Qualitative_Methods_and_Analysis

Unit 1 - Fundamentals of Statistics Abstract This document will study AIU (American Intellectual Union) statistical data practicing one part of qualitative data and one part of quantitative data. It will explain the steps of gaining the outcome and provide the end user in company of visuals that will assist the understanding of the statistical data. . Introduction Descriptive statistics is able to possess countless elements that influence the outcome of a report. Retaining the data coordinated is important to every person. Labeling and classifying the dual forms of descriptive statistics is crucial. Labeling or miscalculate quantitative data is able of changing then consequences. Beneath is a halt of my knowledge of descriptive statistics. Chosen Variables Practicing the statistical data source, the quantitative data I selected is intrinsic and the qualitative data I selected is position. The qualitative data provide 3 scales of work, human supply, data equipment and or knowledge and management. The quantitative data is a dimension or quantity of job satisfaction, number1 as the lowest and 7 as the highest. The intrinsic measurement is in regards the functions of work. I selected these choices because I have performed in all of these places; I was delighted and obtained the main satisfaction out of the management job. It seemed to be the main of demanding and fulfilling. Difference in variable types Qualitative data is an identification number provided to recognize explanatory data. The number provided shows a key that provides the explanatory value. The number for a fact has no numeric value. But, the identification number is practice to measure the way of the explanation. Way or manner/mode is the frequency where a number is performed. Quantitative variables possess genuine numeric value. The numbers performed in quantitative data are able to be measured or similar to measurable data. In company of this measurable data means, medians, modes and standard deviation are available to perform and develop fast suggestion/ citations on assume or imagine data. Mean is the average of data chosen, median is the middle data set of a numerically organized data set. The mode indeed is the frequency or amount of times data is submitted. Standard deviations are the assumed or imagine variable of a set of data. It is a payment of high or low thinkable from the mean. Whenever we performed qualitative description statistics, the discoverer has no numeric value. The discoverer of the explanation can be all number. However, commandingly possess the equal value. In company of quantitative discoverers, the numbers stand for a numeric value. Modifications to the discoverer will modify the total outcome of the statistic. Based on the Editorial Board (2011), descriptive statistics are created to respond few or several questions, frequency, dispersion, position and tendency. These functions for dual forms of variables since dual are available to be citrated or ranked across the sum of distribution lacking discoverer or identifiers. Descriptive statistics: Qualitative variable |KEY TO SURVEY | |  |  | |Demographics | |  |  | |Gender | |1 |Male | |2 |Female | |Department | |1 |Human Resources | |2 |Information Technology | |3 |Administration | |Position | |1 |Hourly Employee (Overtime Eligible) | |2 |Salaried Employee (No Overtime) | Explanation of descriptive statistics The descriptive statistics on top are performed to recognize variables elements of a set of data. The top data is available for thinkable elements during the gain of statistical data. These elements are available in addition to provide us frequency sharing data at the time of being studied. I suggest performing numerical value in company of alphabetical value. During the make up of the information for gender, the evaluator could fail to recall 1= Mans and 2=Women’s and require to search the key. Writing 1=Women 2+Mans would familiarize to what gender arrive first in the alphabet Descriptive statistics: Quantitative variable |Age | |1 |16 - 21 | |2 |22 - 49 | |3 |50 - 65 | |Tenure With Company | |1 |Less than 2 years | |2 |2 to 5 years | |3 |Over 5 Years | |  |  | |Four Survey Measures | |  |  | |SURVEY MEASURE #1 OVERALL JOB SATISFACTION (Scale 1-7) | |1 = Least Satisfied | |7 = Most Satisfied | |SURVEY MEASURE #2 INTRINSIC JOB SATISFACTION (Scale 1-7) | |1= Least Satisfied | |7= Most Satisfied | |SURVEY MEASURE #3 EXTRINSIC JOB SATISFACTION (Scale 1-7) | |1 = Least Satisfied | |7 = Most Satisfied | |SURVEY MEASURE #4 BENEFITS (Scale 1-7) | |1= Least Satisfied | |7= Most Satisfied | |  |  | Explanation of descriptive statistics The top quantitative descriptive statistics provide us numerical value for each identification number. During this information is accumulated. It commands to say the means, median, mode, dispersion and thinkable standard deviation on few sets of Information. The outcome may provide a genuine data that tells coworkers age 22-49 that have been performing here for 2-5 years illustrate to be delighted and satisfied in company of the advantage of their work, next write the additional descriptive statistics in numerical series. I suggest that AIU discover the age range of their coworker’s and performed 10 year augmentations. In addition, suggest the equal for tenure. Pass 5 years leave behind many of unidentified data or not recognize outliers Chart/Graph for qualitative variable [pic] |Position |Bin |Frequency | |Hourly |1 |56 | |Salary |2 |22 | |  |More |0 | Description of Chart The chart say to us of the 78 people evaluated, 56 of them performed in human resources, 22 performed in information technology and 0 performed in administration. The histogram provides us a visual of those measurements. Below the Histogram, our discoverers or Identifiers are 1, 2, and 3 what stand for the position illustrated in the key next to it. The frequency is the quantity of times the position was recorded in the evaluation. Chart/Graph for quantitative variable [pic] |Bin |Bin |Frequency | |0 |1 very unsatisfied |0 | |1.1 |2 |0 | |2.1 |3 |7 | |3.1 |4 satisfied |0 | |4.1 |5 |21 | |5.1 |6 |45 | |6.1 |7 very satisfied |5 | |  |Level |0 | Explanation of standard deviation and variance A standard deviation is the thinkable variance from the mean of a set of data. The change is how much they differ. An assume automotive battery life is 5 years. Few have been discover to last just 3 years and few have lasted 7 years. The standard deviation is 4years in company of a difference of more or less 2 years. On assumption that the sharing of the information is wide the deviation will be wide what create the difference wide. Deviation tells continuing (Murray, 2012). Importance of charts and graphs Charts and graphs add visual aid to comprehend statistical data. They in addition, make a Fast visual citation for information citation. Pie charts and graphs grant us to visually tell or read Calculated information that on daily basis grab allot to read by searching at the numerical Outcome of statistics and tell difference to equaled data. . Conclusion The key perform explained statistics is to obtained the key. Lacking a key the data is pointless to all. However, the evaluator. Pie charts and graphs provide the end user a visual comprehension of the gather data and re place the connection of the data in a smooth way. References Editorial Board (2011), Elementary Statistics. (1st ed). Schaumburg: Words of Wisdom, LLC Murray, L. (2012). Chat posting. Retrieved from AIU Online Virtual Campus. First Week Chat-APA. Quantitative Methods and Analysis: BUSN311-1202B-12 website.