from along the vertical axis are plotted against horizontal range of equal intervals.

Through these fundamental features, analysis of product quality comes with ease for manufacturing reports depend upon histograms to keep track of how often defects occur within a specified timeframe. Hence, the charting process of detecting product defects may be carried out by first counting a number of data pints with reference to the number of defective units found, summarizing the collected data on a tally sheet, and identifying the range. Construction of histogram proceeds with determining interval width out of the known number of intervals.

Then, the counting and plotting of the number of points in each interval makes the crucial step that explicates how such histogram can be taken significant advantage of in evaluating whether or not the standard quality for a product is achieved. Other useful statistical graphs include frequency polygons, ogives, Pareto chart, time series graph, and pie graph. Sources: LeanMan. “Histograms:: Bar Charts:: Quality Improvement Tools.” HubPages. Retrieved from http://leanman.hubpages.com/hub/Histograms-Bar-Charts-Quality-Tools on July 10, 2012.

“Basic Tools for Process Improvement.” Retrieved from http://www.saferpak.com/histogram_articles/howto_histogram.pdf on July 10, 2012. (3) Probability In the business world, the chief role of probability is signified in evaluating risks derived from financial and decision-making terms. Since probability, by simple definition, refers to the chance of an event taking place, then one concrete instance of its application in manufacturing industry would be on determining the regional capacity and requirement for production.

This particularly aids manufacturers to locate strategic sites on which to establish a firm or plant such as if a region is figured to have spots rich in oil or gas reserves then a petroleum refinery may be set up within the area to target optimum refined yields with confidence that this condition is favorable for revenue increase. Hence, there is high probability of generating several large volumes of refined petroleum products, increasing the likelihood of achieving maximum profits for the company that, through probability computations, manages to find initially a field with adequate quantity of resources.

Sources: Gish, Will. “Probability and Manufacturing.” Demand Media. Retrieved from http://smallbusiness.chron.com/probability-manufacturing-18212.html on July 11, 2012. Bluman. Elementary Statistics (A Step By Step Approach). 8th edition. (4) Discrete and Continuous Probability On estimating my annual employee turnover, as a manager, I would use discrete variables for this task accounts for a number of employees to be replaced and an employee count makes a finite instead of a measurable value.

Such discrete variables are essential for discrete probability which is utilized in the determination of the percentage of employee turnover. An applicable general formula would be one based on the ‘uniform probability measure’ given by: which refers to the probability of event E occurring within a sample space S. In my case, S would stand for the average number of employees in the year of interest then the rest of the data would consist of E1 being the number of employees who leave voluntarily and E2 as the number of employees who leave involuntarily.

So, the probability that workers leave the company voluntarily is represented by P(E1) = |E1| / |S| otherwise, the probability of workers leaving due to other reasons or interventions beyond themselves is expressed as P(E2) = |E2| / |S|. Sources: “Chapter 6: Discrete Probability.” Retrieved from http://rumba.biosci.ohio-state.edu/Yuan_notes_fa10.pdf on July 12, 2012. McKenzie, Grant. “How to Calculate Staff Turnover.” Retrieved from http://www.ehow.com/how_5098367_calculate-staff-turnover.

html on July 12, 2012. (5) Sampling and Statistical Inference The poll (June 14-17, 2012) was made on the basis of stirring awareness regarding the state of natural environment. It is intended to estimate basic perceptions (with options: better, worse, about the same, and unsure) of the environment as it is currently experienced compared to how it had been a decade back. Additionally, two survey questions were incorporated asking responders about the impact of human activity (whether positive, negative, or unsure) over the 10-year span as well as how the poll participants envision the natural environment a decade later using the same options used in the first survey question.

Poll’s sample size is N = 1,002 adults nationwide whereas the margin of error = ±3.5. Based on the indicated poll results for each choice, I believe that outcomes reflect public opinion for feedbacks out of the sample size are diverse, being distributed across the three crucial options in which there appears logical order of economy in the sense that the least percentage who opted ‘better’ may be claimed to have come from middle to upper-class people who could afford to see beautiful places of nature whereas the highest percentage of ‘worse’ could have reasonably come from the ones along the poverty line, having normally encountered unpleasant views of the environment.

Sources: “Environment.” Polling Report Inc. Retrieved from http://www.pollingreport.com/enviro.htm on July 12, 2012. Bluman. Elementary Statistics (A Step By Step Approach). 8th edition.