Statistics

profilejaydin23
UpdatedModule1Case-Variables.docx

Health Statistics Module 1 Case 1

Health Statistics Module 1 Case

Module 1 Case

October 11, 2017

Part 1: Variables

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

The researcher is considering the nominal measurement since there is no intrinsic order. These variables are only classified into for groups without referring to any other information. In addition, nominal variables have no numeric value; therefore, they 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 case, the measurement of the variables is ordinal because the assigned values between each category cannot and measured and they are not equal. Ordinal variables are mutually exclusive because the values cannot be used to calculate the difference but can be used to calculate the mean. The values express an order but the difference between them may not be the same (Cook A., Netuveli, G, &sheik, A., 2004).

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

The measurement of the variable (yes or no) is nominal because it has no numerical values and is used to represent two categories. Nominal variables have no quantitative value and they can sometimes 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 since it represents the difference between 100lbs and 200lbs. In addition, the scale is measurable and it allows absolute zero. Ratio scales possess all characteristics of an interval, nominal, and the 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?

The temperature is an interval/ratio type of variable since the values can be compared and a mean can be calculated. The nurse can calculate the mean temperature for patients. Interval scales have 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 is an ordinal variable because the data has an order but the difference between 1 and 2 is not the same as the difference between 3 and 4 since the level of satisfaction is not the same

Part II: Variables

The chosen question is number 6, where a five-point scale is used represent ordinal variable used to rate the level of patients’ satisfaction in the emergency room. The statistician can use the variable to answer the following question “Do the staff respond to patient’s needs within the shortest time possible?” the patients will be provided a questionnaire to respond by filling their level of satisfaction with how the hospital personnel respond to patient’s condition in the emergency room (CDC, 2012). After the patients fill their response, the statistician will analyze the results to determine the overall response. The information should be represented on a column or bar chart to assist in determining the patients’ level of satisfaction about the emergency room.

Part III:

The scientists can measure coping by collecting qualitative data from persons with PTSD through participant observation, sampling, qualitative interview, and focus group discussion. Collecting data about the available support services would assist to determine how various individuals with PTSD manage their condition (CDC, 2012). During data collection, all observations will be recorded to assist in measuring the effect of various coping technique from different patients. The scientist can use the qualitative data to determine the relationship between the effect PSTD on an individual and the coping technique employed. Qualitative techniques are used to collect subjective data where PTSD expresses their personal coping techniques. Qualitative information will also provide the information about various available coping techniques and the most preferred technique. Therefore, the qualitative technique is subjective and the individual’s feelings and opinions on the available coping techniques will be used to measure the relationship between the variables.

On the other hand, the scientist can use a quantitative technique to measure coping using data collected from a structured interview, impact on event scale, PTSD symptom scale interview, or a Likert scale. The quantitative data will be in form of an interval/ratio variable which can be used to determine the relationship between coping and the PSTD condition. The data can be ranked or put into categories to assist the scientist to measure the variable. In quantitative technique, statistical methods will be applied to measure the relationship between coping and the PSTD disorder by computing the mean and the correlation between the variables. The quantitative technique relies on the collected data in numerical to determine the relationship between variables same (Cook A., Netuveli, G, &sheik, A., 2004). Therefore, in this case, the quantitative data will not be subjective in measuring coping among the participants.

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.