Spring 2026 section 001

hot-dog-survey-data/README.md

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 # Project 0: Is a hot dog a sandwich?
+Exploring the question on whether a hot dog is a sandwich and investigating the hypothesis that 1/4 of UVA full-time undergraduate students believe a hot dog is a sandwich.
+
+Data was collected through a Google Form survey.
+
+Survey responses are recorded in Hotdog Survey (Responses).xlsx and the data dictionary can be found in data-dict.md.

hot-dog-survey-data/data-dict.md

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+# Data Dictionary
+| Column | Description | Examples |
+|-------|-------------|---------------------|
+| Timestamp | Indicates the month/day/year and hour, minute, and second that the respondent completed the survey. | Month/Day/Year, Hour:Minute:Second |
+| Year at UVA | Records the current year of the respondent.  | String (e.g., "1st Year, Graduate Student") |
+| What is your Gender Identity? | Records the gender identity of the respondent. | String (e.g., "Female, Nonbinary") |
+| What Schools are you a Part of? | Records the chosen school(s) of the respondent.  | String (e.g., "Arts and Sciences") |
+| Is a Hotdog a Sandwich? | Records the answer to the question *Is a hotdog a sandwich?*| Binary: Y or N. "Yes" indicates the responder believes a hot dog **is** a sandwich; "No" indicates they believe it is **not** |
+| How strongly do you feel about your previous answer? | Records how strongly the respondent feels about the previous answer. | Integer (from 1-5) |
+| How frequently do you eat hot dogs? | Records how frequently the respondent eats hotdogs. | String (e.g., "Frequently (ex. multiple times a month)") |

hot-dog-survey-data/ds4002_project00.Rmd

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+---
+title: "ds4002_project00"
+author: "Stephanie Diau"
+fontsize: 12pt
+geometry: margin=1in
+urlcolor: black
+output: pdf_document
+date: "2026-01-21"
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = TRUE)
+```
+
+#one sample z-test for proportions
+```{r}
+#from cleaned code, proportion of yes was 71
+p_0 <- 0.25
+n <- 175 #total undergrads
+x <- 71
+```
+
+```{r}
+#samp proportion
+phat <- x/n
+
+serror <- sqrt(p_0 * (1 - p_0) /n)
+z <- (phat - p_0)/SE
+
+p_val <- 2 * (1 - pnorm(abs(z)))
+
+phat
+z
+p_val
+```
+
+```{r}
+serror_hat <- sqrt(phat * (1 - phat) / n)
+
+#CI
+CI <- phat + c(-1, 1) * qnorm(0.975) * serror_hat
+CI
+```
+