Reference no: EM132268547

Data Analysis Questions -

Question 1 - This question uses information from the data file cardiac_19.sav found under the Assessment tab on the StudyDesk (also see cardiac_19.txt for more details about the study and the variables measured). Make sure the Variable View in SPSS is setup properly with all 'labels' correctly defined (with units), all 'values' assigned correctly for categorical variables and the correct 'measure' selected for all variables.

A researcher is interested to know if the type of cardiac arrest of the patient is associated with whether the patient is male or female.

(a) Use a contingency table to display the relationship between 'Type of cardiac arrest' and 'Gender' for patients in this study (you should use SPSS to produce this contingency table). The title for this table should reflect the context of the study. (Note that by convention, a table title should appear above the table). Include your name in the title.

(b) What proportion of patients are 'Female' and had experienced 'Coronary Artery Disease'?

(c) Of those who experienced 'Silent Ischemia', what proportion of them are 'Male'?

(d) Does there appear to be an association between 'Type of cardiac arrest' and the 'Gender' for patients in this study? Explain in less than 100 words, using a numerical example(s) from a conditional distribution table to support your conclusion.

Question 2 - Consider the data in the file cardiac_19.sav again. Use SPSS to find the answers to the following questions, but do not copy and paste SPSS output into your answer for parts (c) and (d) (make sure you always include units where appropriate).

(a) Display the distribution of 'height' of patients in the study using an appropriate graph. Label the axes correctly, include units of measure and provide an appropriate title. Include your name in the title of the graph.

(b) Using the graph produced in part (a) only (don't refer to SPSS summary statistics), describe in no more than 60 words, the distribution of 'height' of the patients in this study. Include comments on shape, centre and spread of the distribution and the existence of outliers, if any. Do not perform any calculations; use the graph only.

(c) What is the sample size, mean and standard deviation of the distribution of 'height' of the patients, in this study? (You can use SPSS to calculate them but do not copy/paste SPSS output).

(d) Using SPSS find the median, first quartile, third quartile and IQR of the distribution of 'height' of patients in this study. (Do not copy/paste SPSS output).

(e) For the distribution of 'height' of patients, which statistics are appropriate to measure its centre and spread? Give a reasonable explanation for your choice.

Question 3 - Use this extract taken from the article, "Cranberry Juice Can Effectively Reduce Heart Disease," (appeared on preventdisease.com on January 1, 2019) to answer the questions that follow:

(a) Is this an experimental or observational study? In less than 50 words clearly explain your choice based on the extract given above.

(b) For the above study identify, if appropriate, the

i) response variable(s).

ii) factor and its levels.

iii) sample size.

(c) Are the four principles of experimental design used in this study? Explain, in the context of the study.

(d) Explain explicitly what a confounding variable is. Identify one plausible confounding variable in this study and explain why it is a confounding variable.

Question 4 - A study on the resting heart rates of marathon runners found that their resting heart rates are normally distributed with mean of 58 bpm and a standard deviation of 4 bpm (where bpm = beats per minute). A resting heart rate of 67 bpm is considered very high for a marathon runner. Use this information to answer the questions below:

(a) Identify the variable of interest and the unit of measurement of this variable.

(b) Based on this distribution, what percentage of marathon runners have a high resting heart rate (i.e., exceed 67 bpm)?

(c) Based on this distribution, what percentage of marathon runners have a resting heart rate between 55 bpm and 65 bpm?

(d) From previous records it has been shown that 2% of marathon runners are considered to have a dangerously low resting heart rate. Below what resting heart rate do these marathon runners have?

Question 5 - Consider the data in the file cardiac_19.sav again. This time we are interested to see if there is a relationship between cardiac index and hemoglobin level for patients who did not survive cardiac arrest after being admitted to hospital. Before commencing this problem you first need to select only those patients who did not survive cardiac arrest (see Selecting Cases recordings under SPSS Resources in the StudyDesk for help on how to do this).

(a) What are the two variables the researcher will need to include in the analysis? What type of variables are they?

(b) Use an appropriate graph to display the relationship between the two variables identified in part (a). Label the axes correctly, include units of measure and provide an appropriate title. Include your name in the title of the graph.

(c) From the graph in part (b), describe (in no more than 30 words) the form, direction and scatter of this relationship, and identify any outliers.

(d) Calculate an appropriate statistic to measure the strength and direction of the relationship between the two variables for patients who did not survive cardiac arrest after being admitted to hospital. Justify your choice of this statistic and interpret what it tells you about the relationship.

(e) Use SPSS output to write the equation of the regression line which could be used to predict cardiac index from hemoglobin level for patients who did not survive cardiac arrest after being admitted to hospital and then plot the regression line on the graph in part (b).

(f) Using the regression equation from part (e), predict the expected cardiac index of a patient whose hemoglobin level is 112 g/100mL. Would you consider this to be an accurate prediction? Why or why not?

(g) What proportion of the variability in cardiac index of patients who did not survive cardiac arrest after being admitted to hospital can be explained by the model, i.e. the relationship between cardiac index and hemoglobin level?

Question 6 - A doctor knows from experience that 5% of patients who are prescribed a certain drug will experience undesirable side effects. A randomly selected group of 11 patients have been prescribed this drug. A particular variable of interest is the 'number of patients who experience undesirable side effects'. Based on the above information answer the following questions:

(a) What is an appropriate model to represent the variable of interest? Write down the parameters of the model, if any.

(b) Discuss, in context, how the conditions of the appropriate model in part (a) are satisfied.

(c) Using the parameters of the model find the mean and standard deviation of the number of patients who experience undesirable side effects.

(d) Find the probability that no more than three of these 11 patients will experience undesirable side effects.

(e) Determine the probability that, in a random sample of 500 patients who have been prescribed this drug, 40 or less will experience undesirable side effects. State and check any assumptions, conditions or rules of thumb that should be considered before performing the calculations to determine this probability.

Attachment:- Assignment Files.rar