Presentation#

Now that you submitted both the Data Report and Interim Report, the next destination is the Presentation. The presentation should aim to tell a story about the dataset that you have been working with this entire quarter. The presentation is 10% of your final course grade, of which 90% comes from the presentation and response to questions and 10% comes from the feedback report (see the corresponding section below).

Warning

The presentations will take place during Week 10. Please sign-up for a presentation using this link on GauchoSpace (make sure that you are logged with your UCSB credentials). Please make sure to sign-up by 11/27/2022 by 23.59. There will be a total of four presentation sessions.

Presentation Structure#

  1. Title slide

  2. General research questions (spatial ranomness versus spatial patterns)

  3. Data

    1. Acknowledge source of your data, unit of analysis, and types of variables (numeric, categorical, dummy).

    2. Non-spatial distribution (structure) of data: histograms, various charts and plots, correlation matrices, groupby tables (barcharts).

    3. Spatial distribution of data (choropleth maps or graduated symbols/markers maps).

  4. More detailed research questions (research objectives)

  5. Methods

    1. Describe briefly (clustering, t-tests, ANOVA, regression, correlation, Moran’s I). No need to specify formulas. Use the flow diagram to denote methods and order of analysis. Typically, t-tests / ANOVA –> Global/Local Moran’s I –> Clustering –> Regression.

    2. If you have 3 or more variables in your dataset, consider doing Local and Global Moran’s I on dependent variable only. If you have only 2 variables in your data, do Local Moran’s I and Global Moran’s I for both variables.

    3. For regression analysis, you need to have at least three models: kitchen sink (all variables), m2 (an OLS model where insignificant predictors are dropped), and spatial model (either fixed effect, spatial regimes, SLX, spatial error, or spatial lag). If you only have 2 variables, you need to have two models: kitchen sink and spatial model.

  6. Results

    1. Report p-values and/or statistic values. For regression report coefficients and their corresponding p-values, as well as R-squared. Interpret your coefficients.

    2. If you are using clustering, please make sure to justify the number of clusters.

    3. Make sure to include Global/Local Moran’s I.

  7. Discussion

    1. Re-iterate how the conducted analysis helps you understand you data better.

    2. Acknowledge any limitations of your study.

Presentation Format#

Each student will have 8 minutes to present and 2 minutes for questions.

Slides#

You may use any software to prepare your presentation. Please submit either pdf or pptx to the GauchoSpace by 11/27/2022.

Feedback Report#

As part of the final evaluation, each student will submit an evaluation report with feedback for the peers. Please make sure to include presenter’s name, title, and suggestions on improvement of the presentation. The feedback report must be submitted right after the presentation session that you signed up for. Bring the laptops to the session you are presenting in, so that you could take notes and submit the evaluation reports.