Call: lm(formula = EFFECT_CARE_COMM ~ COMMUNITY + GROWTH, data = selectdata)
im fine with you guys keeping these outputs but ideally they should go into some other nicer looking table
30 Matching Annotations
- Nov 2025
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vraposo.quarto.pub vraposo.quarto.pub
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(p= 0.369
with this p value does the unit increase in feelings really indicate the increase in care-based intervention support?
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Figure 6
figure 6 does not appear labeled, maybe "figure 6" is cut off by the image being cut off? either way i dont see figure captions
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Predictors of Perceived Effectiveness of Violence Prevention Approaches
going to need to fix presentation of the graphs, things are cut off, the legend is blocking a bit of the graph too
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Warning: Removed 2 rows containing non-finite outside the scale range (`stat_count()`).
from here on i wont comment on output, just get rid of it unless it contains something that you dont report in a figure caption/paragraph
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<theme> List of 2 $ axis.text.x : <ggplot2::element_text> ..@ family : NULL ..@ face : NULL ..@ italic : chr NA ..@ fontweight : num NA ..@ fontwidth : num NA ..@ colour : NULL ..@ size : NULL ..@ hjust : num 1 ..@ vjust : NULL ..@ angle : num 45 ..@ lineheight : NULL ..@ margin : NULL ..@ debug : NULL ..@ inherit.blank: logi FALSE $ panel.spacing: 'simpleUnit' num 1lines ..- attr(*, "unit")= int 3 @ complete: logi FALSE @ validate: logi TRUE
get rid of this output
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Wilcoxon rank sum test with continuity correction data: selectdata$EFFECT_CARE_COMM and selectdata$EFFECT_FEAR_POLICE W = 2644, p-value = 3.19e-09 alternative hypothesis: true location shift is not equal to 0
this output isn't awful but since you're reporting the findings already i would say there's no need for this
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inventions
interventions
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4.80 and 4.76. On the other hand, policing, a fear-based strategy, has the lowest rated agreement regarding effectiveness, with a mean of 3.20.
these do not match your figure?
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Warning: Removed 1 row containing non-finite outside the scale range (`stat_bin()`).
output
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Warning: Removed 1 row containing non-finite outside the scale range (`stat_bin()`)
unnecessary
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Warning: Removed 2 rows containing non-finite outside the scale range (`stat_bin()`).
get rid of this output too
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Attaching package: 'ggplot2' The following objects are masked from 'package:psych': %+%, alpha
see if you can get rid of this output
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Normality
section is nicely done
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surveyed
comma before 29
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avishnevetsk.quarto.pub avishnevetsk.quarto.pub
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plot(lm_primary_data
This is not ggplot, I would recommend using ggplot because the look of the graph will be a lot more customizable
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geom_histogram(binwidth = .5)
With your scale for the x-axis, you should edit the binwidth so each bar on the histogram is more visible
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yoominkim.quarto.pub yoominkim.quarto.pub
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While these results expand on earlier research, the study had some limitations
Probably best to make limitations its own paragraph
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Gender Differences in Self-Efficacy
I like the structure of this section! I don't have any edits to make here.
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Print the Test
I would add some explanation between each output. What do these numbers mean for your results?
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Visualize
If possible, change "GENDER01" just to "Gender" as the legend title
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Transform
Your inline comments are very good, I would recommend adding just a small paragraph at the end of this section explaining your preprocessing (removing NAs, transforming variables, etc)
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This study explored whether self-efficacy differed between genders, asking the research question: Are there differences in different groups of self-efficacy based on gender?
I think the inclusion of the research question feels a bit forced and awkward. Unless Dr. Shane specifically said you have to include your research question like this, I would reword the sentence to just start with "This study explored..." and then just explain what you did rather than end the sentence with a question mark.
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ghurford.quarto.pub ghurford.quarto.pub
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Discussion
Overall solid section, I like how you briefly reexplain the process and what the relationships turned out to be. Additionally, it was good to propose an explanation for your results. If I were to add anything, it would be explaining why you suggest those certain topics for future research.
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These findings fail to reject the null hypothesis,
Good!
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yellow
Again, the yellow is not very visible
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Motivations to Start Using Social Medi
I know there are figure captions for each graph, but you should also have a small summarization at the end of each section (1.4.2, 1.4.3, etc) that motivates why you chose certain variables and explains your results a bit.
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"yellow"
I'm not loving the color choice here it is not very visible on a white background. Some people might have dark mode but it should be visible in both modes.
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status_plot + labs (x = "Participants' perceived social status on a scale of 1-10 (ladder method)")
Graph title?
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Transform
After this section, you should include a small paragraph explaining your preprocessing (2-3 sentences maybe). Generally no need to explain your library imports, but you should give some broad info on what all your variables cover.
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