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Faith Owens

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History1Business4Chemistry5

**URGENT** due in a few hours. Please do all of the parts. Directions are in the picture

Since 2014, the United Nations has conducted annual studies that measure the level of happiness among its member countries. Experts in social science and psychology are commissioned to collect relevant data and define measurements related to happiness. Happiness measurements are based on survey questions such as how people feel about their life (i.e. life ladders) levels of positive and negative emotion, freedom to make choices (life choices) and aggregated indicators such as social support, life expectancy, and relative household income. These data are converted into numerical scores for each member country. The accompanying table shows a portion of the United Nation's happiness data.

Country Life Ladder Social Support   Household Income
Albania 4.4623 0.5582 0.3317
Argentina 6.5133 0.8922 0.2726
       
Zimbabwe 3.7570 0.8534 0.5242
 
a. Conduct principal component analysis on all the variables except the Country variable. Should you standardize the data?
  ◯ Yes
  ◯ No
 
b. What percent of the total variability is accounted for by the first principal component? How many principal components must be retained in order to account for at least 80% of the total variance in the data? (Show your final answer as a percentage point with 2 decimal places)
 
   
Percent of the total variability  
Number of principal components  

c-1. Display the weights used to compute the first principal component scores. (Round your final answers to 4 decimal places.) 

  Weight
Life ladder  
Social support  
Positive emotion  
Negative emotion  
Life choices  
Life expectancy  
Household income index  

c-2. Which original variable is given the highest weight to compute the second principal component? 

   was given the most weight to compute the second principal component

d. What is the principal component 1 score for the first record (Albania)? (Round your final answer to 4 decimal places.)

The first record (Albania) had a score of   for the first principal component

 

 

*****URGENT****** due in a few hours. Please help

A national bank has developed a predictive model for identifying customers who are more likely to accept a credit card offer. If a customer is predicted to accept the credit card offer, he or she is classified into Class 1; otherwise, he or she is classified into Class 0 . Applying the model to the validation data set generated a table that lists the actual class membership and predicted Class 1 probability of the 100 observations in the validation data set. A portion of the table is shown below.

Customer Actual Class Predicted Class 1 Probability
1 0 0.30
2 0 0.57
     
100 1 0.50
 
a-1. Specify the predicted class membership for the validation data set using the cutoff value of 0.25. Produce a confusion matrix. 
 
Actual Class Predicted Class 1 Predicted Class 0
Class 1    
Class 0    
 
a-2. Specify the predicted class membership for the validation data set using the cutoff value of 0.50. Produce a confusion matrix. 
 
Actual Class Predicted Class 1 Predicted Class 0
Class 1    
Class 0    
 
a-3. Specify the predicted class membership for the validation data set using the cutoff value of 0.75. Produce a confusion matrix. 
 
Actual Class Predicted Class 1 Predicted Class 0
Class 1    
Class 0    

b.1. Compute the misclassification rate, accuracy rate, sensitivity, precision, and specificity of the classification model for the cutoff value of 0.25. (Round your final answers to 2 decimal places.)

   
Misclassification rate  
Accuracy rate  
Sensitivity  
Precision  
Specificity   

b-2. Compute the misclassification rate, accuracy rate, sensitivity, precision, and specificity of the classification model for the cutoff value of 0.50. (Round your final answers to 2 decimal places.)

   
Misclassification rate  
Accuracy rate  
Sensitivity  
Precision  
Specificity   

b-3. Compute the misclassification rate, accuracy rate, sensitivity, precision, and specificity of the classification model for the cutoff value of 0.75. (Round your final answers to 2 decimal places.)

   
Misclassification rate  
Accuracy rate  
Sensitivity  
Precision  
Specificity   

c-1. Create a cumulative lift chart for the classification modes. At 60 cases, what is the cumulative response using the sorted predicted values?

Cumulative response using the sorted predicted values  

c-2. Crease a decile wise lift chart for the classification model. What is the lift value of the first decile? 

Lift value of the first decile  

d. What is the lift that the classification model provides if 20% of the observations are selected by the model compared to randomly selecting 20% of the observations? (Round your final answer to 2 decimal places)

Lift (1.20)  

e. What is the it that the classification model provides 50%  of the observations are selected by the model compered so randomly selecting 50 s of the observations? (Round your final answer to 2 decimal places)

Lift (1.50)  

 

***URGENT**** These are answered. Please let me know if my answers are right, and if they are wrong please answer with the correct answers. There are multiple parts. I need the answers within a couple hours.

Consider the following portion of data that lists the starting salaries (in $ 1000) of newly hired employees and their college GPAs: 

Employee Salary GPA
1 57 3.39
2 74 2.88
3 80 3.58
     
11 61 3.37

a. Without transforming the values, compute the Euclidean distance for all possible pairs of the first three employees. (Round immediate calculations to at least 4 decimal places and your final answers to 2 decimal places.)

Employees Euclidean distance 
1 and 2 89.06
1 and 3 93.35
2 and 3 104.369

b-1. Compute the z-score standardized salaries and Ga4s for the first three employees. (Round intermediate calculations to at least 4 decimal places and your final answers to 2 decimal places. Negative values should be indicated by a minus sign.)

Employees Standardized salaries () Standardized GPAs ()
1 0.82 0.11
2 0.22 -1.61
3 0.59 0.82

b-2. Based on the z-score standardized salaries and GPAs, compute the Euclidean distance for al possible pairs of the first three employees. (Round intermediate calculations to at least 4 decimal places and your final answers to 2 decimal places.)

Employees Standardized salaries ()
1 and 2 2.06
1 and 3 0.95
2 and 3 1.84

c-1. Based on the z-score standardized salaries and GPAs, compute the Manhattan distance for al possible pairs of the first three employees. (Round intermediate calculations to at least 4 decimal places and your final answers to 2 decimal places.)

Employees Standardized salaries ()
1 and 2 2.77
1 and 3 1.10
2 and 3 1.99
 
C-2. Based on the z-score standardized Manhattan distance values, identify the pair of the first three employees that are most similar.
◯ Employees 2 and 3
◯ Employees 1 and 3
◯ Employees 1 and 2
◯ Undetermined, because the Manhattan distance values give inconclusive results.
Good

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