Technology Strategy Sampling, Hypothesis Testing And Regression - 825 Words

Technology Strategy: Sampling, Hypothesis Testing And Regression (Essay Sample) Content: Information Technology Strategy Name Institution Date Sampling, Hypothesis Testing, and Regression The collected data constitutes of a sample of the daily activity for a period of 10 days. The data represents the entire period of the month. The data utilized in the calculation and analysis is detailed below: Days Inbound calls (mins) Outbound calls (mins) Total (Mins) Monday 150 120.5 270.5 Tuesday 85.6 200 285.6 Wednesday 90.2 140 230.2 Thursday 120 165.7 285.7 Friday 180 60 240 Saturday 200 120 320 Sunday 210 75 285 Monday 85 94 179 Tuesday 98 70 168 Wednesday 76 150 226 Mean=Total time divided by the sample size ((∑X/n) 270.5+285.6+230.2+285.7+240+320+285+179+168+226=2490 Mean=2490/10=249 Variance=∑(X-Mean)/n Variance=[(270.5-249)^2+(285.6-249)^2+(230.2-249)^2+(240-249)^2+(320-249)^2+(285-249)^2+(179-249)^2+(168-249)^2+(226-249)^2]/10=2,056.325 Standard Deviation=ê ­ Variance (Goos Meintrup, 2016) Standard Deviation=45.35 The mean is decreasing because the sample size has reduced. Nonetheless, the sample size is enough to provide a true reflection of the population. Sampling Stratified sampling selects a proportion from strata of the population using simple random sampling (Lane, n.d). The advantages of using the method are that its probabilistic nature ensures validity of the sample, reduces participant and researcher bias and the even spread ensures greater precision. The disadvantages include, the list of population has to be completed, population should be clearly delineated and it is difficult and time consuming to attain a complete population. The sampling technique used to pick the names is simple random sampling (Hanif, Shahbaz, Ahmad, 2018). This is because, the cards are picked randomly and each name has equal probability of being selected. The sampling plan of the phone company is a random sample. However, it is an equal probability systemic sampling (Hanif, Shahbaz, Ahmad, 2018). A researcher using this technique, begins from a random point and selects every nth subject in the sampling frame. There is a danger of order basis because it does not involve separate random selection. The sampling plan does represent a random sample; because the manager talked only to those who attended the meeting. The people who were not present in the meeting because of one reason or another were excluded. Meetings are normally attended by selected individuals, therefore, it is not a proper random sample. The manager discussed about job satisfaction with a group of 25 employees, who had attended the meeting. Therefore, it is a stratified sample based on a proportion from strata of the population. The sampling plan results in a random sample because the educational expert selected 10 schools randomly. The sampling technique is cluster sampling, which occurs when a random sample is drawn from particular aggregational geographical groups (Hanif, Shahbaz, Ahmad, 2018). The method used is stratified sampling. This is because, the school is separated into similar strata and a fixed proportion from each class was selected to represent the population. Stratified sampling ensures each group is appropriately represented in the population (Uriel, 2013). Stratified random sampling is the best design method to investigate workplace attitudes. The sample size is 100 people, therefore, I would place the employees into sub-groups based on departments or gender. I would then select individuals in a random manner from each designated strata. The population size will cover all the employees while the sample group will be the individuals that will be selected to complete the investigation. It is more credible to include every employee in the organization. It is difficult to avoid the issue of participant bias because the employees are often reluctant to share their dissatisfaction for fear of reprisal. The bias in the study is that the survey is limited to the electronic readers of the newspaper. The sample size cannot provide a true reflection of the population or area of study. The sampling error in the study is that only 3.2% of the participants responded to the survey. Therefore, the writer cannot draw accurate conclusions about the housing market based on this results. 3.2% does not reflect the results that would be obtained from the entire population. The writer based his conclusion on a sample size that negatively impacts the validity of t...