401077 - Introduction to Biostatistics - Quantitative Variable - Statistics Assignment Help

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  • Internal Code :

    1BFIFI

  • Subject Code :

    401077

  • Country :

    Australia

Assignment Task :

Question 1 (401077)

Consider the sample from the Framingham Study assigned to you for your assignment. 

  1. Explain why heart rate (heartrte) is a quantitative variable. 
  2. Explain why your student number (yourID) is not a variable. 

 

Question 2

  1. Using the sample from the Framingham Study assigned to you and R Commander, graph the distribution of serum total cholesterol (touch). Provide an appropriate title and descriptive axis labels. 

  2. Using appropriate statistics from R Commander, write one or two sentences describing the distribution of serum total cholesterol (touch). (Hint: consider measures of center, spread, and shape. R commander output alone is insufficient – write the answer in your own words.) 

 

Question 3 

Using the sample from the Framingham Study assigned to you and R Commander, graph the frequency distribution of ‘Attained education’ (educ_f). Provide an appropriate title and descriptive axis labels. Write a sentence or two summarising the main characteristics of this distribution as shown by the graph.

 

Question 4

Using the sample from the Framingham Study assigned to you and R Commander, graph respondents’ ‘serum total cholesterol’ (totchol) against ‘Attained education’ (educ_f). ). Provide an appropriate title and descriptive axis labels. Using the graph and associated statistics, write a sentence or two describing the relationship between these two variables. 


Question 5 

  1. Using the sample from the Framingham Study assigned to you and R Commander, tabulate the relationship between gender (sex) and current cigarette smoking (cursmok). Include frequency counts and either row or column percentages. (Hint: R commander output alone is insufficient – present your table(s) in Word with informative headings.)

  2. Using the results in part a) write a sentence or two describing the relationship between gender and current cigarette smoking. 
  3. If you were to select one person at random from this data set, what is the probability they would be a male and a current cigarette smoker? 
  4. If you were to choose one female at random from this data set, what is the probability they would be a current cigarette smoker? 

 

Question 6

  1. Using the sample from the Framingham Study assigned to you, what proportion of people in your data set are coded as currently using blood pressure medications (bpmeds=Current use)? 

  2. Suppose your answer in a) was the proportion of adults in the US currently using blood pressure medication. Suppose you take a random sample of size 100 from all US adults and ask them if they were currently using blood pressure medication. Use the Binomial probability model and R Commander to estimate the probability that more than 5 of these 100 would be currently using blood pressure medication. (Hint: To avoid any problems in R Commander, use a number slightly more than 5 such as 5.1.) 
  3. Continuing the same scenario as b), in any random sample of 100 US adults how many, on average, would you expect to be currently using blood pressure medications? (Hint: mean is another word for average.) 
  4. Carefully explain why or why not the Binomial model is an appropriate probability model for the scenario described in b). 


Question 7

The mean systolic blood pressure in the frame.p1 data file is 132.9 mmHg with a standard deviation of 22.4 mmHg. 

  1. What is the z-score for a Framingham study participant whose systolic blood pressure is 110.5 mmHg? 

The data set assigned to you is a random sample from the frame.p1 data set.

  1. What is the mean systolic blood pressure in the data set assigned to you? 

  2. Each student in the Unit received a different random sample. Suppose we collected the sample means from each of these data sets. Estimate the mean and standard deviation of the distribution of sample means across all these data sets. Justify your answer.
  3. Calculate the z-score for the sample mean you reported in b). 
  4. Using R Commander, estimate the proportion of samples which would have a sample mean smaller than the sample mean you reported in b).

 

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  • Uploaded By : Grace
  • Posted on : March 18th, 2019
  • Downloads : 11

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