College of Administrative and Financial Sciences Critical Thinking Assignment 1: Module-2 & 3 Deadline: End of Week 3 Course Name: Academic Writing and Student’s Name: Research Skills Course Code: RES500 Student’s ID Number: Term: CRN: Academic Year: For Instructor’s Use only Instructor’s Name: Students’ Grade: Marks Obtained/Out of 60 marks Level of Marks: High/Middle/Low Regulations: ? This assignment is an individual assignment. ? Support your submission with course material concepts, principles, and theories from the textbook along with few scholarly, peer-reviewed journal articles. ? Use Saudi Electronic University academic writing standards and APA style guidelines, citing references as appropriate. ? Submit your findings in a 3-4 page document, excluding the title page, abstract and required reference page, which are never a part of the minimum content requirements, in the Assignment Dropbox. ? It is strongly encouraged that you submit all assignments to the Turnitin Originality Check (available under Information folder on your Blackboard) prior to submitting them to your instructor for grading. If you are unsure how to submit an assignment to the Originality Check tool, review the TurnItIn Originality Check – Student Guide for stepby-step instructions. An Overview about Assignment submission Time & grades: Type of Assignment Posting Date Due date Marks Critical thinking Week 2 End of Week 3 60 Grace period* * Grace Period: with accepted excuse (accepted by instructor) with deduction of 10% for late submission 1 3 days Module 2 & 3 Assignment-I: Topic selection & research questions (draft) (60 points) A topic of research should be chosen. It can be either a research paper or a startup concept. Once the topic is finalized, the draft research questions (based on which objectives of the study will be formed) must be developed (not more than three). Each selection must be discussed in detail with logic and rationale. Reasons for the topic should be discussed first followed by discussion on selection of each of the research questions.

Abstract

          In this assignment it is based on research in quantitative methods. There are 3 questions developed which are answered in details and the problem is presented for the questions solved.

Problem.

You are a Business Analyst working for the ABC Ball Bearing company. An hour ago, you sent an order of 74 boxes of your A1 ball bearings to a customer on your delivery truck. You have just found out that your truck is going to go over a bridge that has a weight limit of 11,500 lbs. You need to determine if your truck will safely make it over the bridge. If you determine that the truck cannot make it over the bridge, you will need to call the driver and have him/her turn back.

The plant manager has told you that an empty delivery truck with the driver weights about 8500 lbs.

Question 1

Discuss several types of sampling: e. convenience sampling, random sampling, stratified sampling, systematic sampling or cluster sampling. Discuss which type of sampling is used in this scenario.

         Convenience sampling is a kind of nonprobability sample in which people take samples only when they are ‘convenient’ sources of data (Sampath). It is defined as a method adopted by researchers in which they collect market research data from a group of readily available respondents. It is the most commonly used sampling technique because it is incredibly fast, simple and inexpensive. In many cases, members are easily accessible to join the sample. Convenience sampling is the most common form of non-probability sampling, mainly because it is misused. It is a method of collecting samples by taking samples that are conveniently located in a location or Internet service. We've all seen studies that exploit students in computer science classes. This is misused convenience sampling. A suitable use of convenience sampling would be sampling from Craigslist, Silk Road, or other black-market services to study cybercrime communication. Selecting a set of found communications would adequately represent other criminal communications for which computer science students do not represent the general public very well.

 Random sampling is a kind of sample that means each sample has the same probability as other samples to be selected (Subramani). It is also called probability sampling which allows random sampling. It is one of the simplest forms of collecting data from the total population. In random sampling, each member of the subset has an equal chance of being chosen as part of the sampling process. For example, the total workforce in organizations is 300, and to conduct a survey, a sample of 30 employees is selected to complete the survey. In this case, the population is the total number of employees in the company and the sample of 30 employees is the sample. Each member of the workforce has an equal chance of being selected because all of the employees who were selected to be part of the survey were selected at random. But there is always the possibility that the group or sample does not represent the population as a whole, in which case any random variation is called sampling error.

Stratified sampling is a kind of sampling from a population which can be divided into subpopulations (Wolter). It is considered to be one of the most popular and straightforward methods of collecting data in research. It allows for unbiased data collection, which allows studies to draw unbiased conclusions.

Systematic sampling is a method of sampling that involves the selection of elements from an ordered sampling frame (Sudakar). When the given population is logically homogeneous, this method is applied. It is a type of probability sampling method in which members of a sample from a larger population are selected based on a random starting point but with a fixed periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size. Although the sample population is selected in advance, systematic sampling is still considered random if the periodic interval is determined in advance and the starting point is random.

Cluster sampling is a method of sampling that is used when mutually homogenous but internally heterogeneous clusters are visible in a statistical population (Zinger). In this example it is used stratified random sampling since the given data divides into five strata of equal size. It is defined as a method of sampling in which the researcher creates several groups of people from a population in which they are indicative of homogeneous characteristics and have an equal chance of being part of the sample.

Question 2

Discuss what sampling bias is. Do you believe that using the 30 boxes in your warehouse caused sampling bias?

         Sampling bias: It occurs in a sample where some members of a population are more likely to be systematically selected than others. (Reddy S). It occurs when certain members of a population are consistently more likely to be selected from a sample than others. In the medical field, it is also called evaluation bias. Sampling bias limits the generalizability of results because it poses a threat to external validity, in particular population validity. In other words, biased sample results can only be generalized to populations that share characteristics with the sample.

Bias = E (T) - 

 ;where 

 is a population parameter

E (T) = mean

if E (T) - 

 > 0 then it will be positive bias

if E (T) - 

 = 0 then it is unbiased

if E (T) - 

? <0 then it is negative bias

??????Bias = E (T) - 

 = 40.1833 - 30 = 10.1833 >0

This contains positive bias.

Question 3

What does the central limit theorem state and why is it important to solving this problem? Are the thirty boxes of ball bearings enough to predict the probability of safely going over the bridge?

            Central Limit Theorem: States that ,if we have a population with mean 

and standard deviation 

 and take sufficiently large random samples from the population with replacement, then the distribution of sample means will be approximately normally distributed (2015 & 540-6.). The thirty boxes of ball bearings are enough to predict the probability of safely going over the bridge.