Week 1 Quiz of Predictive Modeling and Analytics

At what stage(s) of Data Exploration would you address missing values in a data set?

Which of the following statements regarding data transformation and data reduction is correct?

What does a data value measure after centering and scaling has been applied?

Why would one want to center and scale a set of data?

For the following three questions, match the Box-Cox Transformation associated with the given value of lambda.

When Lambda = 0, transformation is

When Lambda = 0.5, transformation is

When Lambda = – 1, transformation is

What is the purpose of applying a Data Reduction?

What must be done to variables of a data set before applying principal component analysis and why?

Which of the following can be an appropriate way to deal with missing values? (Select all that apply.)

Your organization asks you to analyze a dataset that shows the number of FreeFly ALTA drones sold in 2016. You noticed that only 2 drones were sold the day after Black Friday, while the average number of drones sold in 2016 is around 100 a day. What is the most probable explanation for this small data value?

What are the risks of replacing a missing value with a guess? (Select all that apply.)

Why removing all data records with missing values is often not a good way to deal with missing values? (Select all that apply.)

The table below shows the number of patients visiting a clinic on ten consecutive business days.

On July 4, 2014, the clinic is closed to observe the Independence Day. We would like to impute a value for patient count on July 4, 2014. Which of the following are reasonable imputed values? ( Select all that apply )

What are the characteristics of an outlier? (Select all that apply.)

A data point is not considered an outlier unless it deviates dramatically on either the x-axis or the y-axis?

Why do outliers exist? (Select all that apply.)

Which statistical measure is more resistant to outliers?

To say a variable is degenerate means which of the following: (Select all that apply.)

Which of the following is a remedy to collinearity issues in regression analysis?

Check all valid observations about the set of box plots below: (Select all that apply.)

Which function on the graph is both linear and displays a positive relationship?

How could this time series graph be improved for data visualization purposes?

Given the table below, how many dummy variables should you create based on the number of categories present?