IntroductionSuicide to extreme. Another justification for this hypothesis,

IntroductionSuicide is an increasingly major public health concern in society today that needs to be controlled. In fact in many parts of the world, it is one of the leading causes of death. It is caused by voluntary self-inflicted destructive behavior with the intent of self-demise (Canadian Association for Suicide Prevention, 2016). Though difficult for researchers to pinpoint a specific reason or method of suicide, there are numerous factors that cause it. Generally triggered from psychiatric illnesses such as depression or bipolar disorders, or extreme emotions that overtake the mind such as rejection or remorse; suicide is something dangerous that needs to be prevented as much as possible. (HelpGuide, n.d.). HypothesisIt is hypothesized that overall in Canada, as time passes, females are more likely to commit suicide at a greater rate than males. The gender stereotypes and science suggests that females are more emotional especially during times of post-childbirth. Statistics state that 50% to 80% of  women experience “postpartum depression” within days or weeks of giving birth, in which symptoms per female can vary from mild to extreme. Another justification for this hypothesis, is the premenstrual syndrome (PMS) all females experience several weeks leading up to their menstruation cycle. Moreover, around ages 45 to 51, many women also experience menopausal depression. This marks the end of their menstrual cycle. For all these conditions, the symptoms include confusion, fatigue, guilt, mood swings, insomnia, or feelings of hopelessness and shame. For many these feelings can be so overwhelming, resulting in them taking their own life (Shore, 2016). On the contrary, gender norms suggests males are more strong and collected when it comes to dealing with their mental state (Powell, 2015).Measures of Central TendencyCentral tendencies indicate the values around which the data tends to cluster. The mean gives an average estimate of the number of suicides, whereas the median concludes that 50% of the data is above the median and the other 50% is below, and the mode is any value that repeats most often. Calculations for the mean, median and mode of males and females are listed below.YearMalesFemales20002,79880820012,87082220022,85179920032,90386220042,73487920052,85788620062,69581720072,72788420082,77792820092,98990120102,98197020112,91098620122,97295420133,0411,01320143,1591,095Figure 1. Deaths by Intentional Self-Harm Males vs. Females 2000-2014. Reprinted from Leading causes of death, total population, by age group and sex, Canada annual, In Statistics Canada. Retrieved from http://www5.statcan.gc.ca/cansim/a47. Copyright 2018 by Statistics Canada.Mean = ?xNMales:          = (2798 + 2870 + 2851 + 2903 + 2734 + 2857 + 2695 + 2727 + 2777 + 2989 + 2981 + 2910 + 2972 + 3041 + 3159) / 15          = 2884.27Females:          = (808 + 822 + 799 + 862 + 879 + 886 + 817 + 884 + 928 + 901 + 970 + 986 + 954 + 1013 + 1095) / 15          = 906.93Median = list values from least to greatest; middle value is the median.Males:2695, 2727, 2734, 2777, 2798, 2851, 2857, 2870, 2903, 2910, 2972, 2981, 2989, 3041, 3159Females:799, 808, 817, 822, 862, 879, 884, 886, 901, 928, 954, 970, 986, 1013, 1095Mode = value that occurs most often. Since there are no repeating values for either males or females, mode does not exist. The mathematical calculations done proves the hypothesis wrong. According to the graph, the suicide rates among males are significantly higher than females. The mean suicides over the last 15 years for males is approximately 2,884 and the median is 2,870, whereas for females it is 907 and 886 respectively. The values are about two times more than that of females. This proves that on average, males commit more suicide than females; thus refuting the hypothesis.Line of Best Fit Different regressions were used to find a correlation of determination that best fit for both males and females. Linear regression was used, as well as the regression that was most suitable and closest to one. Males:Exponential: r2= 0.415Quadratic: r2= 0.691Cubic: r2= 0.696Quartic: r2= 0.728Linear: r2= 0.426Females:Exponential: r2= 0.846Quadratic: r2= 0.881Cubic: r2= 0.892Quartic: r2= 0.894Linear: r2= 0.836Figure 2. Deaths by Intentional Self-Harm Males vs. Females 2000-2014. Reprinted from Leading causes of death, total population, by age group and sex, Canada annual, In Statistics Canada. Retrieved from http://www5.statcan.gc.ca/cansim/a47. Copyright 2018 by Statistics Canada.Though the linear regression is used, the calculations above prove that the quartic regression is the most suitable model to display the relationship between the two variables as the data points lie more appropriately along it since the values are closer to one. Based off figure 2, r2is 0.426 for men and 0.836 for women, proving that the data points lie relatively close and tightly clustered to the linear line of regression for females than males. Thus, indicating that there’s been more fluctuation in the data for males over the years while women are more consistent. Moreover, ris a measure of the direction and strength of a linear relationship of two variables (Creative Research Systems, 2018). The closer ris to one, the stronger the relationship between the two variables; time and deaths. A negative rvalue shows an inverse relationship, whereas a positive rvalue shows an increasing relationship. Rwas calculated by square rooting the r2value. r male = 0.426 = 0.653r female = 0.836 = 0.914The rvalue for males is 0.653, indicating a moderate positive correlation whereas for females is 0.914, proving a strong positive correlation. The graph is positively skewed, because as time increases, the number of suicides also increases. This further shows the difference in slopes of the two datas. As time passes, the suicides for males increases at a rate of 18.8 suicides/year, whereas for females it’s 17.3 suicides/year. Judging by the higher slope, it can be concluded that the number of suicides for males increases at a greater rate in comparison to females; thus refuting the hypothesis. Measures of SpreadInterquartile Range for MalesRange gives no specific information about how spread out the data is.Range = highest value – lowest value = 3,159 – 2,695 = 4642695, 2727, 2734, 2777, 2798, 2851, 2857, 2870, 2903, 2910, 2972, 2981, 2989, 3041, 3159Median = 2,870Q1 (25th percentile)  = 2777Q3 (75th percentile) = 2981OutliersIQR = Q3 – Q1        = 2981 – 2777        = 204Any data < Q1 - (1.5)IQR = 2777 - (1.5)204 = 2,471Any data > Q3 + (1.5)IQR = 2981 + (1.5)204 = 3,287Overall in the years 2000 to 2014, there are no values less than 2,471 or greater than 3,287, proving that there are no mathematical outliers. All the data points seem to follow a linear growth and there is no exception that skews the overall data. Moreover, the high interquartile range (204) suggests that there is a greater range of data and a larger spread of the central half of the data or its mean.Interquartile Range for Females:Range = 1,095 – 799= 296799, 808, 817, 822, 862, 879, 884, 886, 901, 928, 954, 970, 986, 1013, 1095Median = 886Q1 (25th percentile) = 822Q3 (75th percentile) = 970Outliers:IQR = Q3 – Q1        = 970 – 822        = 148 Any data < Q1 - (1.5)IQR = 822 - (1.5)148 = 600Any data > Q3 + (1.5)IQR = 970 + (1.5)148 = 1,192In the years 2000 to 2014, there are no values less than 600 or greater than 1192, thus proving that there are no mathematical outliers in the data. All the data points seem to follow a positive linear growth and there is no point significantly off that skews the overall data. Moreover, the low interquartile range (148) indicates that there is a smaller spread of the central half of the data, thus more consistent and tightly clustered data around the mean.Standard DeviationThe standard deviation shows how values in a distribution are centered about the mean. Below are the standard deviations for both males and females based off the 2000 to 2014 data. The larger the standard deviation, the greater the spread in the data.Males:= ((27982+28702+28512+29032+27342+28572+26952+27272+27772+29892+29812+29102+29722+30412+31592) – (152884.272)) /   15= 17,086= 124.69Females:= (8082+8222+7992+8622+8792+8862+8172+8842+9282+9012+9702+9862+9542+10132+10952) –  (15906.932) / 15= 6548.73= 81.67 This further refutes the hypothesis, proving that males commit more suicide than females. As shown through the calculations, the standard deviation is significantly higher for males (124.69)  than females (81.67). Thus, the high standard deviation of males shows that the data points are spread out over a wider range of values, and are more spread out from the mean. On the contrary, women are significantly less spread out as the data is more stable and steady. Furthermore, because of the wider spread for males, this essentially means that the highest value is much farther away from the average in comparison to the smaller standard deviation value of females. Z-scoresThe z score values suggest how many standard deviations the highest and lowest values of the data set are from the mean. Values are closer to the mean as the z scores approach zero. Positive values indicate how far above the value is from the mean. Similarly, negative values indicate how below the value is from the mean.Males:Highest 2014:z = (3159 – 2884.27) / 124.69   = 2.20Second highest 2013: z = (3041 – 2884.27) / 124.69   = 1.26Lowest 2006:z = (2695 – 2884.27) / 124.69    = -1.52Second lowest 2007:z = (2727 – 2884.27) / 124.69   = -1.26Females:Highest 2014:z = (1095 – 906.93) / 81.67   = 2.30Second highest 2013:z = (1013 – 906.93) / 81.67   = 1.30Lowest 2002:z = (799 – 906.93) / 81.67   = -1.32Second lowest 2000:z = (808 – 906.93) / 81.67   = -1.21 If outliers were to exist in this data, the z scores would have been evidently higher or lower than the rest of the data. Overall these calculations prove that as the z score increases, so does the suicide probability rate.Future PredictionsThe line of best fit for males is y=18.8x+2752. For females, it is y=17.3x+786.Using these equations, values for ‘y’ can be found in order to determine the suicides in ‘x’ year.LimitationsThousands are rushed to the hospital every year due to self-harm injuries however, sometimes it can be difficult to distinguish between intentional and unintentional self-harm behaviors. For example, intentional could be one purposely hanging themselves, whereas unintentional could be a child accidentally choking themselves to death. Moreover, though Statics Canada is a reliable website many attempts go unreported or untreated (American Foundation for Suicide Prevention, 2018), which is known as a non-response bias. These limitations result in some bias and overall less accurate information and calculations.AssumptionsSince this is a statistic of the entire population of Canada, it is hard to distinguish age groups or provinces/territories where most suicides may have taken place. So the assumption is that all age groups and provinces have equal factors leading to suicide. When in reality, there may be a main cause for a younger age group and an entirely different purpose of suicide for an older group. The suicide rate could also be significantly higher for one place, and low for another based off different factors like sexual abuse, crimes or economic wealth, but it is unclear and hard to differentiate as this data is treated as an entire population. Future Considerations Research suggests that more suicides occur in Asia and Eastern Europe, however only suicides in Canada were compared. The results could have been significantly different if international suicides were studied. (World Psychiatry, 2015). For future considerations, international suicide rates could be determined based on economic factors of different countries, or different provinces/territories in Canada, or socioeconomic positions of individuals. Also, different age groups could be compared and studied to understand why the rates for the group may be higher than others. This could help researchers to identify and narrow the main factors that cause people to perform this act of suicide, and help them implement preventative methods to reduce the rate as much as possible.Conclusion Through mathematical analysis, it can be concluded that the hypothesis was inaccurate and in fact, males commit more suicide than females as observed through the 2000-2014 Canada Suicide Statistics. Overall, men seemingly had higher mean and medians which showed how men commit more suicide on average. Mathematical reasoning further proves that males had a smaller correlation coefficient value, meaning there was a moderate positive linear relationship between the two variables whereas females had a strong positive linear correlation. This fluctuation further shows how males make irrational and impulsive decisions and have a higher suicide rate. Moreover, when comparing the line of best fits, it was undeniable that the slope for males was higher than that for females. This goes on to show that the suicide rate for males increases at a quicker rate annually.It is still undetermined if there are other outside factors or variables which have contributed to the significant intentional self-harm of males, and is difficult to recognize and address this issue exactly. This can be considered a common cause relationship as there are many factors leading to suicide and different methods of suicide that can vary per province in Canada, per individual. Overall, this research refutes the hypothesis and the reason for this “gender paradox” in suicidal behaviour could be due to many factors, which is very intriguing. Stereotypically, men are thought of as the more dominant beings, thus, are imagined to be a certain way; in control of their emotions, and overall stronger  (Powell, 2015). While women are more emotionally expressive, men are not (May, 2017). Furthermore, there are various hormonal differences between the two genders. These hormonal differences suggest that a reason suicides are so high for  men could be due to testosterone. Testosterone can change almost suddenly and are highest around ages 20 to 30. After ages 30 to 35, they usually go down. Research states that there is a higher rate of suicide for males around the ages 45 to 54 and this could be why, as men with low testosterone may experience mood swings and is one of the major causes of  depression; a symptom of suicide. (Integrated Psychiatry, 2017). Another factor could be the increase of “feminisation” of employment in today’s world. This makes them feel less involved in the professional world, thus losing a sense of their masculine identity and pride. Employment can be difficult for them as well, since if they lose their jobs, they cannot provide for the family and lose that pride (Walton, 2012). Males are expected to meet societal expectations as “masculine” or told to “man up” when any signs of weakness are shown. This could be a reason why science proves that males have a higher threshold for pain in attempts to reach these expectations, ultimately leading to a higher risk of suicide as it builds up. Overall, leading to impulsive and poor decisions. In addition, both males and females equally consider suicide, however males are more likely to die from these attempts as they use more destructive methods, such as firearms and hanging, where females are more likely to use drugs and overdose. Since males uses more lethal methods, it results in immediate death.

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