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Load data
mosquitos <-read_tsv("mosquitos.txt")
Rows: 100 Columns: 3
── Column specification ────────────────────────────────────────────────────────
Delimiter: "\t"
chr (1): sex
dbl (2): ID, wing
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Kable presentation
kable(head(mosquitos))
ID
wing
sex
1
37.83925
f
2
50.63106
f
3
39.25539
f
4
38.05383
f
5
25.15835
f
6
57.95632
f
Research Question: How does the sex of mosquitoes influence their wingspan?
Exploring average wingspan by sex
mosquitos %>%# Start with mosquito's dataset and use the pipe operator functiongroup_by(sex) %>%# Group the mosquito data by the 'sex' column to perform operations separately for males and femalessummarise(wingmean=mean(wing)) %>%# Calculate the average wing length for each group and create a new column called 'wingmean'ungroup()
# A tibble: 2 × 2
sex wingmean
<chr> <dbl>
1 f 47.2
2 m 50.4
Mean data seems to show males having larger wings than female.
Exploring range of wingspan by sex
mosquitos %>%# Start with mosquito's dataset and use the pipe operator functiongroup_by(sex) %>%# Group the mosquito data by the 'sex' column to perform operations separately for males and femalessummarise(wingdifference=max(wing)-min(wing)) %>%# Calculate the difference between the maximum and minimum wing length for each sex and create a new column called 'wingdifference'ungroup()
# A tibble: 2 × 2
sex wingdifference
<chr> <dbl>
1 f 44.7
2 m 38.7
Females appear to have a bigger range than males.
Exploring data to visualise the wing size distribution
mosquitos %>%# Start with mosquito's dataset and use the pipe operator functionggplot(aes(x=wing, # Set the x-axis to 'wing' variablefill=sex))+# Use 'sex' to fill the density curves with different coloursgeom_density(alpha=0.7)+# Add a density plot layer with a transparency level of 0.7labs(x="Wingspan/mm",y="Density",color="Sex") # Change the labels on the plot to have more info and capital letters
Fig. 1: A density plot showing how the wingspan of mosquitos is distributed for males and females.
Exploring mean and dispersion of data by creating a boxplot
mosquitos %>%# Start with mosquito's dataset and use the pipe operator functionggplot(aes(x=sex, # Set the x-axis to 'wing' variabley=wing,color=sex))+# Group data by 'sex' for the boxplotgeom_boxplot()+# Add a boxplot layer to visualise the distribution of wing sizeslabs(y="Wingspan/mm",x="Sex",fill="Sex") # Change the labels on the plot to have more info and capital letters
Fig. 2: A box plot showing how the wingspan of mosquitos is distributed for males and females.
Summarising the data
summary(lm(wing~sex, data=mosquitos)) # Fit a linear model to examine the relationship between wing size and sex
Call:
lm(formula = wing ~ sex, data = mosquitos)
Residuals:
Min 1Q Median 3Q Max
-22.9515 -7.2651 -0.0677 6.2607 22.6409
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 47.177 1.357 34.771 <2e-16 ***
sexm 3.202 1.919 1.669 0.0984 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 9.594 on 98 degrees of freedom
Multiple R-squared: 0.02762, Adjusted R-squared: 0.0177
F-statistic: 2.784 on 1 and 98 DF, p-value: 0.09839
Results
Mean t-test on data shows p-value of 0.09, therefore not statistically significant.
Conclusion
Sex does not significantly influence wingspan, mean data suggests males having bigger wings however females appear to have a bigger range of wingspan than males.
