Introduction to ANOVA

The Analysis of Variance (ANOVA) method is the most popular and highly used statistical technique by researchers. Like T tests, ANOVAs are used to compare the means of groups for a given independent variable to determine whether they are statistically different from each other. However, T tests can only compare two groups. ANOVAs allow you to compare two or more (usually, ANOVAs are conducted with at least three groups). Using ANOVA, you can compare all mean differences simultaneously. This is advantageous as using multiple t tests increases the rate of Type I error, which means rejecting the null hypothesis when it is true (Tarlow, 2016).

For example, say you are interested in whether socioeconomic status is related to individuals self-reported happiness. By separating the individuals into groups representing low, middle, and high socioeconomic status (or even low, low-mid, mid, mid-high and high, or some other combination of groups), you could then determine whether mean reported happiness is different across each of the groups. How many groups might you need to investigate in your own research? If the answer is more than two, then this will be an important week. This week, you will extend your knowledge by identifying and applying the use of a one-way ANOVA test.

References/ Materials

Tarlow, K. R. (2016). Teaching principles of inference with ANOVA. Teaching Statistics, 38(1), 1621.

  • American Psychological Association. (2020). Academic Writer. American Psychological Association.
  • Knapp, H. (Academic). (2016). ANOVA [Streaming video]. SAGE Research Methods.

Statistical reasoning for everyday life

Bennett, J. O., Briggs, W. L., & Triola, M. F. (2017). Statistical reasoning for
everyday life (5th ed.). Boston, MA: Pearson-Addison Wesley.

This is the required Redshelf textbook for the course. You will be using this textbook all through the course for weekly assignments. For this week, review Chapters 9 and 10. Access the textbook in the Getting started module of your course or the Bookshelf link at the top of your course. 

Instructions

Download the assignment template and data files from this weeks resources and review the steps for this assignment. Once you have reviewed the steps, complete the problems and questions as presented. Show your work using your statistical program output. You may show manual/hand calculations only if the SPSS program cannot be accessed. There are two deliverables you must submit this week:

  • SPSS output file or manual calculations: Submit the SPSS output file in PDF form, or you can scan your work and submit it as a low-resolution graphic.
  • Word document: Submit a Word file answering the questions asked in the assignment. Describe the results in APA style incorporating relevant tables and figures formatted in APA style. 

Length: SPSS output or manual calculations and 1 to 2-page Word document

The completed assignment should address all of the assignment requirements, exhibit evidence of concept knowledge, and demonstrate thoughtful consideration of the content presented in the course. The writing should integrate scholarly resources, reflect academic expectations and current APA standards, and adhere to Northcentral University’s Academic Integrity Policy.

Statistics

Assignment 2 & Your first step for the final project project is to identify a data set of interest from Kaggle that is amenable to Excel manipulation and allows for extensive application of analytics models from our course. For example, a data set about types of jobs in the technology field might be interesting, but does not qualify (not a business analytics issue at the center of the topic). However, a data set about a company’s sales or customer satisfaction, etc. works fine. Kaggle has some great data sets for our purposes — Sales, satisfaction, HR analytics, etc. Have fun – find something you like.

Once you have identified a data set upload the data set in Excel. If it is approved, 10 points extra credit  are awarded if submitted before 11:45 PM on 6-12-22. I will also confirm in writing that it is approved (i.e. will add comment on Sakai). If it is not approved, it will receive a score of zero (0) in the grade center. Keep submitting a new data set until approved.

Here is the Kaggle location for the data set search:

https://www.kaggle.com/datasets?fileType=csv

Statistics

On an APA formatted paper that demonstrates your understanding of the hypothesis test. Think of an organization (real or fictitious), state an organizational problem (develop a problem statement), as a result of the problem statement state three research questions, develop real or fictitious data, and then demonstrate three hypothesis test. State your conclusion for each hypothesis and one general overall conclusion for the paper. At least one textbook, journal, or article as a Reference. About 5 – 6 pages. 

Stats

Discussion Prompt: How do you use statistics in your work as a nurse or healthcare provider? Find and discuss at least two examples of how statistics are used in your field. Do you feel like statistics are a vital part of the nursing field? Why or why not?

Hypothesis: Elaborate & Include Post

From the hypothesis, there are some information that can be obtained and used to develop a conclusion. For instance, the hypothesis is about shaving or not shaving preoperative. From this hypothesis, a person will get to know the essence of shaving before surgery. Most people shave few minutes before surgery which can contribute to Surgical Site Infection. In order to avoid such infections, a person is supposed to shave at least one day before surgery. This ensures that all bacteria that might be at the surgical site have died. Also, people should not use clippers for shaving surgical areas, but they should use traditional razors in order to reduce the chances of bacteria in the hair follicles to cause skin infection that is known as folliculitis. If a person must use a clipper, he or she has to ensure that it is at a lower setting. This ensures that the hair is cut uniformly at a lower level. According to Center for Disease Control (CDC) guidelines, a patient is supposed to shower or bathe using antiseptic agents in order to ensure that there are no bacteria around the surgical area. Those bacteria can lead to infections, thus risking the surgical process as well as the life of the patient. With this kind of information, a person will be able to make a conclusion concerning shaving the surgical area (“To Shave or Not Shave Preoperative Preparation,” 2021). 

In this hypothesis, one of the variables that would be tested is surgery. In this case, the person will determine the relationship between shaving or not shaving with the surgical process. The person will realize that it is impossible to conduct a surgical process in a hairy place; for instance, a person has been injured at the head, and the wound has to be administered. In this case, the person has to shave to ensure the surgical process will be conducted accordingly and ensure no infection. Many studies have been conducted to determine the risks of Surgical Site Infection between people who have shaved and those who haven’t. Results obtained show that people who shave immediately before surgery are at risk of SSI than people who have shaved few days before surgery.

Reference 

To Shave or Not Shave Preoperative Preparation. (2021). Retrieved 17 August 2021, from

linear relationship – multiple regression

 Download the dataset. The data set is information about the tax assessment value assigned to medical office buildings in a city. The following is a list of the variables in the database:

  • Floor Area: square feet of floor space
  • Offices: number of offices in the building
  • Entrances: number of customer entrances
  • Age: age of the building (years)
  • Assessed Value: tax assessment value (thousands of      dollars)

As you work through the following exercises, note your answers to the given questions so you can easily summarize them in your reflection.

Use the data set to construct a model that predicts the tax assessment value assigned to medical office buildings with specific characteristics.

1. Construct a scatter plot in Excel with Floor Area as the independent variable and Assessment Value as the dependent variable. Insert the bivariate linear regression equation and R2 in your graph. 

  • Do you observe a linear relationship between the 2      variables?

2. Use Excels Analysis ToolPak to conduct a regression analysis of Floor Area and Assessment Value. 

  • Is Floor Area a significant predictor of Assessment      Value?

3. Construct a scatter plot in Excel with Age as the independent variable and Assessment Value as the dependent variable. Insert the bivariate linear regression equation and R2 in your graph. 

  • Do you observe a linear relationship between the 2      variables?

4. Use Excels Analysis ToolPak to conduct a regression analysis of Age and Assessment Value. 

  • Is Age a significant predictor of Assessment Value?

Construct a multiple regression model.

  • Use Excels Analysis ToolPak to conduct a regression      analysis with Assessment Value as the dependent variable and Floor Area,      Offices, Entrances, and Age as independent variables. 
  • What is the overall fit R2? What is the adjusted R2?
  • Which predictors are considered significant if we work      with =0.05? Which predictors can be eliminated?
  • What is the final model if we only use Floor Area and      Offices as predictors?
  • Suppose our final model is: Assessed Value = 115.9 +      0.26 x Floor Area + 78.34 x Offices. 
  • What would be the assessed value of a medical office      building with a floor area of 3500 sq. ft., 2 offices, that was built 15      years ago? 
  • Is this assessed value consistent with what appears in      the database?

Reflection

In a minimum of 500 words, reflect on the types of medical offices you would advise management to close and open, and why. Use your exercise notes to support your rationale.