Color Of Bees Lab Report
Independent Variable- colours of five artificial flowers. Colours used: yellow, red, blue, light violet, white.
Dependent Variable- Amount of bees attracted by the colours (± 1 bee).
Raw Data-
Colour Amount of bees every five minutes (± 0.1 s; ±1 bee) Trial 1 Trial 2 Trial 3 Trial 4 Trial 5
Red 0 0 0 0 0
Yellow 2 3 5 2 7
Blue 0 0 1 1 1
Light Violet 1 1 0 1 0
White 2 2 1 1 1
Table 1- Raw data.
Qualitative Data-
At the beginning of the experiment the weather was cloudy, while at the end of the experiment the sun came out. Since my experiment lasted for about 25-30 minutes, the weather may have affected my data. In fact, bees are more likely to leave the house when the weather outside is warm.
The bee hives were all placed in the same area, …show more content…
so all the students were carrying out their experiment in the same area. The experiments of some of the students involved different smells. Since my experiment didn't involved particular smells and the only attractant I had was honey, the bees may have been more attracted to the areas where the smells were stronger.
Calculations-
Calculate the mean for each colour by using the values of every trial.
Example for the yellow colour:
To calculate the mean, add the data of the different trials and divide the sum by the number of scores: →mean=(2+3+5+2+7)/5=3.8
Since we cannot have 3.8 bee, I will approximate the values to the closer number.
3.8→4
Statistical Tests- The standard deviation is a statistical test that enables to assess how far the values are spread above and below the mean.
Example for the yellow colour:
To calculate the standard deviation, start by calculating the mean. →mean=(2+3+5+2+7)/5=3.8
Since we cannot have 3.8 bee, I will approximate the values to the closer number.
3.8→4
Subtract the approximate mean to the values of each trial, add these values and square the result.
Σ〖(x-x̅)〗^2=4+1+1+4+9=19 degree of freedom=number of scores-1=4
Standard deviation=√((Σ〖(x-x̅)〗^2)/(degree of freedom))=2.17
As we can't have 2.17 bees, we need to approximate the values to the closer number. For this example the value changes from 2.17 to 2. The standard error is a way to measure the accuracy of different means. It is calculated dividing the standard deviation by the roots of the number of trials.
Example for the yellow colour:
Standard Error=(standard deviation)/√5=0.97
Also for the standard error, we need to approximate the values to the closer number. So here the standard error changes from 0.97 to 1. To the uncertainty of the mean shows how far the mean can be wrong. To calculate it you need to add and subtract twice the values of the standard error.
Colour Mean (±1) Standard Deviation Standard Error Uncertainties of means
Red 0 0 0 0 ± 0
Yellow 4 2 1 4 ± 2
Blue 1 1 0 1 ± 0
Light Violet 1 1 0 1 ± 0
White 1 1 0 1 ± 0
Table 2- Showing the mean of the amount of bees attracted to each colour, the standard deviation, the standard error and the uncertainties of the means. All these values have been approximated to the closer …show more content…
value. Graph 1- Showing the mean of bees attracted to different colours (±1 bee). The column for the red flower isn't visible because the total amount of bees that were attracted to the red colour was zero. The error bars represent the standard deviations.
Conclusion and Evaluation
Conclusion-
The aim of this experiment was to investigate the effect of different colours on bees behaviour.
I placed the five different artificial flowers at the same distance from the beehive so that the bees wouldn't see the closer flower first. To attract more bees I used some honey as attractant- I placed 20 ml of honey on the top of each flower. When I planned the investigation, I hypothesized that bees are more attracted to the yellow colour as bees perceive colours in a different way from humans and yellow is perceived as a bright colour. I also predicted that bees wouldn't be attracted to red colour as it is perceived as black and bees are warned off by dark colours.
From my results, I can say that bees prefer yellow above all the other colours (mean 4 ± 2). Moreover, during the 25 minutes of my experiment, not even one bee lied down on the red flower. Overall, the colours blue, light violet and white attracted equally amounts of bees. This shows that my hypothesis was right: bees are more attracted by the colour yellow and warned off by red colour as they perceive it as
black.
In table 1 an anomaly for trial 5 of the yellow colour (T5: 7 bees) is pointed out. This amount of bees was much higher than the other values for this colour. There are not other anomalies in my result. Maybe that only anomaly was due the fact that many other students that were carrying the experiment in my same area were starting to pack up and therefore the bees were less distracted by other odours, colours and textures and more attracted to my flowers.
In graph 1 the error bars represent the standard error that I calculated before. As it is visible from the graph, the standard error for the yellow flower is the highest of the experiment (standard error: 1). Maybe this is due to the anomaly in trial 5. However for the other colours the standard error is zero which means that the data is quite reliable (see table 2 for results and graph 1 for graphic representation of data).
To support my hypothesis I researched how bees perceive colours. The colour sense of bees have been of great interest for scientists in the past. In 1910, professor C. Von Hess studied the way bees perceive colours by using a spectrum to see where bees would lie the most. He found out that bees where more attracted to the green and yellow areas than to the others. Since the yellow and green part of the spectrum are the brightest colours for a fully colour-blind human eye, he hypothesized that bees are completely colour-blinds and that they cannot distinguish between different colours but they can only perceive dark, bright and "more bright" colours. However, other studies have been done after him and scientists found out that bees have a sense of colour, but unlike humans, they can distinguish less colours. One of them is ultraviolet, which in invisible to the human eye. Because bees have a different spectrum, they perceive colours differently and are red-blind. These studies explain why the bees didn't lie on the red flower but preferred the yellow one.
Bees are attracted to flowers by perceiving odours, sizes, colours and textures. As humans, bees perceive trichromatic colours, but their first three primary colours tend to shift to the light colours. This means that their orange-red band of colours is shorter than it is for humans. However, this implies that they can see ultraviolet colours, which are invisible to humans, as distinct colours. This explains why bees are more attracted to yellow, white and light-violet colours and why they perceive red and orange colours as dark colours and therefore they are warned off by flowers that present these features.
Evaluation-
The experiment supported my hypothesis, even if I didn't count as many bees as I expected. Before starting the experiment, I doubled the amount of attractant that I was going to use (from 10 ml to 20 ml) so that more bees would be attracted to my flowers. However, there were other factors that influenced my final results:
Factor Limitation Improvement
Weather conditions At the beginning of the experiment the weather was cloudy so less bees were likely to leave the beehives. However throughout the experiment the weather warmed up so more bees left the beehives. The next time carry out the experiment during a day with stable weather conditions. It would be even better to repeat the experiment during a summer day, so that the weather would be warmer and more bees would be likely to leave the beehives.
Position of beehives All the beehives available were in the same place, so great part of the students carried out their experiment in the same area. Overall the experiments involved different odours, colours, textures and sizes, so this probably affected the amount of bees attracted to my artificial flowers. Repeat the experiment alone so that particular odours, sizes and textures are avoided.
Distractions Rapid movements of the people behind me and the sounds that we involuntarily made while we were waiting may have warned off the bees from coming close to the artificial flowers. Repeat the experiment avoiding people in the area where the artificial flowers are placed.
Table 2- Showing the factors that limited the experiment and possible improvements.
Dependent Variable- Amount of bees attracted by the colours (± 1 bee).
Raw Data-
Colour Amount of bees every five minutes (± 0.1 s; ±1 bee) Trial 1 Trial 2 Trial 3 Trial 4 Trial 5
Red 0 0 0 0 0
Yellow 2 3 5 2 7
Blue 0 0 1 1 1
Light Violet 1 1 0 1 0
White 2 2 1 1 1
Table 1- Raw data.
Qualitative Data-
At the beginning of the experiment the weather was cloudy, while at the end of the experiment the sun came out. Since my experiment lasted for about 25-30 minutes, the weather may have affected my data. In fact, bees are more likely to leave the house when the weather outside is warm.
The bee hives were all placed in the same area, …show more content…
so all the students were carrying out their experiment in the same area. The experiments of some of the students involved different smells. Since my experiment didn't involved particular smells and the only attractant I had was honey, the bees may have been more attracted to the areas where the smells were stronger.
Calculations-
Calculate the mean for each colour by using the values of every trial.
Example for the yellow colour:
To calculate the mean, add the data of the different trials and divide the sum by the number of scores: →mean=(2+3+5+2+7)/5=3.8
Since we cannot have 3.8 bee, I will approximate the values to the closer number.
3.8→4
Statistical Tests- The standard deviation is a statistical test that enables to assess how far the values are spread above and below the mean.
Example for the yellow colour:
To calculate the standard deviation, start by calculating the mean. →mean=(2+3+5+2+7)/5=3.8
Since we cannot have 3.8 bee, I will approximate the values to the closer number.
3.8→4
Subtract the approximate mean to the values of each trial, add these values and square the result.
Σ〖(x-x̅)〗^2=4+1+1+4+9=19 degree of freedom=number of scores-1=4
Standard deviation=√((Σ〖(x-x̅)〗^2)/(degree of freedom))=2.17
As we can't have 2.17 bees, we need to approximate the values to the closer number. For this example the value changes from 2.17 to 2. The standard error is a way to measure the accuracy of different means. It is calculated dividing the standard deviation by the roots of the number of trials.
Example for the yellow colour:
Standard Error=(standard deviation)/√5=0.97
Also for the standard error, we need to approximate the values to the closer number. So here the standard error changes from 0.97 to 1. To the uncertainty of the mean shows how far the mean can be wrong. To calculate it you need to add and subtract twice the values of the standard error.
Colour Mean (±1) Standard Deviation Standard Error Uncertainties of means
Red 0 0 0 0 ± 0
Yellow 4 2 1 4 ± 2
Blue 1 1 0 1 ± 0
Light Violet 1 1 0 1 ± 0
White 1 1 0 1 ± 0
Table 2- Showing the mean of the amount of bees attracted to each colour, the standard deviation, the standard error and the uncertainties of the means. All these values have been approximated to the closer …show more content…
value. Graph 1- Showing the mean of bees attracted to different colours (±1 bee). The column for the red flower isn't visible because the total amount of bees that were attracted to the red colour was zero. The error bars represent the standard deviations.
Conclusion and Evaluation
Conclusion-
The aim of this experiment was to investigate the effect of different colours on bees behaviour.
I placed the five different artificial flowers at the same distance from the beehive so that the bees wouldn't see the closer flower first. To attract more bees I used some honey as attractant- I placed 20 ml of honey on the top of each flower. When I planned the investigation, I hypothesized that bees are more attracted to the yellow colour as bees perceive colours in a different way from humans and yellow is perceived as a bright colour. I also predicted that bees wouldn't be attracted to red colour as it is perceived as black and bees are warned off by dark colours.
From my results, I can say that bees prefer yellow above all the other colours (mean 4 ± 2). Moreover, during the 25 minutes of my experiment, not even one bee lied down on the red flower. Overall, the colours blue, light violet and white attracted equally amounts of bees. This shows that my hypothesis was right: bees are more attracted by the colour yellow and warned off by red colour as they perceive it as
black.
In table 1 an anomaly for trial 5 of the yellow colour (T5: 7 bees) is pointed out. This amount of bees was much higher than the other values for this colour. There are not other anomalies in my result. Maybe that only anomaly was due the fact that many other students that were carrying the experiment in my same area were starting to pack up and therefore the bees were less distracted by other odours, colours and textures and more attracted to my flowers.
In graph 1 the error bars represent the standard error that I calculated before. As it is visible from the graph, the standard error for the yellow flower is the highest of the experiment (standard error: 1). Maybe this is due to the anomaly in trial 5. However for the other colours the standard error is zero which means that the data is quite reliable (see table 2 for results and graph 1 for graphic representation of data).
To support my hypothesis I researched how bees perceive colours. The colour sense of bees have been of great interest for scientists in the past. In 1910, professor C. Von Hess studied the way bees perceive colours by using a spectrum to see where bees would lie the most. He found out that bees where more attracted to the green and yellow areas than to the others. Since the yellow and green part of the spectrum are the brightest colours for a fully colour-blind human eye, he hypothesized that bees are completely colour-blinds and that they cannot distinguish between different colours but they can only perceive dark, bright and "more bright" colours. However, other studies have been done after him and scientists found out that bees have a sense of colour, but unlike humans, they can distinguish less colours. One of them is ultraviolet, which in invisible to the human eye. Because bees have a different spectrum, they perceive colours differently and are red-blind. These studies explain why the bees didn't lie on the red flower but preferred the yellow one.
Bees are attracted to flowers by perceiving odours, sizes, colours and textures. As humans, bees perceive trichromatic colours, but their first three primary colours tend to shift to the light colours. This means that their orange-red band of colours is shorter than it is for humans. However, this implies that they can see ultraviolet colours, which are invisible to humans, as distinct colours. This explains why bees are more attracted to yellow, white and light-violet colours and why they perceive red and orange colours as dark colours and therefore they are warned off by flowers that present these features.
Evaluation-
The experiment supported my hypothesis, even if I didn't count as many bees as I expected. Before starting the experiment, I doubled the amount of attractant that I was going to use (from 10 ml to 20 ml) so that more bees would be attracted to my flowers. However, there were other factors that influenced my final results:
Factor Limitation Improvement
Weather conditions At the beginning of the experiment the weather was cloudy so less bees were likely to leave the beehives. However throughout the experiment the weather warmed up so more bees left the beehives. The next time carry out the experiment during a day with stable weather conditions. It would be even better to repeat the experiment during a summer day, so that the weather would be warmer and more bees would be likely to leave the beehives.
Position of beehives All the beehives available were in the same place, so great part of the students carried out their experiment in the same area. Overall the experiments involved different odours, colours, textures and sizes, so this probably affected the amount of bees attracted to my artificial flowers. Repeat the experiment alone so that particular odours, sizes and textures are avoided.
Distractions Rapid movements of the people behind me and the sounds that we involuntarily made while we were waiting may have warned off the bees from coming close to the artificial flowers. Repeat the experiment avoiding people in the area where the artificial flowers are placed.
Table 2- Showing the factors that limited the experiment and possible improvements.