Exploring Statistical Concepts and Research Methodologies in Business and Healthcare

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Exploring Statistical Concepts and Research Methodologies in Business and HealthcareWeek 1Since statistics is the science of data, the relationship between a sample, population, descriptivestatistics, and inferential statistics is that they are all components of statistics.All of thesecomponents involve collecting classifying, summarizing, organizing, and interpreting numericalinformation.Also, all of these components are connected in some form. For example, a sample isa subset ofa population and one or both are included inthe elements of descriptive or inferentialstatistical problems.This means that you cansurvey iPhoneusers but this population is too largeso, you can break that down intoiPhone users between that ages 25 to 29.According to McClave, Benson, and Sincich (2011),a population is a set of units (people,objects, or events) that we are interested in studying (p. 5).Asample as a subset of the units of apopulation or any set of output produced by a process.Descriptiveutilizes numerical andgraphical methods to look for patterns in a data set, to summarize the information revealed in adata set and to presentthe information in a convenient form (McClave, Benson, & Sincich, 2001,p. 3). The text states that inferential statistics utilizes sample data to make estimates, decisions,predictions, or other generalizations about a larger set of data.McClave, J. T., Benson, P. G., & Sincich, T. (2011).Statistics for Business and Economics(11thed.) Boston, MA: Pearson.Week 21.Read the Albert Einstein quote in “The Research Process” section in Ch. 4 ofBusinessResearch Methods.What is the value of this statement in terms of the research process?What is the relevance and relationship of this statement to the technologically advancingbusiness world? Where do these questions allow us to go?'A familiar quotation from Albert Einstein, no less apt today than whenit was written, supports this view:The formulation of a problem is far more often essential than its solution, which may be merely a matter of mathematicalorexperimental skill. To raise new questions, new possibilities, to regard old problems from a new angle requirescreativeimagination and marks real advance in science.1In terms of the research process there will be as many probable solutions as there are researchers.For this reason it is imperative that all data extrapolated utilizing the basic formula is verified tobe valid. To find new ideas to all problems researchers must approach the issue with a questionattitude.It is safe to say that the pneumoniahas been around since thebeginning of time.However, there is continues research that is time consuming andnever ending battle tofindbetter ways to treat the illness. Being that the pneumonia is becoming more complex and harderto treat,there is no cure once a person has contracted it, it can be treated but it has to run itscourse.Although there isa vaccine to combat against whatever strand of the virus exist duringthat particular calendar year. The questions above allow us to take a long hard look at finding theproper solution to problems to benefit the world. These questions allow us to continue to becomemore creative and to continue to develop new or modern solutions in the business world.

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2.What are some examples of operational definitions in research design within yourprofession?An operational definition defines a variable, term, or object in terms of the specific process or setof validation tests used to determine its presence and quantity. Some examples that myorganization use is measuring the effectiveness or validity of ourelectronic medical records.Werun a series of validation test to ensurethe system is properly working. This in turn tells us aboutthe access, flow andproductivityby measuringhow longpatients have to wait for anappointment to a specialty outpatientclinic or how effectively the flow is in the emergency roomor inpatient departments.Otheroperational definitions in health care include patient andemployeesafety by measuring how often adverse drug events happen as wellasmeasuring howmany employee injuries/illnesses occur thatresult in being classified asOSHArecordable.3.Of the exploratory, formalized, and causal research designs types, which would you useto assess the effectiveness of an aspect of your job? Explain.I build health care electronic medical records. In my job, we are always asking why. So, I wouldsay of the exploratory, formalized, and causal research designs types causal would be would usedto assess the effectiveness of my job.Causal research explores the effect of one thing on anotheror to put it in formal terms the effect of one variable on another.For example, when we haveproblems with the system, such as failures or workflow issues, we try to determine why ithappened so if it happens it again,we can fix the problem. We attempt to recreate the problem inour test system that runs parallel to our live system and documentall the steps when trying tocreate a fix. We found that these problems happen when we install upgrades to our system.Basically, any change can inadvertently effect a different part of our system and cause it to failand it is our job to find the culprit.4.What is the purpose of sampling? What are some concerns and dangers ofsampling?How important is the sample design to data validity? Explain. Provide anexample where a sample might misrepresent data validity.According toMcClave, Benson, and Sincich,a sample is“a subset of the units of apopulation” (p. 6).Also, the sample portion must be carefully selected to represent thatpopulation.The purpose of sampling is to learn about the larger population withouthaving toresearch the entire population.We obtain a sample rather than a complete census of thepopulation because it is cost effectiveand less time consuming. Some concerns and dangers ofsamplingis thatone formula for a sample may be good for one sample may not be good foranother. Also, this formula may part of the population.All kinds of sampling procedures mayyield samples which are inaccurate and unreliable. There are techniques which minimize thesedangers, but some potential error is the price we must pay for the convenience and savings thesamples provide.The sampling design is important to data validity because it includes everyperson within the target population. For example, when a new medication is created, the researchis done on men and women who are both healthy and sick to determine side effects ofmedicationsand how effect it is to treat an illness. This sample may misrepresent data validity

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because different people have different reactions to medication and there is always at least onepercent of the population that will reject the medication.Week 31.How does technological advancement affect the ability to collect data? Provide examples.Does this advancement increase the chance for errors? Explain.Technological advancementaffectthe ability to collect data because it allows us tocollect more data whilelowering cost andincreasingprocessingspeed.Technology alsoallows store more data than and allow us to make future forecast for companies.Forexample, I part-time in retail we are able to compute the number of customers that visitedour store within the hour with real time data. We can also easily compute sales in order toforecast future progress.Sure, technological advancement increase the chance of errorbecause just likehumans it can be unpredictable at times and there is some factor ofhuman error involved. For example, I build electronic medical records, if I get onenumber, letter, or symbol wrong in the formulait could potentially cause the system toinput the information in the wrong areas.2.Validity is more critical to measurement than reliability. A valid measurement is reliable,but a reliable measurement may not be valid. Do you agree with these statements?Explain your answer. Provide examples to support your rationale.I agree with both statements aboutvalid and reliable measurements. Reliability is more sofocused on being consistent or stable but just because the information is consistent doesnot mean it is valid. Whereas, validity refers to accuracy. I have an undergraduate degreein Biology and spent numerous amounts oftime in the lab. This consisted of measuringhundreds of chemicals. I once was conductinga research experiment and my results wereconsistent but based on other studentsresults my measurements were not valid. When Iwent back to figure out what went wrong, my measurements were not correct due to thecalibration of the balance scale I was using. Although, my information was reliable, ithad to be thrown out because it wasn’t valid.3.What are some critical decisions involved in selecting an appropriate measurement scale?How do these decisions influence the research design?Some critical decisions when selecting an appropriate measurement scale are4.What is the importance of pretesting survey questions and instruments? What are risks ofnot doing this? Provide an example.5.How do survey question content and wording, response strategy, and preliminary analysisplanning affect survey question construction? Provide examples of questions that werepositively and negatively influenced by these elements.6.What is the importance of the null hypothesis? Why has it been the backbone ofmainstream hypothesis testing for decades? What are its limitations?

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