# BUSN625 discussion response

Help me study for my Business class. I’m stuck and don’t understand.

Hello,

I need four responses of at least 175 words each for the below students discussions for this week. Also in the bold below are the questions the students at answering.

What is data? What is sampling? Explain the importance of sampling from a managerial perspective. Provide examples.

Student one:

What is data? What is sampling? Explain the importance of sampling from a managerial perspective. Provide examples.

From the textbook, we know that data are numerical facts and figures that are collected through some type of measurement process. (Evans, 2013) According to the dictionary, a sampling is the act, process, or technique of selecting a suitable sample.

There are many different methods of sampling, simple random sampling, systematic sampling, stratified sampling, cluster sampling and sampling from a continuous process are some examples. In order to understand the importance of sampling, from a managerial perspective, I think it’s that the data in the sample should do three things:

1. Confirm or disprove what you were thinking.
2. Make you ask more of the right questions.
3. Cause you to act on what you discover. (Jiwa, 2013)

It is also necessary that the sample be random, without any bias, for it to be a good representation of the population. This will help ensure the results are significant and reliable. (Lesson 2)

There are many reasons that a manager would conduct a sampling, they may be performing market research to compare their product to similar products in the market, they may be considering new product development, or trying to determine why there seems to be a change in customer satisfaction. (Jensen, n.d.)

In my job as a finance officer one item, in particular, that falls within my responsibility is the payment of invoices. A consistent problem with this seems to be timeliness. The expected standard is that payment is made within 30 days of receiving the invoice, but there were too many times where payment was delayed resulting in unnecessary interest charges. In order to figure out what the problem was, we conducted a survey. We ensured that the sample was big enough to be a good representation of the companies we purchased from. The results of the survey confirmed that the problem wasn’t with the suppliers (what we had thought). We then asked questions of the invoice clerks and realized that the workload had increased, and we were short one clerk and the one clerk was new and inexperienced. With this data, we reprioritized our staffing requirements and made the invoice clerk a higher priority. We also provided additional training and established an SOP (Standard Operating Procedure) for the payment of invoices. Though we were unable to completely eliminate interest charges, we were able to significantly reduce the interest charges. We were successful because we disproved what we thought was the problem and found the actual issue, by asking the right questions. We then acted on the information.

There are challenges with sampling, such as choosing the correct method and size to ensure it is unbiased and a good representation of the population, but it is worth the effort of the managers, if it is used properly. “The power of data isn’t in the information. It’s what you do with it that matters.” (Jiwa, 2013)

References:

Evans, J. R. (2013). Statistics, Data Analysis, and Decision Modeling. Upper Saddle River: Pearson Education.

Jiwa, B. (2013, June 3). The Story of Telling. Retrieved January 14, 2020, from The Purpose of Data: https://thestoryoftelling.com/purpose-of-data/

Student two:

The role data plays in all areas of the economy is huge. Data analytics has become a topic of discussion in sports, business, and beyond because of the useful information that can be derived from diving deep into numbers to find a picture of results. Data is information “… used in virtually every major function in business, government, health care, education, and other nonprofit organizations” (Evans, 2013).

What this means to me is that data can be anything we do as individuals, or as an entity, that creates a measurable outcome. This measurable outcome provides details that can be traced and calculated to find an enormous number of further outcomes that depend on how and what is being searched for. A simple example of data is when you go to the grocery store and purchase one hundred dollars’ worth of items every other week, of which thirty dollars is in the deli area. The grocery store you purchased from is able to use that information, typically through their rewards cards, to directly market to you with deli specific sales you would be interested in, based on the data.

Sampling, on the other hand, is a means to compile and extract data for specific purposes. This type of data extraction is something that came about because surveying huge amounts of data could not be possible or may take too much time. An example of sampling would be if the Department of Agriculture was interested in the top five vegetables preferred across the country. There are far too many consumers in the country to take a survey and compile all of the data, so they would survey/sample a smaller number of individuals from each state to find an outcome.

From a managerial perspective, sampling is important because of the ability to make decisions based on the data provided by doing it. All managers need to understand where the business is currently and be able to breakdown information that provides details for past, current, and future situations where action can be taken now or in the future.

References

Evans, J. (2013). Statistics, Data Analysis, and Decision Making. (5th ed.). Upper Saddle River, NJ: Pearson Education Inc.

Student three:

What is data?

Research data can be collected and used in a wide variety of ways. “It can consist of numbers in a spreadsheet, it also takes many different formats, including videos, images, artifacts, and diaries.” (Defining Research Data, 2019)

Data can be numbers used in a spreadsheet or an “object as in physical research materials such samples of rocks, plants, or insects.” (Defining Research Data, 2019)

Here are some examples of the formats that data can take:

 Documents (text, MS Word), spreadsheets Lab notebooks, field notebooks, diaries Questionnaires, transcripts, surveys Codebooks Experimental data Films, audio or video tapes/files Photographs, image files (Defining Research Data, 2019) Sensor readings Test responses Artifacts, specimens, physical samples Models, algorithms, scripts Content analysis Focus group recordings; interview notes

Quantitative data is used when a manager wants to quantify a problem, “or address the “what” or “how many” aspects of a research question.” (Qualitative vs. Quantitative, 2019)

Qualitative “data describes qualities or characteristics.” It is collected “using questionnaires, interviews, or observation, and frequently appears in narrative form.” (Qualitative vs. Quantitative, 2019)

What is sampling?

Sampling is a statistical procedure that is concerned with the selection of the individual observation. In sampling, samples are drawn from the population and sample means and population means are equal. There are multiple types of sampling:

• Simple random sampling
• Equal probability systematic sampling
• Stratified simple random sampling
• Multistate stratified random sampling
• Cluster sampling
• Multistate cluster sampling
• Types of non-random sampling
• Availability sampling
• Quota sampling
• Expert sampling
• Analyzing non-response sampling
• Weighting
• Dealing with missing data

The importance of sampling from a managerial perspective, with examples

In the medical field, there are surveys done with every patient. At least the opportunity for feedback is given. Surveys go out in the mail, email, even text. Questions range from how clean was the facility, to how were you greeted? Full surveys have a lot of questions and the text surveys are generally shorter so patients will potentially take the time out to give feedback. The numeric scores are averaged at the end of 60 days to see how patients feel about making the appointment, how the appointments went, the staff, the facility, etc. This type of data is used for a variety of reasons. Department managers use the information about the staff to make improvements or to see if the improvements that were made are working. Facility managers use the information to address the facility maintenance and upkeep. Department heads use this data to determine pay increases and performance evaluations for promotion. Call center managers use this data to improve processes in making appointments and to handle call volume. This can determine staffing levels and hours of operations. These scores are also used nationally to score health care facilities. This gives the hospital presidents the opportunity to see how well their hospital scores nationally; how providers score compared to their peers; and how their specialty clinics compare to other specialty clinics. Healthcare is a business and patients do use these scores to “shop around”.

Reference:

Defining Research Data. Research Guides. (2019). Data Module #1: What is Research Data? Retrieved from https://libguides.macalester.edu/c.php?g=527786&p=3608657

Qualitative vs. Quantitative. Research Guides. (2019). Data Module #1: What is Research Data? Retrieved from https://libguides.macalester.edu/c.php?g=527786&p=3608639

Student four:

Data is information gathered during the business research process. Data is used in every aspect of every major business function (Evans, 2013). Information that is gathered about a business through different channels is data. That data can be analyzed and used to make business decisions.

Sampling is using a fraction of the entire population when using the entire population is not feasible. A sample is understood to be a representation of the entire population (Jensen, n.d.) There are instances when the population is extremely small, and the testing involved is not destructive to the population and therefore the entire population can be sampled (Evans, 2013). In instances where the population is vast, using a sample from the larger population is the best route to use. Management is presented with a variety of decisions that will affect their staff and the business as a whole. Some of the decisions is based upon information that collected and reports that are generated regularly. Many times, there is a vast amount of data that they analyze, and it is not always feasible to come every bit of information. Managers can then utilize sampling in order to get a better grasp on all of the information. They are able to take the sampled date and use that information to make better informed decisions.

A good example would be analyzing the budget. Looking at the budget as a whole would be harder for them to pinpoint whether the monies are being utilized properly. If a sample is taken, like maybe from the least important expenditures, they will be able to narrow down where money is being wasted and where they should cut back. Another example would be if someone is managing a call center where all call times are documented. A sample of all the calls can be taken to see the length of each call and what time of day the most times is being spent with each call. That could help a manager decided when they need more or less staff based upon call volume and length of calls.

Evans, J. R. (2013). Statistics, data analysis and decision modeling (5th ed.). Cincinnati, OH: Pearson Education