Homework

Authors
Affiliation

Instructions

Warning

All homework assignments are due at 11:59 p.m. on the date listed. They should be typed up in Quarto and submitted as PDFs on Gradescope.

  • There is no template for the homework. For each homework assignment, start a new Quarto document and include the following fields in the YAML header:
    • title: The assignment number (e.g., “HW #1”)
    • subtitle: SDS 210
    • author: Your name
    • date: The due date of the assignment (in ISO 8601 format)
    • format: For PDF output, put pdf. Please note that this may require the one-time installation of tinytex
    • abstract: Please include a collaborations statement that lists the names of all classmates or individuals with whom you collaborated (or, if you did not work with anyone, the statement “I did not collaborate with anyone on this assignment.”)
  • For each question on the homework, please:
    • Start each question with a section header ## and include the question number at the start of your response. For example: ## IMS 1.4.2
    • If asked to compute or calculate a number, give your answer in a sentence (or more, if needed) and show all work (either hand calculations or R code with the accompanying output).
    • If asked to make a graph, show the graph and describe what is shown by the graph in 1–2 sentences. You should also provide the R code required to create the graph.
    • Use complete sentences when answering any question.
  • Please include only relevant R commands and output: do not print errors, messages, warnings, or anything else that makes your homework unwieldy. This will help anyone who reads your assignment, whether that’s the grader or future you!
  • Please read the guide to \(\LaTeX\) for help with formatting mathematics
  • Please see the Extension policy

Assignments

  • HW #1 (due Friday, January 30, at midnight):
  • HW #2 (due Friday, February 6, at midnight):
  • HW #3 (due Friday, February 13, at midnight):
    • IMS: 7.5.4, 7.5.6, 7.5.8, 7.5.10, 7.5.14, 7.5.22, 7.5.25, 7.5.30
  • There is no homework this week!! If you want to practice for the exam, consider these problems:
    • IMS: 8.6.7, 8.6.8, 8.6.11, 8.6.12
  • HW #4 (due Friday, February 27, at midnight):
    • OI: 3.1, 3.2, 3.5, 3.7 (don’t hand in part (b)), 3.12
  • HW #5 (due Friday, March 6, at midnight):
    • OI: 3.13, 3.16, 3.20, 3.29, 3.34, 3.36
  • HW #6 (due Friday, March 13, at midnight):
    • IMS: 12.5.1, 12.5.4, 12.5.7
  • HW #7 (due Friday, March 27, at midnight):
    • IMS: 11.5.2, 11.5.3, 11.5.4, 11.5.7
    • IMS: 16.4.2
    • [data analysis problem]: In a 2010 Survey USA poll, 70% of the 119 respondents between the ages of 18 and 34 said they would vote in the 2010 general election for Prop 19, which would change California law to legalize marijuana and allow it to be regulated and taxed. These data can be found in the leg_mari data frame from the openintro package.
      1. Compute the observed proportion of the respondents who support Prop 19. Use the specify() and calculate() functions from the infer package.
      2. Explain in words how the bootstrap could be used to simulate the sampling distribution of the sample proportion. Be as specific as you can!
      3. Use the generate() and calculate() functions from the infer package to generate a bootstrap distribution for the sample proportion, and use the visualize() function to display it.
      4. Use the get_ci() function to display a confidence interval for the true proportion of the population that supports Prop 19.
      5. Does your confidence interval contain 50%? How does this inform your understanding of support for Prop 19?
  • HW #8 (due Friday, April 3, at midnight):
    • IMS: 13.8.2, 13.8.3
    • IMS: 16.4.4, 16.4.8, 16.4.16
    • [data analysis problem]: We will continue working with the previous data set about views on Prop 19 (i.e., openintro::leg_mari).
      1. Just like you did before, compute the sample proportion \(\hat{p}\) who support Prop 19. This time, save the resulting value as a vector (of length 1). You may have to use pull() or $ or [[ to extract this vector from the data.frame that is returned by calculate().
      2. Just like you did before, simulate the sampling distribution of \(\hat{p}\) using infer. This time, use the summarize() and sd() functions to compute the standard deviation of your bootstrapped sampling distribution.
      3. Use your answer for part (a) and the appropriate formula to compute the approximate standard error of the sample proportion.
      4. Compare your answer for part (b) to your answer for part (c). Are the two values for the standard error the same? Are they meaningfully different?
      5. Explain in your own words what how the two quantities are related, and how they are different.
  • HW #9 (OPTIONAL due Friday, April 10, at midnight):
    • IMS: 17.5.10, 17.5.11
  • HW #10 (due Friday, April 17, at midnight):
    • IMS: 18.4.2, 18.4.7, 18.4.11, 18.4.16
    • IMS: 19.4.3, 19.4.4, 19.4.13, 19.4.14, 19.4.16

Rubric

All homework will be graded on an ordinal 5 point scale based on a combination of accuracy and effort (see Table 1).

Table 1: Grading rubric for homework assignments.
Score Description
5 All problems completed with detailed solutions/good faith attempts at answering and with at least 75% of the solutions fully correct.
4 Either (i) all problems completed with detailed solutions and with 50%–75% of the solutions correct or (ii) nearly all problems completed with detailed solutions and with at least 75% of the completed solutions correct.
3 Nearly all problems completed with detailed solutions and with less than 75% of the completed solutions correct.
2 More than half (but fewer than all) problems completed with at least 75% of the completed solutions correct.
1 Either (i) more than half (but fewer than all) problems completed with less than 75% of the completed solutions correct or (ii) less than half of the problems completed with detailed solutions.
0 Either (i) work is not submitted or is submitted more than 48 hours after the stated deadline or (ii) less than half of the problems completed without detailed work supporting the solution.
Tip

Excessive R printouts or failure to otherwise follow the homework instructions above will result in scores of 5 being reduced down to a 4.