Loading presentation...

Present Remotely

Send the link below via email or IM


Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.



No description

Fay Qi

on 4 April 2013

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of Statistic

Xiaoxia Duan

Xianfang Tang

Xuejing Wang

Yang Dai

Fei Qi Research of Crime In Canada Two-Sample t-Test Independence assumption Two-Sample t-Test whether the crime is worse in larger cities than in small cities Congratulations Finally, we find the exit! Background Introduction
Large cities are more dangerous than small ones?
In this case, Crime Severity Index(CSI) and populations in each city are the two main factors we want to analyze. CATALOGUE 1. Introduction and Crime Severity
2. Map Of Regions and Scatterplots
3. Linear Correlation Between Regions
4. Linear Correlation Between Large &
Small Cities
5. T-Test (Part 1)
6. T-Test (Part 2)
7. Conclusion
8. Q & A Important Defination Crime Severity Index (CSI) : An Index based on the seriousness of crimes.

Higher the CSI is, more serious crime rate is existing in the city. Lin Zhu Hao Zhang Canada Regional Map Atlantic Quebec Ontario Prairies West Regional Scatterplots Conclusion Big Cities' Correlation Small Cities' Scatterplots Correlation and Scatterplots Big Cities' Scatterplots Small Cities' Correlation Now it's time for QUESTIONS Both variables are quantitative Plot linear no outliers The correlation of big cities
is -0.53925, it is negative The correlation of small cities
is -0.09028, it is negative Randomization condition Independent group assumption Nearly normal condition Using software, we obtain the following basic statistics: The difference is not statistically significant,with a P-value:0.34>0.05. So This value fail to reject the null hypothesis. R= -0.53925
negative correlation R= -0.09028
negative correlation R=0.31888 R=0.63636 R=-0.23757 R=-0.79389 R=-0.55186
Full transcript