STATS - Week 4 Confidence Intervals and Chi Square (Chs 11 - 12)

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Week 4 Confidence Intervals and Chi Square  (Chs 11 - 12)       Let's look at some other factors that might influence pay.     
For question 3 below, be sure to list the null and alternate hypothesis statements.  Use .05 for your significance level in making your decisions.           
For full credit, you need to also show the statistical outcomes - either the Excel test result or the calculations you performed.
           
1 One question we might have is if the distribution of  graduate and undergraduate degrees independent of the grade the employee?            
 (Note: this is the same as asking if the degrees are distributed the same way.)          
 Based on the analysis of our sample data (shown below), what is your answer?          
 Ho: The populaton correlation between grade and degree is 0.          
 Ha: The population correlation between grade and degree is > 0          
 Perform analysis:          
OBSERVED A  B C D E F Total    
COUNT - 0 (Deg) 7 5 3 2 5 3 25    
 COUNT - 1 (Deg) 8 2 2 3 7 3 25    
Total 15 7 5 5 12 6 50    
EXPECTED           
 7.5 3.5 2.5 2.5 6 3 25    
 7.5 3.5 2.5 2.5 6 3 25    
 15 7 5 5 12 6 50    
By using either the Excel Chi Square functions or calculating the results directly as the text shows, do we reject or not reject the null hypothesis?  What does your conclusion mean?
2 Using our sample data, we can construct a 95% confidence interval for the population's mean salary for each gender. Interpret the results.  How do they compare with the findings in the week 2 one sample t-test outcomes (Question 1)? 
3 Based on our sample data, can we conclude that males and females are distributed across grades in a similar pattern within the population?   
 Ho: The populaton correlation between grade and degree is 0.
 Ha: The population correlation between grade and degree is > 0 
4 Using our sample data, construct a 95% confidence interval for the population's mean service difference for each gender.  Do they intersect or overlap?  How do these results compare to the findings in week 2, question 2? 
5 How do you interpret these results in light of our question about equal pay for equal work?                
               
               
      

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    STATS - Week 4 Confidence Intervals and Chi Square (Chs 11 - 12)
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