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business analytics and machine learning
Question 2: Machine Learning a) Which of unsupervised or supervised machine learning is best suited to assessing causatio ...
business analytics and machine learning
Question 2: Machine Learning a) Which of unsupervised or supervised machine learning is best suited to assessing causation? Explain your choice. b) Your analytics team presents you with two sets of results that have improved the organization’s ability to predict customer defections. The first method uses deep learning and has a precision of 85%. The second method uses decision trees and has a precision of 70%. The previous approach had a precision of 40%. i) Make a case for using the results of the deep learning method. ii) Make a case for using the decision tree method. In your answers, consider aspects of customer lifetime value and managerial decision making. c) An analytics team used two different models to predict the likelihood of an outcome. The results from two different analysts are below: Don’s Analysis Actual Positive Negative Predicted Positive 220 100 Negative 30 650 Katie’s Analysis Actual Positive Negative Predicted Positive 170 10 Negative 80 740 i) Use the Confusion Matrix and Index Calculation tables below to calculate the model performance measures. Confusion Matrix Actual Positive Negative Predicted Positive TP FP Negative FN TN Formula Don Calculation Katie Calculation Accuracy (completed as an example) (TP + TN) / (TP + TN + FP + FN) (220 + 650) / (220 + 650 + 100 + 30) 0.87 (170 + 740) / (170 + 740 + 10 + 80) 0.91 Precision TP / (TP + FP) Error rate (FP + FN) / (TP + TN + FP + FN) Recall TP / (TP + FN) Specificity TN / (TN + FP) False positive rate FP / (TN + FP) F-score 2* ((Precision*Recall) / (Precision + Recall)) ii) Describe a medical or business context where you would prefer to use Don’s model. Why do you prefer Don’s model? iii) Describe a medical or business context where you would prefer to use Katie’s model. Why do you prefer Katie’s model? Ian is an intern with the team who claims he made a breakthrough with a model that outperforms both Don’s and Katie’s. The confusion matrix for his model is below: Ian’s Analysis Actual Positive Negative Predicted Positive 249 2 Negative 1 748 iv) What could possibly have gone wrong that would result in his results being invalid? How could this be solved? (15 marks) Question 3: Experiments Jennifer was given the results of an experiment that was designed to determine if a 10% reduction in price on an online shopping portal would lead to an increase in purchases. Control and treatment group were created. These groups are described below: Control Group Treatment Group Number of males 25 25 Number of females 25 25 Average age 47 years 37 years Average spend per visit in the month BEFORE the experiment $25.00 $25.00 Average spend per visit in the month AFTER the experiment $25.00 $29.00 a) Were the control and treatment groups effectively randomized? Why or why not? b) What are the two most likely explanations for the treatment groups showing a higher average spend than the control group? c) What type of analysis could be used to remove one of the possible explanations for the difference in average spend? d) Experiments are useful in helping determine if people have responded due to a stimulus or if they would have responded even without the stimulus. Design an experiment that could demonstrate what proportion of people have responded to a stimulus. These people could be customers or employees within a company. Examples could be an advertising campaign to customers, or a policy of flexible work hours for employees. Requirements: i) How would you pick the treatment and control groups? Fill in the table below to indicate the number of people and 3 important characteristics that describe each group Control Group Treatment Group People Characteristic 1: Characteristic 2: Characteristic 3: ii) Predict the results and state the managerial conclusion you could make from this result. Use the table below to indicate the change in behavior you expect to observe. Control Group Treatment Group Observed behavior before treatment: Observed behavior after treatment: iii) State the managerial action you could take from the results of your experiment. Briefly describe a useful follow-up experiment that would further deepen understanding of why people behaved in the manner observed.
1-1 Discussion: Practical Approach to Applied Statistics
Can data from an experiment ever be both discrete and continuous? Explain your answer.Refer to the Discussion Rubric for d ...
1-1 Discussion: Practical Approach to Applied Statistics
Can data from an experiment ever be both discrete and continuous? Explain your answer.Refer to the Discussion Rubric for directions on completing these discussions.
kaplan-meier survival curve
The AssignmentUsing Week 8 Dataset (SPSS document) from the Learning Resources area, answer the following:DataCreate a var ...
kaplan-meier survival curve
The AssignmentUsing Week 8 Dataset (SPSS document) from the Learning Resources area, answer the following:DataCreate a variable for Time-to-event by subtracting the start time (variable = start) from the stop time (variable = stop). Label the new variable “Time”.Produce the appropriate descriptive statistics, numerical and graphical, for the following variables:EventIntervalTxNumSizeTimeKaplan-Meier Survival Analysis (Without factor or Strata)Run a Kaplan-Meier analysis in SPSS, using Time as the Time variable and Event as the Status variable (Be sure to define the event). Do not add a factor or strata at this time.Produce a Survival Table (you do not need to submit this)Produce a plot of the survival functionWhat is the mean survival time (include confidence intervals)? What is the median survival time (include confidence intervals)? Why do you think they are so different from each other?Kaplan-Meier Survival Analysis (With Factor)Run a Kaplan-Meier analysis in SPSS, using Time as the Time variable and Event as the Status variable (Be sure to define the event). Add Tx as the factor.Test the difference between Tx groups (Compare Factor) using Log-Rank, Breslow, and Tarone-WareProduce a plot of the survival functionDescribe what the Overall Comparisons mean in terms of treatment groups and survival times.Kaplan-Meier Survival Analysis (With Strata)Run a Kaplan-Meier analysis in SPSS, using Time as the Time variable and Event as the Status variable (Be sure to define the event). Add Interval as the Strata variable.Produce a plot of the survival function for each strata.Why would you want to produce Kaplan-Meier Survival Curves after stratifying for a variable?Resources: Daniel, WW & Cross, CL. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. Hoboken, NJ: Wiley.Chapter 14: Survival Analysis (pp. 750-767
GCU Wk 5 Summary and Descriptive Statistics Measures of Central Tendency Worksheet
Summary and Descriptive Statisticsthere is often the requirement to evaluate descriptive statistics for data within the or ...
GCU Wk 5 Summary and Descriptive Statistics Measures of Central Tendency Worksheet
Summary and Descriptive Statisticsthere is often the requirement to evaluate descriptive statistics for data within the organization or for health care information. Every year the National Cancer Institute collects and publishes data based on patient demographics. Understanding differences between the groups based upon the collected data often informs health care professionals towards research, treatment options, or patient education.Using the data on the "National Cancer Institute Data" Excel spreadsheet, calculate the descriptive statistics indicated below for each of the Race/Ethnicity groups. Refer to your textbook and the Topic Materials, as needed, for assistance in with creating Excel formulas.Provide the following descriptive statistics:Measures of Central Tendency: Mean, Median, and ModeMeasures of Variation: Variance, Standard Deviation, and Range (a formula is not needed for Range).Once the data is calculated, provide a 150-250 word analysis of the descriptive statistics on the spreadsheet. This should include differences and health outcomes between groups.APA style is not required, but solid academic writing is expected.This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
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Most Popular Content
business analytics and machine learning
Question 2: Machine Learning a) Which of unsupervised or supervised machine learning is best suited to assessing causatio ...
business analytics and machine learning
Question 2: Machine Learning a) Which of unsupervised or supervised machine learning is best suited to assessing causation? Explain your choice. b) Your analytics team presents you with two sets of results that have improved the organization’s ability to predict customer defections. The first method uses deep learning and has a precision of 85%. The second method uses decision trees and has a precision of 70%. The previous approach had a precision of 40%. i) Make a case for using the results of the deep learning method. ii) Make a case for using the decision tree method. In your answers, consider aspects of customer lifetime value and managerial decision making. c) An analytics team used two different models to predict the likelihood of an outcome. The results from two different analysts are below: Don’s Analysis Actual Positive Negative Predicted Positive 220 100 Negative 30 650 Katie’s Analysis Actual Positive Negative Predicted Positive 170 10 Negative 80 740 i) Use the Confusion Matrix and Index Calculation tables below to calculate the model performance measures. Confusion Matrix Actual Positive Negative Predicted Positive TP FP Negative FN TN Formula Don Calculation Katie Calculation Accuracy (completed as an example) (TP + TN) / (TP + TN + FP + FN) (220 + 650) / (220 + 650 + 100 + 30) 0.87 (170 + 740) / (170 + 740 + 10 + 80) 0.91 Precision TP / (TP + FP) Error rate (FP + FN) / (TP + TN + FP + FN) Recall TP / (TP + FN) Specificity TN / (TN + FP) False positive rate FP / (TN + FP) F-score 2* ((Precision*Recall) / (Precision + Recall)) ii) Describe a medical or business context where you would prefer to use Don’s model. Why do you prefer Don’s model? iii) Describe a medical or business context where you would prefer to use Katie’s model. Why do you prefer Katie’s model? Ian is an intern with the team who claims he made a breakthrough with a model that outperforms both Don’s and Katie’s. The confusion matrix for his model is below: Ian’s Analysis Actual Positive Negative Predicted Positive 249 2 Negative 1 748 iv) What could possibly have gone wrong that would result in his results being invalid? How could this be solved? (15 marks) Question 3: Experiments Jennifer was given the results of an experiment that was designed to determine if a 10% reduction in price on an online shopping portal would lead to an increase in purchases. Control and treatment group were created. These groups are described below: Control Group Treatment Group Number of males 25 25 Number of females 25 25 Average age 47 years 37 years Average spend per visit in the month BEFORE the experiment $25.00 $25.00 Average spend per visit in the month AFTER the experiment $25.00 $29.00 a) Were the control and treatment groups effectively randomized? Why or why not? b) What are the two most likely explanations for the treatment groups showing a higher average spend than the control group? c) What type of analysis could be used to remove one of the possible explanations for the difference in average spend? d) Experiments are useful in helping determine if people have responded due to a stimulus or if they would have responded even without the stimulus. Design an experiment that could demonstrate what proportion of people have responded to a stimulus. These people could be customers or employees within a company. Examples could be an advertising campaign to customers, or a policy of flexible work hours for employees. Requirements: i) How would you pick the treatment and control groups? Fill in the table below to indicate the number of people and 3 important characteristics that describe each group Control Group Treatment Group People Characteristic 1: Characteristic 2: Characteristic 3: ii) Predict the results and state the managerial conclusion you could make from this result. Use the table below to indicate the change in behavior you expect to observe. Control Group Treatment Group Observed behavior before treatment: Observed behavior after treatment: iii) State the managerial action you could take from the results of your experiment. Briefly describe a useful follow-up experiment that would further deepen understanding of why people behaved in the manner observed.
1-1 Discussion: Practical Approach to Applied Statistics
Can data from an experiment ever be both discrete and continuous? Explain your answer.Refer to the Discussion Rubric for d ...
1-1 Discussion: Practical Approach to Applied Statistics
Can data from an experiment ever be both discrete and continuous? Explain your answer.Refer to the Discussion Rubric for directions on completing these discussions.
kaplan-meier survival curve
The AssignmentUsing Week 8 Dataset (SPSS document) from the Learning Resources area, answer the following:DataCreate a var ...
kaplan-meier survival curve
The AssignmentUsing Week 8 Dataset (SPSS document) from the Learning Resources area, answer the following:DataCreate a variable for Time-to-event by subtracting the start time (variable = start) from the stop time (variable = stop). Label the new variable “Time”.Produce the appropriate descriptive statistics, numerical and graphical, for the following variables:EventIntervalTxNumSizeTimeKaplan-Meier Survival Analysis (Without factor or Strata)Run a Kaplan-Meier analysis in SPSS, using Time as the Time variable and Event as the Status variable (Be sure to define the event). Do not add a factor or strata at this time.Produce a Survival Table (you do not need to submit this)Produce a plot of the survival functionWhat is the mean survival time (include confidence intervals)? What is the median survival time (include confidence intervals)? Why do you think they are so different from each other?Kaplan-Meier Survival Analysis (With Factor)Run a Kaplan-Meier analysis in SPSS, using Time as the Time variable and Event as the Status variable (Be sure to define the event). Add Tx as the factor.Test the difference between Tx groups (Compare Factor) using Log-Rank, Breslow, and Tarone-WareProduce a plot of the survival functionDescribe what the Overall Comparisons mean in terms of treatment groups and survival times.Kaplan-Meier Survival Analysis (With Strata)Run a Kaplan-Meier analysis in SPSS, using Time as the Time variable and Event as the Status variable (Be sure to define the event). Add Interval as the Strata variable.Produce a plot of the survival function for each strata.Why would you want to produce Kaplan-Meier Survival Curves after stratifying for a variable?Resources: Daniel, WW & Cross, CL. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. Hoboken, NJ: Wiley.Chapter 14: Survival Analysis (pp. 750-767
GCU Wk 5 Summary and Descriptive Statistics Measures of Central Tendency Worksheet
Summary and Descriptive Statisticsthere is often the requirement to evaluate descriptive statistics for data within the or ...
GCU Wk 5 Summary and Descriptive Statistics Measures of Central Tendency Worksheet
Summary and Descriptive Statisticsthere is often the requirement to evaluate descriptive statistics for data within the organization or for health care information. Every year the National Cancer Institute collects and publishes data based on patient demographics. Understanding differences between the groups based upon the collected data often informs health care professionals towards research, treatment options, or patient education.Using the data on the "National Cancer Institute Data" Excel spreadsheet, calculate the descriptive statistics indicated below for each of the Race/Ethnicity groups. Refer to your textbook and the Topic Materials, as needed, for assistance in with creating Excel formulas.Provide the following descriptive statistics:Measures of Central Tendency: Mean, Median, and ModeMeasures of Variation: Variance, Standard Deviation, and Range (a formula is not needed for Range).Once the data is calculated, provide a 150-250 word analysis of the descriptive statistics on the spreadsheet. This should include differences and health outcomes between groups.APA style is not required, but solid academic writing is expected.This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
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