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  <url>
    <loc>https://voxpopsci.com/jonathancorbin</loc>
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    <lastmod>2023-10-15</lastmod>
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    <loc>https://voxpopsci.com/blog</loc>
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    <lastmod>2015-09-29</lastmod>
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  <url>
    <loc>https://voxpopsci.com/blog/firstpost</loc>
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    <lastmod>2016-08-06</lastmod>
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  <url>
    <loc>https://voxpopsci.com/voxpopscience</loc>
    <changefreq>daily</changefreq>
    <priority>1.0</priority>
    <lastmod>2024-12-01</lastmod>
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      <image:title>Vox Pop Science</image:title>
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  <url>
    <loc>https://voxpopsci.com/voxpopscience/2024/12/1/gratitudethanksgivingdid</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2024-12-11</lastmod>
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      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/22cb7951-92e0-4427-b1a5-726260f45c1f/gratitude_time_percent.png</image:loc>
      <image:title>Vox Pop Science - does thanksgiving increase gratitude? A Bayesian difference-in-differences approach. - Make it stand out</image:title>
      <image:caption>Figure 7. The dots reflect the best estimate of the % of respondents choosing that option — the bars reflect uncertainty (95% CIs). For stats nerds: I ran a Bayesian ordinal regression (cumulative link function). To test for an effect of Thanksgiving, I simplified things and just ran a model with country, Thanksgiving/Not Thanksving, and the interaction term (which captures the effect.) The beta for the interaction was 0.05 95% CI [-0.64, 0.77], so needless to say, my general conclusions from above remain unchanged.</image:caption>
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    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/6c73d5b6-f83d-4c15-b943-fec16ec76584/did_hypothetical_thanksgiving.png</image:loc>
      <image:title>Vox Pop Science - does thanksgiving increase gratitude? A Bayesian difference-in-differences approach. - Make it stand out</image:title>
      <image:caption>Figure 1. We rely on the assumption that the pre-Thanksgiving differences from the 25-27 would have persisted on the 28th. Since we have the real value for the comparison, we use that to estimate a counterfactual value that would have continued that trend. The difference between the observed value and the counterfactual is our estimate! (It never looks this perfect in real life…sigh)</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/47dc6bce-9f10-43cd-8b1b-eada65879ef0/gratitude_parallel.png</image:loc>
      <image:title>Vox Pop Science - does thanksgiving increase gratitude? A Bayesian difference-in-differences approach. - Make it stand out</image:title>
      <image:caption>Figure 2. This is more like reality… the distance between Canada and USA from the 25-27th are not identical, but they’re close enough to go ahead with this approach. For stats nerds: Posterior marginal effects from a Bayesian linear regression. I also did a joint hypothesis test for the day X country effect for the 25th and 26th (reference was the 27th), in which the 95% credible interval for the linear combination of the terms was between -.39 and .85.</image:caption>
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    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/f66175f9-6b8f-4968-8aec-7e42235d8f11/DiD_estimate_all_gratitude_measures.png</image:loc>
      <image:title>Vox Pop Science - does thanksgiving increase gratitude? A Bayesian difference-in-differences approach. - Make it stand out</image:title>
      <image:caption>Figure 4. A simple way to interpret this is to think of the yellow bell curves as all the possible values that the effect of Thanksgiving could be. More specifically, this figure shows the posterior distributions (in yellow) for the effect of Thanksgiving for each of the 3 gratitude emotions. The red dots are the median of the posterior distribution and the red bars show the credible intervals (the thick part is where we think there’s a 66% chance the effect lies and the thinner part is a 95% chance. For stats nerds: I estimated these with a Bayesian multivariate linear regression, in which I also modeled the correlation between measures, which were r(thankful, grateful) = 0.84, 95% CI [0.8, 0.86]; r(thankful, appreciative) = 0.78, 95% CI [0.74, 0.82]; r(grateful, appreciative) = 0.81, 95% CI [0.78, 0.84].</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/17e1222d-4c21-4cce-9f57-1a5b086fdcce/Posteriors_under_diff_priors_gratitude.png</image:loc>
      <image:title>Vox Pop Science - does thanksgiving increase gratitude? A Bayesian difference-in-differences approach. - Make it stand out</image:title>
      <image:caption>Figure 5. A visual for how someone with a strong belief in Thanksgiving increasing gratitude might change their belief in the face of new data (left) vs. someone with a weaker belief (right). The top (red) reflects their belief prior to reading this blog, the data (yellow) are the results of the study, and the new belief (yellow + red = orange) is their updated belief after incorporating this new data into their prior!</image:caption>
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    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/2e33300b-9bea-49fc-b4e5-f1e56ba4dc80/gratitude_ROPE.png</image:loc>
      <image:title>Vox Pop Science - does thanksgiving increase gratitude? A Bayesian difference-in-differences approach. - Make it stand out</image:title>
      <image:caption>Figure 6. The posterior distribution of our effect of Thanksgiving on gratitude (the yellow part reflects ±2.5% of the distribution. The blue bar reflects our ROPE. This pretty clearly demonstrates that we should still be pretty darn uncertain!</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/029fb471-a42f-4005-bc86-c0c151cd9a33/lm_gratitude_parallel_event_plot.png</image:loc>
      <image:title>Vox Pop Science - does thanksgiving increase gratitude? A Bayesian difference-in-differences approach. - Make it stand out</image:title>
      <image:caption>Figure 3. An event plot simply shows you the estimates of how much larger (or smaller) the difference between countries is than the difference on the 27th (which is the day before the treatment (in this case — Thanksgiving.) This is a standard plot that economists use for evaluating assumptions in difference-in-difference designs.</image:caption>
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  </url>
  <url>
    <loc>https://voxpopsci.com/voxpopscience/2024/11/15/ingroupfavoritismpart2</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2024-11-24</lastmod>
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      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/b2dee6ff-4875-46fd-8a6d-c7f2fcf421a6/dem_support_totals.png</image:loc>
      <image:title>Vox Pop Science - Democrats are split on affirmative action (for themselves)... regardless of whether or not you call it affirmative action - Make it stand out</image:title>
      <image:caption>Figure 1.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/a9c1eba6-14e9-4749-bb58-704d8501defb/dem_support_totals_rep_academia.png</image:loc>
      <image:title>Vox Pop Science - Democrats are split on affirmative action (for themselves)... regardless of whether or not you call it affirmative action - Make it stand out</image:title>
      <image:caption>Figure 2.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/e6be3739-7c98-4c5d-94d7-aa79e4cc0da0/dem_aa_plot_precinct.png</image:loc>
      <image:title>Vox Pop Science - Democrats are split on affirmative action (for themselves)... regardless of whether or not you call it affirmative action - Make it stand out</image:title>
      <image:caption>Figure 3. For stats nerds: I ran a Bayesian ordinal regression (with a cumulative link function) using the brms R package (Bürkner, 2017) using default priors. The effect of removing “Affirmative action” wording was b = 0.19 95% CI [-.30, .70], with 77.7% of posterior draws greater than zero (e.g., probability of direction.) (In other words, if I was into betting, I’d probably say that removing the wording increases support, but if I was writing this up for a scientific journal, I’d say we need more data.)</image:caption>
    </image:image>
  </url>
  <url>
    <loc>https://voxpopsci.com/voxpopscience/2023/10/6/ingroupfavoritism</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2024-11-24</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/ae3a3764-1f56-4764-a844-ea19965d4186/affirmative_action_precinct_dem_rep_responders.png</image:loc>
      <image:title>Vox Pop Science - Republicans are split on affirmative action (for themselves)… Until You call it affirmative action - Make it stand out</image:title>
      <image:caption>Whatever it is, the way you tell your story online can make all the difference.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/b9fbfdfa-fc6b-4de7-918d-e845c50a77bd/affirm_action_target.png</image:loc>
      <image:title>Vox Pop Science - Republicans are split on affirmative action (for themselves)… Until You call it affirmative action - Make it stand out</image:title>
      <image:caption>Figure 1. The original scale is 1 to 7, but for the sake of simplicity, I’m just plotting Against, Neither, and In favor here. Also, these percents combine participants who did and did not have the program described as “Affirmative Action”.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/217cb085-9898-4cb9-93eb-f879a060c2e2/precinct_Dem_target_Rep_sample.png</image:loc>
      <image:title>Vox Pop Science - Republicans are split on affirmative action (for themselves)… Until You call it affirmative action - Make it stand out</image:title>
      <image:caption>Figure 2.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/dc856dab-b44f-4556-a426-af573af0b415/affirm_action_rep.png</image:loc>
      <image:title>Vox Pop Science - Republicans are split on affirmative action (for themselves)… Until You call it affirmative action - Make it stand out</image:title>
      <image:caption>Figure 3. Reminder: the only difference between conditions is the words “Affirmative action” were either included or left out of the description — everything else was the same. For the stats nerds — I ran a Bayesian ordinal regression with a cumulative link function — the effect of leaving out Affirmative action was b = 0.5 (probability of direction = 97.42%)</image:caption>
    </image:image>
  </url>
  <url>
    <loc>https://voxpopsci.com/voxpopscience/2024/9/23/check-your-voter-registration</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2024-09-24</lastmod>
  </url>
  <url>
    <loc>https://voxpopsci.com/voxpopscience/2024/3/15/a-tidy-approach-to-schaffer-2020-itt-analysis-using-arima-models</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2024-03-17</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/e4b2d606-4258-4309-8ffb-0357062763da/Creating+step+and+ramp+variables-1.png</image:loc>
      <image:title>Vox Pop Science - A tidy approach to Schaffer (2020) (Interrupted time series using ARIMA models) - Make it stand out</image:title>
      <image:caption>Whatever it is, the way you tell your story online can make all the difference.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/a8e74f6d-365a-4434-9e38-c8498d8de453/differenced+plots-1.png</image:loc>
      <image:title>Vox Pop Science - A tidy approach to Schaffer (2020) (Interrupted time series using ARIMA models) - Make it stand out</image:title>
      <image:caption>Whatever it is, the way you tell your story online can make all the difference.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/28201205-e6f5-4f9d-a61e-e33a2f545e8c/Modeling+and+plotting+counterfactual-1.png</image:loc>
      <image:title>Vox Pop Science - A tidy approach to Schaffer (2020) (Interrupted time series using ARIMA models) - Make it stand out</image:title>
      <image:caption>Note. The black line is the real data and the purple line is the forecasted counterfactual.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/bd30b728-b920-465e-bf71-694a9017a731/Running+model+and+diagnostics-1.png</image:loc>
      <image:title>Vox Pop Science - A tidy approach to Schaffer (2020) (Interrupted time series using ARIMA models) - Make it stand out</image:title>
      <image:caption>Whatever it is, the way you tell your story online can make all the difference.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/82fca0b5-6fc6-43b5-8702-41e13a4fa517/plots-1.png</image:loc>
      <image:title>Vox Pop Science - A tidy approach to Schaffer (2020) (Interrupted time series using ARIMA models) - Make it stand out</image:title>
      <image:caption>Whatever it is, the way you tell your story online can make all the difference.</image:caption>
    </image:image>
  </url>
  <url>
    <loc>https://voxpopsci.com/voxpopscience/2023/10/10/is-personality-stable-yes-and-no</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2024-01-07</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/bba37027-303f-41a4-be93-edbf570ecd09/extraversion_continuum_edited.png</image:loc>
      <image:title>Vox Pop Science - Is Personality Stable? Yes. Also, no. (Part 1) - Make it stand out</image:title>
      <image:caption>Figure 1. Each dot represents any given situation in time. I’ve color coded 3 different types of situations (at work, at home, with friends) to demonstrate how personality might interact with environment. With friends, they’re more extraverted and at work — more introverted. At home, they’re pretty spot on with their overall average. If you think about it, your personality at home is probably best aligned with your overall trait personality, because you have more control over that environment! The extravert’s home will have a great space for hosting the monthly book club whereas the introvert will have a nice cozy reading nook.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/49d5f25a-fefd-4f53-8a3c-7b1a877ec4b8/extraversion_continuum_GoodPlace_edited.png</image:loc>
      <image:title>Vox Pop Science - Is Personality Stable? Yes. Also, no. (Part 1) - Make it stand out</image:title>
      <image:caption>Figure 2. Some folks are more sensitive to their environment than others. (Did you catch the references? There are 3 of them in this figure — one is super obvious if you know the show, one is a little tricky, and I think the third is pretty difficult.)</image:caption>
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  </url>
  <url>
    <loc>https://voxpopsci.com/voxpopscience/2023/12/1/are-we-more-thankful-on-thanksgiving</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2023-12-22</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/746db143-1008-4f88-b484-f802e729a83d/emotion_plot.png</image:loc>
      <image:title>Vox Pop Science - Are we more thankful on Thanksgiving? - Make it stand out</image:title>
      <image:caption>Figure 2. Estimated difference in ratings between people on Thanksgiving and people on other days. (Note, the scale goes from 1 to 5, so the differences could potentially range from -5 (Thanksgiving rating is a 0 and no-holiday rating is a 5) to 5 (Thanksgiving rating is a 5 and no-holiday rating is a 0.) How to interpret this graph: The dots are the best estimates for the average differences. The lines around the dots represent our uncertainty for those estimates — we have uncertainty because we only surveyed a small sample of people, so we need to reflect just how much information that sample can provide us in terms of the estimate of interest! The thick lines around the dots represent the interval by which there’s a 66% chance that the difference lies along that region. The thinner, wider intervals reflect a 90% chance that the difference lies along that region. For stats nerds: these estimates were calculated via mixed-effects Bayesian regression (where we interacted holiday and emotion with participant as a random effect.)</image:caption>
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    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/40764442-fa78-40b8-bc5e-71ad6326a75e/thankful_plot.png</image:loc>
      <image:title>Vox Pop Science - Are we more thankful on Thanksgiving? - Make it stand out</image:title>
      <image:caption>Figure 1. Estimated percentage of people choosing each Thankfulness category. How to interpret this graph: This is a series of stacked bar charts. For each day, we have a percentage of people who chose one of the five response options. If you add up the percentages within each day it should equal roughly 100% (though there may be some errors due to rounding.) For stats nerds: these estimates were calculated via ordinal Bayesian regression (with a cumulative link function). We also ran an additional model with just Thanksgiving vs. not Thanksgiving — the overall effect of Thanksgiving was b = 0.37 95% CI [-0.04, 0.81], probability of direction = 0.96. The estimated increase in people choosing “Very much” was 8.1 pp 95% CI [-.01, 0.18],</image:caption>
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  </url>
  <url>
    <loc>https://voxpopsci.com/voxpopscience/2023/10/5/is-it-common-for-people-to-lick-their-fingers-when-eating-chips</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2023-11-10</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/7a55ca89-7afd-4997-91e9-d1422644a5f5/finger_lickin.png</image:loc>
      <image:title>Vox Pop Science - Is it common for people to lick their fingers when eating chips? - Make it stand out</image:title>
      <image:caption>Figure 1. The CDC recommends to wash your hands for the amount of time it takes to sing “Happy Birthday” twice — don’t forget to scrub under those finger-nails!</image:caption>
    </image:image>
  </url>
  <url>
    <loc>https://voxpopsci.com/voxpopscience/2023/10/31/halloween-and-personality</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2024-11-01</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/69747bf0-6d0e-43af-bd54-ebc50cb9614a/halloween_attitude_extraversion.png</image:loc>
      <image:title>Vox Pop Science - Halloween and Personality - Make it stand out</image:title>
      <image:caption>Figure 2. Halloween attitudes (“How much do you dislike or like Halloween in general?”) get more positive as extraversion increases (for the stats nerds: r(161) = 0.25, p = .001). How to read this graph: “Liking rating” goes from 1 (Dislike strongly) to 7 (Like strongly). Lower numbers mean more introverted/higher numbers mean more extraverted. Each Jack O’Lantern is a person’s response (they are jittered a bit to help with visibility.) The line reflects the best estimate for the average response, assuming the relationship between the two variables is a straight line.</image:caption>
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      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/dc4eaac7-a84e-4a6c-93f0-7469c458c6f2/Screen+Shot+2023-10-31+at+8.47.15+PM.png</image:loc>
      <image:title>Vox Pop Science - Halloween and Personality - Make it stand out</image:title>
      <image:caption>Note. We went with a range voting (or score voting) method here, meaning I just took the average rating and ranked by that.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/ee9ede9f-1059-4198-8adf-243b0328f3b1/halloween_attitude.png</image:loc>
      <image:title>Vox Pop Science - Halloween and Personality - Make it stand out</image:title>
      <image:caption>Figure 1. “Sisters! All Hallows’ Eve has become a night of frolic, where children wear costumes and run amok.” How to read this graph: This is a stacked bar graph, meaning each color reflects the % of respondents choosing that option, and they are stacked next to each-other, with the total % choosing any one of them at the far end (79.7% chose one of the “Like” options for Halloween.)</image:caption>
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  </url>
  <url>
    <loc>https://voxpopsci.com/voxpopscience/2023/10/17/baseratesandfareevasion</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2023-11-06</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/9be262d7-3899-4fde-aeee-22e01aca3953/Screen+Shot+2023-11-05+at+7.58.39+AM.png</image:loc>
      <image:title>Vox Pop Science - what do base-rates have to do with Metro fare evasion laws? - Make it stand out</image:title>
      <image:caption>That’s a lot of zeros…</image:caption>
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    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/ca283bc0-27ba-446c-bc58-29fa0805bac7/comparing+base+rates.png</image:loc>
      <image:title>Vox Pop Science - what do base-rates have to do with Metro fare evasion laws? - Make it stand out</image:title>
      <image:caption>On the left: The statistic being used to convince us that stricter fare evasion laws will reduce violent crime. On the right: The statistic we actually need to know to verify the claim.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/b97e8efe-cfda-4174-abc9-b434000ae7dd/Screen+Shot+2023-11-05+at+8.21.53+AM.png</image:loc>
      <image:title>Vox Pop Science - what do base-rates have to do with Metro fare evasion laws?</image:title>
      <image:caption>To make this a bit less painful, each number is per 100,000. Also things may not add up perfectly due to rounding.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/a3a00812-a6c1-4685-9da1-53a7152315ea/comparing+base+rates_complete.png</image:loc>
      <image:title>Vox Pop Science - what do base-rates have to do with Metro fare evasion laws? - Make it stand out</image:title>
      <image:caption>Note: The size of the big blue circles are not to scale (obviously the “criminals” blue circle on the left would have to be minuscule compared to the fare evaders circle.)</image:caption>
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  </url>
  <url>
    <loc>https://voxpopsci.com/voxpopscience/2023/9/19/does-personality-tell-us-anything-about-vacation-preferences</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2023-11-01</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/e8442582-1f42-4e62-acb1-ed4f311030a2/vaca_pref_plot_urbruralpref.png</image:loc>
      <image:title>Vox Pop Science - Does personality tell us anything about vacation preferences? - Make it stand out</image:title>
      <image:caption>Figure 3. If you have to choose a vacation for somebody you don’t know, and it is between a rural and urban setting, this data suggests you bet on rural. But honestly, you might as well flip a coin…</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/3cc73b4b-e3dd-4e81-a5a5-a8ae6bd2709a/vaca_personality_plot1.png</image:loc>
      <image:title>Vox Pop Science - Does personality tell us anything about vacation preferences? - Make it stand out</image:title>
      <image:caption>Figure 1. The survey question was “How much would you say you like or dislike vacationing at/in the:” How to read this graph: These are stacked bar graphs, meaning each color reflects the % of respondents choosing that option, and they are stacked next to each-other, with the total % choosing any one of them at the far end (e.g., 85.6% chose one of the “Like” options for the beach.)</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/bb082adb-148e-4b17-ae49-b05cac220192/vaca_pref_plot2.png</image:loc>
      <image:title>Vox Pop Science - Does personality tell us anything about vacation preferences? - Most people prefer vacations that tilt towards relaxation.</image:title>
      <image:caption>Figure 4. “Do you prefer relaxing or active vacations?“</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/ecf5813b-b6da-4b15-8205-1ae5b2e3b8ff/vaca_pers_plot_3.png</image:loc>
      <image:title>Vox Pop Science - Does personality tell us anything about vacation preferences? - Make it stand out</image:title>
      <image:caption>Figure 5. “I can have fun anywhere as long as we can go out, but I guess if I had to choose, I’d go with the beach!“ says the extravert. How to read this graph: “Liking rating” goes from 1 (Dislike strongly) to 7 (Like strongly). Lower numbers mean more introverted/higher numbers mean more extraverted. Each dot is a person’s response (they are jittered a bit to help with visibility.) The lines reflect the best estimate for the average response, assuming the relationship between the two variables is a straight line.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/49785b2e-09fb-4aed-83ad-4ac9ca4750ae/vaca_pref_plot5.png</image:loc>
      <image:title>Vox Pop Science - Does personality tell us anything about vacation preferences? - Make it stand out</image:title>
      <image:caption>Figure 6. ”Hey, I’m happy with whatever!” says the person high in openness to experience (and consequently not helping anyone make a decision…) Note: The openness scale starts at 1.5 because nobody had a score of 1.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/1695503468309-GS339LMUS5IZ6KBLCD5F/1+-+African+Jedi+with+short+hair+and+a+hood+over+h.png</image:loc>
      <image:title>Vox Pop Science - Does personality tell us anything about vacation preferences? - Leave me alone, I’m communing.</image:title>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/1695503489750-501ULZAVTKVUPQ6BR9CJ/0+-+Party+on+the+beach.png</image:loc>
      <image:title>Vox Pop Science - Does personality tell us anything about vacation preferences? - Extraverts extraverting all over the place...</image:title>
      <image:caption />
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/18d95afe-c4e5-4d26-9d89-60448658d874/vaca_pref_plot_mtnbchpref.png</image:loc>
      <image:title>Vox Pop Science - Does personality tell us anything about vacation preferences?</image:title>
      <image:caption>Figure 2. If you’re in the very strange situation of picking a vacation for someone who you know nothing about, then go with the beach. What do these numbers mean? Preference scores were calculated by subtracting mountain from beach attitudes. This means that if they rated beach a 7 (Like strongly) and mountain a 6 (Like moderately), they’d have a score of 7-6=1 (a +1 preference for the beach.) If both were rated equally they would have a score of 0 (e.g., with a 7 for both beach and mountain, 7-7=0.) If the mountains were a 7 and the beach a 6, that would be a 6-7=-1.</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/fc62d806-b8a6-404d-8b90-ba24ee9acd87/vaca_pref_plot6.png</image:loc>
      <image:title>Vox Pop Science - Does personality tell us anything about vacation preferences? - Make it stand out</image:title>
      <image:caption>Figure 7. “I hear “staycations” can be really nice…” (he says as he stares at the suitcases, the pile of beach accessories, and the car topper.)</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/7ff0581f-f54c-4b2a-b514-3cf2131a5491/vaca_pers_plot_4.png</image:loc>
      <image:title>Vox Pop Science - Does personality tell us anything about vacation preferences? - Make it stand out</image:title>
      <image:caption>Figure A1. Scatterplots, barplots, and correlation coefficients across vacation and personality variables.</image:caption>
    </image:image>
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      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/1695504219222-NQGFM78G4WHAZNP1JB0Y/image-asset.png</image:loc>
      <image:title>blog pics</image:title>
      <image:caption>Look at all those extraverts just extraverting all over the place!</image:caption>
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      <image:title>blog pics</image:title>
      <image:caption>Look at all those extraverts just extraverting all over the place!</image:caption>
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      <image:loc>https://images.squarespace-cdn.com/content/v1/560983d7e4b012afaf1c5c93/1695504277236-YTA88SMX0XUQWL3G2GBH/1+-+African+Jedi+with+short+hair+and+a+hood+over+h.png</image:loc>
      <image:title>blog pics - Leave me alone, can't you see I'm communing?</image:title>
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      <image:title>Psych and Law Class Performance</image:title>
      <image:caption>Figure 1. Proportion of yes responses to questions about eyewitness memory. Students were given a pretest at the beginning of the semester and a posttest at the end. Questions were taken from Benton, Ross, Bradshaw, Thomas, and Bradshaw, 2006. Click here for the full questions associated with each label. N = 21 for PreTest and N = 15 for Posttest).</image:caption>
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      <image:title>Psych and Law Class Performance</image:title>
      <image:caption>Figure 2. Students confidence rating (1-Not at all to 5-Extremely) in their answers to the eyewitness memory questions.</image:caption>
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