Or mine means that itself and 1 can only go into it. Conposit means that multiple numbers can go into it like 24. 12,6,8,2 can all go into it
        
             
        
        
        
Answer:
X is the GPA 
Y is the Salary 
Standard deviation of X is 0.4
Standard deviation of Y is 8500
E(X)=2.9
E(Y)=47200
We are given that The correlation between the two variables was r = 0.72
a)


So, slope =  15300
Intercept =  2830
So, equation : 
b) Your brother just graduated from that college with a GPA of 3.30. He tells you that based on this model the residual for his pay is -$1880. What salary is he earning?

Observed salary = Residual + predicted = -1860+53320 = 51440
c)) What proportion of the variation in salaries is explained by variation in GPA?
 The proportion of the variation in salaries is explained by variation in GPA = 
 
        
             
        
        
        
Answer:
-3 degrees C
Step-by-step explanation:
We need to subtract 3 degrees from Thursdays temperature
0 - 3
-3 degrees C
 
        
             
        
        
        
Answer:
noisy I think because of how they're describing them
 
        
                    
             
        
        
        
Answer:

And we can calculate the p value with the following probability taking in count the alternative hypothesis:

And for this case using a significance level of  we see that the p value is larger than the significance level so then we can conclude that we FAIL to reject the null hypothesis and we don't have enough  evidence to conclude that the true proportion is less than 0.02
 we see that the p value is larger than the significance level so then we can conclude that we FAIL to reject the null hypothesis and we don't have enough  evidence to conclude that the true proportion is less than 0.02 
Step-by-step explanation:
For this case we want to test the following system of hypothesis:
Null hypothesis: 
Alternative hypothesis: 
The statistic for this case is given by:
 (1)
 (1)  
And for this case we know that the statistic is given by:

And we can calculate the p value with the following probability taking in count the alternative hypothesis:

And for this case using a significance level of  we see that the p value is larger than the significance level so then we can conclude that we FAIL to reject the null hypothesis and we don't have enough  evidence to conclude that the true proportion is less than 0.02
 we see that the p value is larger than the significance level so then we can conclude that we FAIL to reject the null hypothesis and we don't have enough  evidence to conclude that the true proportion is less than 0.02