Counting Cards Discrete Math probabilities
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A four-of-a-kind is a five-card hand consisting of four cards of one rank, with a fifth of another. How many different four-of-a-kind hands are there?
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A professor states that in the United States the proportion of college students who own iPhones is .66. She then splits th ...
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A professor states that in the United States the proportion of college students who own iPhones is .66. She then splits the class into two groups: Group 1 with students whose last name begins with A-K and Group 2 with students whose last name begins with L-Z. She then asks each group to count how many in that group own iPhones and to calculate the group proportion of iPhone ownership. For Group 1 the proportion is p1 and for Group 2 the proportion is p2. To calculate the proportion you take the number of iPhone owners and divide by the total number of students in the group. You will get a number between 0 and 1.
What would you expect p1 and p2 to be?
Do you expect either of these proportions to be vastly different from the population proportion of .66?
Would you be surprised if p1 was different than p2?
Would you be surprised if they were the same or similar?
What statistical concept describes the relationship between the first letter of someone's last name and whether or not they own an iPhone?
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Most Popular Content
DAT 565 University of Phoenix Sales and Advertisement Expenditure Worksheet
Respond to the following in a minimum of 175 words:Models help us describe and summarize relationships between variables. ...
DAT 565 University of Phoenix Sales and Advertisement Expenditure Worksheet
Respond to the following in a minimum of 175 words:Models help us describe and summarize relationships between variables. Understanding how process variables relate to each other helps businesses predict and improve performance. For example, a marketing manager might be interested in modeling the relationship between advertisement expenditures and sales revenues.Consider the dataset below and respond to the questions that follow:Advertisement ($'000) Sales ($'000)1068 44891026 5611767 3290885 41131156 48831146 5425892 4414938 5506769 3346677 36731184 65421009 5088Construct a scatter plot with this data.Do you observe a relationship between both variables?Use Excel to fit a linear regression line to the data. What is the fitted regression model? What is the slope? What does the slope tell us?Is the slope significant?What is the intercept? Is it meaningful?What is the value of the regression coefficient,r? What is the value of the coefficient of determination, r^2? What does r^2 tell us?Use the model to predict sales and the business spends $950,000 in advertisement. Does the model underestimate or overestimates ales?
MATH 211 WCU Number of Death on Weekends Are Higher than Weekdays Discussion
Minimum 250 WordsSimple discussion post for stats class1 SourceTopic: Multiple studies conducted in the United States, Can ...
MATH 211 WCU Number of Death on Weekends Are Higher than Weekdays Discussion
Minimum 250 WordsSimple discussion post for stats class1 SourceTopic: Multiple studies conducted in the United States, Canada, Germany, and the United Kingdom show that the probability of dying in the hospital is higher if you are admitted on the weekend. Why might this be? What factors might contribute to this probability? What could hospitals do to reduce/eliminate this phenomenon?
1-1 Discussion: Applications of Probability
A professor states that in the United States the proportion of college students who own iPhones is .66. She then splits th ...
1-1 Discussion: Applications of Probability
A professor states that in the United States the proportion of college students who own iPhones is .66. She then splits the class into two groups: Group 1 with students whose last name begins with A-K and Group 2 with students whose last name begins with L-Z. She then asks each group to count how many in that group own iPhones and to calculate the group proportion of iPhone ownership. For Group 1 the proportion is p1 and for Group 2 the proportion is p2. To calculate the proportion you take the number of iPhone owners and divide by the total number of students in the group. You will get a number between 0 and 1.
What would you expect p1 and p2 to be?
Do you expect either of these proportions to be vastly different from the population proportion of .66?
Would you be surprised if p1 was different than p2?
Would you be surprised if they were the same or similar?
What statistical concept describes the relationship between the first letter of someone's last name and whether or not they own an iPhone?
5 pages
One Way Anova
The research question of interest was with regards to whether there is a significant difference in the infrastructure inde ...
One Way Anova
The research question of interest was with regards to whether there is a significant difference in the infrastructure index among various regions of ...
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.
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