Correlation and Regression

In summary, the conversation involves discussing data on per capita cigarette consumption and deaths from coronary heart disease in various countries. The coefficient of determination is mentioned as 0.607, indicating a potential link between the two variables. The question is then posed about using an ax+b equation to predict the number of deaths in a country with a per capita consumption of 2000 cigarettes. The conversation ends with the expert asking for the solution to be shared for the benefit of the community.
  • #1
aprilryan
20
0
I just need a little assistance on the last two questions. I place per capita and death in L1 and L2 but I am lost.

Country Per Capita Cigarette Consumption
3900
United States 3350
Canada 3220
Australia 3220
New Zealand 2790
United Kingdom 2770
Ireland 2290
Finland 2160
West Germany 1890
Netherlands 1810
Austria 1770
Belgium 1700
Mexico 1680
Italy 1510
Sweden 1270
Spain 1200
Norway 1090

Deaths from Coronary Heart Disease (per 100,000)
259.9
211.6
238.1
211.6
238.1
211.8
194.1
187.3
110.5
233.1
150.3
124.7
182.1
118.1
31.9
114.3
126.9
43.9
136.3

3. What does the coefficient of determination indicate about the relationship?
Would the coefficient of 0.607 indicate there's a link between the variables?4. Use the data above to predict the number of death (per 100,000) in a country with a per capita consumption of cigarettes of 2000.

Would the ax+b equation be useful here?

Sorry, I know this one is a little long.
 
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  • #2
Nevermind I got i!
 
  • #3
aprilryan said:
Nevermind I got i!

Would you mind posting your solution for the benefit of the community?
 
  • #4
Sure! I got 0.607.
 

1. What is correlation and regression?

Correlation and regression are statistical methods used to measure the strength of a relationship between two variables. Correlation measures the linear relationship between two continuous variables, while regression predicts the value of one variable based on the value of another variable.

2. How do you interpret a correlation coefficient?

A correlation coefficient, also known as the Pearson correlation coefficient, ranges from -1 to 1. A value of -1 indicates a perfect negative correlation, 0 indicates no correlation, and 1 indicates a perfect positive correlation. The closer the value is to 0, the weaker the relationship.

3. What is the difference between correlation and causation?

Correlation does not imply causation. Just because two variables are strongly correlated does not necessarily mean that one causes the other. There could be other factors at play that are causing the observed relationship.

4. How do you perform a regression analysis?

To perform a regression analysis, you will need to first collect data on the two variables of interest. Then, you will need to plot the data on a scatter plot and calculate the correlation coefficient. Finally, you can use a statistical software or calculator to perform a linear regression and obtain the regression equation.

5. What is the purpose of using correlation and regression in scientific research?

Correlation and regression are used in scientific research to understand the relationship between two variables and make predictions based on that relationship. They can also be used to identify potential causation and inform decision-making processes.

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