Publications by Kitada Smalley
DATA 151: Time and Space (SP 25)
UPDATED SPRING 2025 Learning Objectives In this lesson students will learn how to create Time series plots Choropleths (colored map plots) Time Series Plots Time series plots show how a variable (on the y-axis) changes over time (on the x-axis). Example 1: Salem, Oregon AQI Step 0: Library Tidyverse library(tidyverse) Step 1: Load the Data sa...
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DATA429: Canned vs Homemade
Learning Objectives: In this lesson students will learn to: Use survey packages in R Weight data based on auxiliary information Analyze categorical responses Example: Thanksgiving Survey 0. The Data: We are using the data from fivethirtyeight the Here’s What Your Part of America Eats on Thanksgiving article https://fivethirtyeight.com/features...
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DATA429: Basics of srvyr Package
Learning Objectives: In this lesson students will learn to: Use survey packages in R Define survey objects Inference for the mean The Data These data were put together from NBA and WNBA records for the 2022-2023 and 2022 seasons, respecitively. For this activity we are going to pretend that we are doing a survey on professional basketball players...
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DATA429/599:Item Nonresponse and Imputation
Learning Objectives: In this lesson students will learn to: Visualize missing data Implement imputation methods The Data These data were put together from NBA and WNBA records for the 2022-2023 and 2022 seasons, respecitively. For this activity we are going to pretend that we are doing a survey on professional basketball players. These data repre...
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DATA429: Woes of NonResponse
Learning Objectives: In this lesson students will learn to: The woes of nonresponse! How to use auxiliary data to re-weight survey responses in the face of nonresponse The Data These data were put together from NBA and WNBA records for the 2022-2023 and 2022 seasons, respecitively. For this activity we are going to pretend that we are doing a sur...
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SurveyTopics: Stratified Estimators
Learning Objectives In this lesson students will learn to: Construct estimates and confidence intervals for stratified random samples from finite populations Examples from “Sampling: Design and Analysis” by Sharon Lohr. Warm-up / Review Data from a SRS of 120 golf courses, selected from a list of 14,938 golf courses in the United States, are...
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Tables and Bars: Happy Little Trees
Learning Objectives In this lesson students will learn to apply categorical data analysis methods to data sets with fundamentally different structures. Work with individual and cross-tabulated level raw data Create univarite tables to show marginal distributions Create two-way tables to show joint and conditional distributions Create bar graphs an...
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SurveyTopics: SRS Estimators
Learning Objectives In this lesson students will learn to: Plot weighted survey data Use weights in analyses Construct confidence intervals for simple random samples from finite populations Motivating Example Motivating example from “Sampling: Design and Analysis” by Sharon Lohr. A university has 807 faculty members. For each faculty member, ...
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SurveyTopics: Random Sets and Estimators
Learning Objectives This Rmd is mean to accompany a hands-on sampling activity to help students practice: Drawing random subsets from a finite population Estimate means and totals Compute sampling distributions Calculate expected value, variance, bias, and mean squared error I. Framework for Probability Sampling Suppose we have a finite populatio...
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SurveyTopics: Intro to Probability Sampling
Learning Objectives In this lesson students will learn to: Implement fundamental probability sampling methods (simple random sample, stratified sample, cluster sample, and systematic sample) Based on notes from “Sampling: Design and Analysis” by Sharon Lohr. I. Basic Sampling Methods In probability samples each unit in the population has a k...
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