Week 8 “Final Project” This week, you must submit a final project in a traditional paper, PowerPoint Presentation, and a video where you orally discuss the work that you did throughout the term. The...

Suicides in the united states
Table of Contents
Executive Summary    2
Objectives    2
Results    2
Conclusions    2
Recommendations    2
Introduction: Background and Objectives    3
Methodology    4
Objective 1    4
Methodology for other objectives    4
Results    5
Objective 2    5
Objective 3    5
Objective 4    5
Limitations    7
Conclusions and Recommendations    8
Appendix    9
Detailed calculations    9
Objective 2    9
Objective 3    9
Objective 4    10
General tables    13
Objective 1    13
Reference    17
Executive Summary
Objectives
The objective of this report is to collect the data regarding the number of suicides in the United States during the time span 2000-2015. The trend of the number of suicides should be analysed. It is required to test if the number of suicides is Greater for males in comparison to females. Building a regression model to predict the number of suicides is also an area of concern.
Results
The average number of suicides for males and females is 4725 and 1269 respectively.
The regression model is given by total suicides = 1124 + 0.000187*population -0.0286*gdp_per_capita + 81.35*time -3600*female.
Conclusions
There is an increasing trend in the total number of suicides in the United States from the year 2001 till the year 2015. There is sufficient evidence to conclude that the average number of suicides for males is Greater and comparison to females. Population and gender are significant predictors of total suicides in the United States.
Recommendations
It is recommended to providing a free counselling session regarding how stay happy in life and target low-income levels groups.
Introduction: Background and Objectives
The purpose of this report is to analyze the number of suicides in the United States. The Other variables considered for the purpose of the analysis is the population of the United States in the corresponding year, Gross Domestic Product per capita, year and gender. 
The suicides rates in the United States has increased from the year 1999 through 2014, with a greater annual percentage increases after the year 2006. It was reported that deciding traits for Siemens work printer in the year 2014 in comparison to the year 1999 considering the age group under 75 years of age. The same was reported for male suicides. The suicide cases of suffocation have increased from 1999 through the year 2014. However, a decrease in the percentage of suicide involving firearms and poisoning has decreased from the year 1999 in comparison to the year 2014. Curtin, S. C., Warner, M., & Hedegaard, H. (2016).
The objective of this report is:
1) To collect the data regarding the number of suicides in the United States during the time span 2000-2015.
2) To analyze the trend of the number of suicides in the United States from the Year 2000 until the year 2015.
3) to test if the number of suicides is Greater for males in comparison to females
4) To build a regression model which can predict the number of suicides in the United States
Methodology
Objective 1
This is secondary research and the source of the data is kaggle.com. The data is obtained from is https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016 The variables which are measured by the ratio scale of measurement are the number of suicides, population, suicides per 100k population, HDI for the year, Gross domestic product (GDP) for the year, and Gross domestic product (GDP) per capita. The variables Gross domestic product (GDP) for the year, and Gross domestic product (GDP) per capita are measured in USD dollars. This data is filtered for the country of the United States. For that filters are applied to obtain the data for the year 2000-2015 only. 
Methodology for other objectives
The line chart is used as a method of visualization to analyze the trend of the total number of suicides in the United States from the year 2001 to 2015.
T-test for independent samples is used to test the hypothesis if the average number of suicides for males is greater than that of females. Since the two groups of male and females are independent of each other, It is sufficient to use a t-test for independent samples.
The technique of regression analysis is used for predicting the number of suicide in the United States. The dependent variable is the total number of suicides. The independent variables are population, Gross Domestic Product per capita, time (1 corresponding to the year 2000), and female.
All the analysis is carried out in Excel. T-test and regression analysis from the data analysis is used to obtain the output.
Results
Objective 2
There is a continuous increasing trend in the total number of suicides in the United States from the year 2001 till the year 2015.
Figure 1
The total number of suicides was 29343 only in the year 2000. This has increased tremendously to 44189 in the year 2015.
Objective 3
The average number of suicides for males is Greater in comparison to females. The average number of suicides per year for males is 4725 in comparison to 1269 for females.
Figure 2
The null hypothesis, there is no significant difference in the average number of suicides between males and females. This is tested against an alternative hypothesis, the average number of suicides for males is Greater and comparison to females. From table 3, t=9.34, p<5%, the null hypothesis is rejected at 5% level of significance. There is sufficient evidence to conclude that the average number of suicides for males is Greater and comparison to females.
Objective 4
From table 6, the regression model is given by total suicides = 1124 + 0.000187*population -0.0286*gdp_per_capita + 81.35*time -3600*female
The null hypothesis is the regression model is not significant. This is tested against an alternative hypothesis, the regression model is significant. From table 5, (F=116, p<5%), the null hypothesis is rejected at 5% level of significance. There is sufficient evidence to conclude that the model is significant.
From table 4, the coefficient of determination, R square is 0.71. There is 71% variation in the total number of suicides which is explained by population, GDP per capita, time, and females.
With one individual increase in the population of the United States, the total number of suicides increased by 0.000187. From table 6, this value is significant at 5% level of significance with t=15.8011, p<5%.
With one $ increase in the Gross Domestic Product per capita the United States, the total number of suicides decreased by -0.0286. From table 6, this value is NOT significant at 5% level of significance with t=-0.28755, p>5%.
Every year, the total number of suicides increased by 81. From table 6, this value is NOT significant at 5% level of significance with t=0.586619, p>5%.
For females, the total number of suicide is 3600 less in comparison to that of males. From table 6, this value is significant at 5% level of significance with t=14.9142, p<5%.
Limitations
The limitation of using a line chart is that the variable represented on the y-axis should be quantitative variable.
The limitation of using a t-test for independent samples with equal variances is the homogeneity of variances between two groups. It is also required that the two groups of the independent variables should not be related to each other.
The limitation of regression analysis lies in this assumption. One of the main assumptions of regression analysis is the normality of residuals. From figure 7, the non-S-shaped indicates that this assumption is violated. Another assumption is the equality of error variances. The random pattern in figure 3, 4 and 5, indicates that the variance of errors is constant. Hence the assumption of the equality of error variances is satisfied in this case. 
Conclusions and Recommendations
There is a continuous increasing trend in the total number of suicides in the United States from the year 2001 till the year 2015. There is sufficient evidence to conclude that the average number of suicides for males is Greater and comparison to females. The regression model is given by total suicides = 1124 + 0.000187*population -0.0286*gdp_per_capita + 81.35*time -3600*female. With one individual increase in the population of the United States, the total number of suicides increased by 0.000187. For females, the total number of suicide is 3600 less in comparison to that of males.
In order to control the suicide in rates in the United States, it is recommended to providing a free counselling session. This session should include a talk regarding how to refresh self and stay happy in life. It is recommended to focus on individuals with low-income levels.
Appendix
Detailed calculations
Objective 2
Table 1
    Row Labels
    Sum of suicides_no
    2000
    29343
    2001
    30607
    2002
    31645
    2003
    31477
    2004
    32428
    2005
    32629
    2006
    33292
    2007
    34596
    2008
    36030
    2009
    36900
    2010
    38362
    2011
    39508
    2012
    40596
    2013
    41143
    2014
    42769
    2015
    44189
    Grand Total
    575514
Objective 3
Table 2
    
    Male
    Female
    mean
    4725.09375
    1269.84375
    sd
    3430.151815
    1164.172761
Table 3
    t-Test: Two-Sample Assuming Equal Variances
    
    
    
     
    suicides_males
    suicides_females
    Mean
    4725.09375
    1269.84375
    Variance
    11765941.48
    1355298.217
    Observations
    96
    96
    Pooled Variance
    6560619.846
    
    Hypothesized Mean Difference
    0
    
    df
    190
    
    t Stat
    9.346040478
    
    P(T<=t) one-tail
    1.26241E-17
    
    t Critical one-tail
    1.652912949
    
    P(T<=t) two-tail
    2.52482E-17
    
    t Critical two-tail
    1.972528182
     
Objective 4
Table 4
    SUMMARY OUTPUT
    
    
    Regression Statistics
    Multiple R
    0.844348
    R Square
    0.712924
    Adjusted R Square
    0.706783
    Standard Error
    1671.333
    Observations
    192
Table 5
    ANOVA
    
    
    
    
    
     
    df
    SS
    MS
    F
    Significance F
    Regression
    4
    1.3E+09
    3.24E+08
    116.0989
    1.42E-49
    Residual
    187
    5.22E+08
    2793353
    
    
    Total
    191
    1.82E+09
     
     
     
Table 6
     
    Coefficients
    Standard Error
    t Stat
    P-value
    Lower 95%
    Upper 95%
    Lower 95.0%
    Upper 95.0%
    Intercept
    1124.234
    3801.711
    0.295718
    0.767774
    -6375.52
    8623.987
    -6375.52
    8623.987
    population
    0.000187
    1.19E-05
    15.8011
    2.8E-36
    0.000164
    0.000211
    0.000164
    0.000211
    gdp_per_capita ($)
    -0.0286
    0.099454
    -0.28755
    0.774008
    -0.22479
    0.167598
    -0.22479
    0.167598
    time
    81.35867
    138.6908
    0.586619
    0.558167
    -192.241
    354.9584
    -192.241
    354.9584
    female
    -3600.46
    241.4111
    -14.9142
    1.19E-33
    -4076.7
    -3124.22
    -4076.7
    -3124.22
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
General tables
Objective 1
Table 7
    suicides_no
    population
    gdp_per_capita...