BULLYING VS CYBERBULLYING Is there a relationship between percentage of bullying or cyberbullying and grade level?
Introduction
Bullying has been around for quite a long time now and is a common problem that many schools have most likely faced before. Not only that, but many students have been victims of all types of bullying whether it’s verbal, physical, or even cyber. Some actions of bullying include making threats, spreading rumors, attacking someone physically or verbally, excluding someone from a group on purpose,etc. As you can tell, there are many ways people get bullied and victims can get seriously affected in different ways and aspects of their lives. So what exactly is bullying? It is basically when someone repetitively has an aggressive type of behaviour toward a person, usually in order to get power over them. Victims of bullying may have a hard time making friends or even any long-lasting relationships because they might have the fear of getting bullied again.
In these days, another common type of bullying is cyber-bullying and the only difference is that it occurs when you use electronic devices. Especially nowadays, everyone has phones from younger kids to older people making this even more of a problem. Some examples of cyberbullying include sending rude text messages, spreading rumors through social media, posting embarrassing or unwanted pictures of someone without their consent, and so on. There can be many causes for cyberbullying to occur like, for example, someone might be mad at another student and they do something to take revenge and most often, they would take revenge by posting something embarrassing online. Cyberbullying is a very serious issue and shouldn’t be taken lightly because one possible outcome is that the victim could commit suicide and that exact case happened with someone. Jamey Rodemeyer was a gay teenager who died at the age of 14 from hanging himself because of the constant bullying he was facing. Following his death, a new cyberbullying legislation was launched.
The National Crime Victimization survey (NVCS) was conducted to get data to see the extent to which students with different personal characteristics report cyberbullying and bullying. The estimates included responses by student characteristics like gender, race/ethnicity, grade, and also household income. Not only that, but school characteristics were also included like public or private schools, level, enrollment size, student to teacher ratio, percentages of combined races and ethnicities; and last but not least, the percentage of students who were eligible for free or reduced-priced lunch. The data was showing the relationship between bullying and cyberbullying victimization as well as other crime-related variable like the reported presence of guns, gangs, drugs, and alcohol at school. A few other things included were the selected school security measures, fighting, and weapon carrying to school. In this report, the data has been taken to find out if bullying or cyberbullying has anything to do with what grade level a student is in from grades 6-12.
Data Collection
Graph
The graph above shows the results for the percentage of students who were either bullied and what grade they were in and the percentage of students who were cyberbullied and what grade level they were in. Looking at the graph, you can see that the blue bars are for the students who were cyberbullied and the red bars indicate the students who were bullied at school. The percentages of students who were cyberbullied are within a very small range with the highest bar only going to 12% while the percentages for the students who were bullied at school were much higher with the highest bar going to 38%.
Scatter Plot
Analyzing the Data
The scatter plot above shows the relationships between bullying and the grade levels as well as cyberbullying and the grade levels students are in. If you were to look back at this scatter plot, there is a line going through most of the dots called the line of best fit and that is used for predicting further values. This shows the data being categorized as linear because the residuals that were calculated were the smallest with a linear line when compared to the quadratic or exponential line.
The blue line for cyberbullying indicates that there is a slight positive correlation because after calculations, the correlation coefficient (r) was 0.56857353268418 and since the line of best fit is directed or going upwards, it has a positive slope. The strength for this piece of data is slight because in order for it to be strong, (r) has to be close to positive one. All of this basically means that there is a slight positive relationship between the X (grade levels) and Y (Percentages) variables. As for the purple line for the students bullied at school, you can tell there is a strong negative correlation because the correlation coefficient (r) was -0.9276 which is very close to one and because the line of best fit is directed downwards, there is a negative slope.
The line of regression can be calculated using the linear function which is "y=mx+b" where m is the slope and b is the y-intercept. This equation is used to predict values for the Y variable.The y-intercept is generally where the line created crosses the y-axis. For the students who got cyberbullied aka the purple line, the y-intercept is 4.035714286 since thats the point where the line crosses the y-axis. The slope, m, for this data on students cyberbullied is 0.5357142857 or if we were to put it into other words, it would be the rate of change or rise/run. If you put all this into the equation "y=mx+b" as told before, then the linear equation for this data turns out to be y=0.5357142857x+4.035714286.
If were to do the same thing for the students bullied at school, then the y-intercept would be 47.57142857 and the slope would be -2.142857143 which would make the overall linear equation turn out to be y=-2.142857143x+47.57142857. Now that we have a linear equation for both of the relationships, we can use it to predict other values by simply just substituting the x for a number. If we wanted to predict what y (the percentage being bullied) would be when x is 13(in this case, that means college), then by plugging in 13 for x we would get an outcome of 19.714285711 for y.
For this particular set of data, there is a positive correlation for the students who were cyberbullied while there is a negative correlation between the students who got bullied at school. Correlation is, in basic words, the degree to which two events are associated with each other and for this case, as I said before, its between the bullying and cyberbullying and the grade levels. Causation is different from correlation though because causation is more of a cause and effect relationship while correlation doesn't necessarily mean that one thing causes the other since there could be other reasons why the data could have a good correlation. In this data, you can see from the results that as the grade level gets higher,the percentage of bullying in school decreases so does this mean that if you are in a higher grade level you will get bullied less? Well, according to this data that is true, but it doesn't have to always be like that because there could be other factors contributing in this as well. Causation can also mean the changes in one variable measured directly causing changes in the other variable which is basically the cause/effect relationship as it was mentioned before.
Conclusion
In conclusion, by looking at all this data, we can get a pretty good idea about the difference in relationships between bullying in school and if its more common in one grade level than the other. We can also see the difference of whether cyberbullying is more common in the same grade levels as bullying in school was or if they were completely different. Now, you can also predict the percentage of bullying or cyberbullying in even higher grade levels such as college. This data has shown how bullying in school was much more common than cyberbullying and how they were the complete opposites with cyberbullying occurring more in higher grade levels and bullying in school occurring more in lower grades especially between 6th graders. The answer found at the end of this research concluded that there is a negative relationship between bullying and the grade levels and a positive relationship between cyber-bullying and the grade levels. As these common types of bullying become a bigger issue and continue to grow, it's important to know what grade levels are impacted the most so you can think of ways to be prepared and avoid this kind of behaviour in the future.