Introduction to Health Statistics

Introduction to Health Statistics

Running head: VARIABLES AND PROBABILITY 1

 

VARIABLES AND PROBABILITY 3

 

 

 

 

 

 

 

 

Trident University International

Javidi Thomas

Module 1: Case Assignment

BHS220: Introduction to Health Statistics

Dr. Sharlene Gozalians

January 12, 2018

 

 

 

 

 

 

 

 

 

 

Part 1: Variables

1. A researcher studying life categorizes individuals into single, married, divorced, or widowed. What type of variable measurement is this?

 

This type of variable is the nominal measurement because there is no intrinsic order. Nominal variables are only classified into four groups without referring to any other information. Therefore, nominal variables do not have numeric value and cannot be quantified.

2. A cognitive scientist places her subjects into categories based on how anxious they tell her that they are feeling: “not anxious”, “mildly anxious”,” moderately anxious”, and “severely anxious” and she uses number 0,1,2 and 3 to label categories where lower numbers indicate less anxiety. What type of variable measurement is this? Are the categories mutually exclusive?

 

In this situation, the type of measurement variable is ordinal because the assigned values used between each category cannot be measured. None of them are equal. Ordinal variables are mutually exclusive because the you cannot use values to calculate the difference. You can use them to calculate the mean. The values express an order. However, the difference between them are not always the same. (Cook A., Netuveli, G, &sheik, A., 2004).

3. A physician diagnosis the presence or absence of disease (i.e. yes or no). What type of measurement is this?

This type of measurement (yes or no) is nominal because they do not have any numerical values. They are used to represent two categories. Nominal variables do not have any quantitative value. Therefore, at times they can be assigned numbers to represent labels within a given category.

 

4. A person weighing 200lbs. is considered to be twice as heavy as a person weighing 100lbs. in this case, what type of measurement is body weight?

 

The type of variable is an interval/ratio. It represents the difference between 100lbs and 200lbs. The scale is measurable so it allows absolute zero. Ratio scales have all the characteristics of an interval, nominal, and ordinal scales.

5. A nurse takes measurements of body temperature on patients and reports them in units of degree Fahrenheit as part of the study. What type of variable measurement is this?

 

This type of variable measurement is an interval/ratio. These values can be compared and you can calculate a mean. In the situation, the nurse can calculate the mean temperature for patients. Interval scales possess similar properties to nominal and ordinal scales.

 

6. Patients rate their experience in the emergency room on a five-point scale from poor to excellent (1=very poor, 2=not very good, 3=neither good nor bad, 4=quite good, and 5=excellent). What type of variable measurement is this? Is the difference between 1 and 2 necessarily the same as the difference between 3 and 4? Explain briefly.

 

This type of variable is an ordinal variable because the data contains an order. However, the difference between 1 and 2 is not the same as the difference between 3 and 4 because the level of satisfaction is not the same.

Part 2: Variables

I chose to answer number six. There is a five-point scale used represent ordinal variable to rate the level of patients’ experience in the emergency room. The statistician can use the variable to answer this question: “Does the staff respond to patient’s needs in a timely manner?” Each patient will be provided with a questionnaire to fill out by stating their level of satisfaction with how the hospital personnel respond to patients in the emergency room (CDC, 2012). Once the patients fill out the survey, the statistician will analyze the results to determine the overall performance of the hospital staff. The information should be represented in a graph or bar chart to show the patients’ level of satisfaction about the emergency room results.

Part III

The health scientist can measure how well participants with Post Traumatic Stress Disorder are coping by collecting qualitative data from each participant with PTSD. They can do this by using participant observation, sampling, qualitative interview, and focus group discussions. Collecting data about the available support services can help determine how each individual with PTSD can manage their condition (CDC, 2012). During data collection, all observations will be recorded to help measure the effect of different coping techniques from the various patients. The scientist can also use qualitative data to determine the relationship between the effects of PSTD per individual and the different coping techniques used. Qualitative techniques can be used to collect subjective data where PTSD expresses each individual’s personal coping technique. Qualitative information can be used to provide information about the different types of coping techniques available as well as the most preferred technique. With that being said, the qualitative technique is subjective and each participant’s feelings and opinions on the coping techniques available, will be used to measure the relationship between the variables.

However, the scientist can also use a quantitative technique to measure coping by using data collected from a structured interview, impact on event scale, PTSD symptom scale interview, or a Likert scale. The quantitative data will be done by an interval/ratio variable. That way, it can determine the relationship between coping and PSTD condition. The data found can be ranked or placed into categories in order to help the scientist measure the variable. Quantitative technique and statistical methods will be added to measure the relationship between coping and the PSTD disorder. This will be done by computing the mean and the correlation between the variables. The quantitative technique must be based on the collected data in numbers to determine the relationship between variables same (Cook A., Netuveli, G, &sheik, A., 2004). For this case, the quantitative data will not be subjective in measuring coping among the individuals.

 

References

Centers for Disease Control and Prevention(CDC). (2012, May 18). Lesson 4: Displaying Public Health Data. Retrieved from Centers for Disease Control and Prevention: https://www.cdc.gov/ophss/csels/dsepd/ss1978/lesson4/index.html

Cook A., Netuveli, G., & Sheikh, A. (2004).  Basic skills in statistics: A guide for healthcare professionals. London.

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