All questions

Why do we cluster the basketball data with 3 clusters after we analyze it with 2 clusters?

What does the Akaike Information Criterion (AIC) do?
Select all that apply

Which standard delimiters can Excel identify to split text into multiple columns?

What is heteroscedasticity?

Where can you download the Excel Solver from?

What is one of the most effective methods for tuning an algorithm?

Which of the below statements are TRUE about n-fold cross validation?

What happened to the AUC when we ran a boosted random forest model after the initial random forest model?

Which of these is not an assumption of time series analysis?

Which of these statements is true?

Why do we see mostly zeroes in the term-document matrix that we created from the NYT articles?

1. In order to create interactive data visualizations, we will use:

1. Fill in the blank.

1. Fill in the blank below.

2. Identify the three things necessary to make a graph in ggplot2.
Select all that apply

1. Which function tells Shiny to visualize a graph?

1. Which two variables showed the strongest correlations with two clusters?
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1. Why might it be more challenging to do a sentiment analysis on communications between Millenials?

1. When using data you may encounter any of the challenges listed below. Match each challenge with its description.

2. How does density affect a network?
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2. Betweenness tells you which nodes can be
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1. Which questions would seasonality analysis help answer?
Select all that apply

1. What is true about this directed network image?

Select all that apply

1. Which two functions do you need to save your image output as a PDF?
Select all that apply

2. Identify the three things necessary to make a graph in ggplot2.

2. Fill in the blank below.

2. Which function do we use for each tab in our app?

2. Why do we cluster the basketball data with 3 clusters after we analyze it with 2 clusters?

3. Based on this word cloud, generated from hotel reviews, order the words by frequency. Put the most frequently used words at the top.

3. What is Big Data?
Select all that apply

2. What happened when Target predicted pregnancy in their customers?

3. When building a forecasting model, it is better to have more variables in the model.

How often is this statement true?

2. Which function can you use in the igraph package to eliminate duplicate data?

2. Match the functions to the actions they perform in R.

3. What is heteroscedasticity?

3. What is TRUE about adding more variables to your regression model?
Select all that apply

2. Put the steps for calculating undirected eigenvectors in the correct order.

2. What is an example of how the direction of trust does not always go both ways?

2. Why does it make sense to save a graph to PDF format?
Select all that apply

3. Fill in the blank below.

3. Why do we use packages for data manipulation instead of just using built-in R functions?
Select all that apply

3. Why might bar graphs be misleading?

4. Which Shiny functions integrate Leaflet so it can be displayed as an application?
Select all that apply

3. Why is clustering more powerful than visualizing?
Select all that apply

4. Order these data formats from most to least structured.

4. Sort the network from the broadest community to the most niche community.

5. Identify whether the activity would need a data science team member with a low level or high level of expertise.

3. Which of the following are ethical questions you may face when using data?
Select all that apply

4. Which of the below were top indicators for Target that a customer was pregnant?
Select all that apply

4. Label each aspect of the graph.

4. Fill in the blanks.

4. Put the 5 similar functions of an organization in the correct order.

4. Sort the variables as either continuous or discrete.

5. Match the methods below to their respective purpose.

5. Fill in the blank below.

4. Match the arguments to what they do.

4. What does Louvain Modularity assume?

5. The aes layer contains:

5. What aspects of a graph should you keep in mind while creating it?
Select all that apply

What did you think of the material in this section?

5. What does missing data prevent?

5. What are some important things to remember when working with outliers in your data?
Select all that apply

5. What is TRUE about followers in a directed network?
Select all that apply

5. What is a takeaway we learned from analyzing Congressional donation data?

5. Which function eliminates duplicate rows?

Fill in the blanks below.

Given the table above, what SQL function would you use to perform the following tasks?

Match the models to the correlation they are displaying.

How was Target able to identify their pregnant customers?

Which of the following SQL functions can be used on date fields?
Select all that apply

Which operator pulls rows that contain specified terms you’re searching for to create a new dataset with only those rows?

Fill in the blank below.

Fill in the blank below.

How do we know we still need to refine our model further?

What result would we get if we used the formula RIGHT(G2, 3)?

What result would we get if we used the formula RIGHT(G2, 3)?

Match the terms to the descriptions.

Match each data quality with its description.

In which scenario below would we want to minimize the false negatives of our model?
Please select all that apply

What are some of the fields that text mining methods employ?
Please select all that apply

How does clustering help when there are more than 3 attributes in the data?

Please fill in the blanks below:

5. Which of these is an example of exploratory data analysis?

Which piece of code will retrieve only the third column of a matrix called 'm'?

What types of data are difficult to cluster?
Select all that apply

Which questions can datafication help us answer
Select all that apply

Which function converts wide data to long data?

Which of these is an example of exploratory data analysis?

How can we address the limitations of our analysis to see the data differently?
Select all that apply

What is heteroscedasticity?

Which function would I use to change transform the text below to all capital letters?

 coUpE --> COUPE

What is R Squared?

What is the objective of solving an optimization problem?

What type of data analysis gives you an overview of your data quickly by visualizing it?

Which R function makes sure that we can reproduce the exact same results when we use the createFolds() function?

What is the output of the formula below?

What is a moving average?

Why do we use the silhouette coefficient to determine the number of clusters for sk-means?

Why is it important to convert all words to lower case before removing 'stop words'?

1. Fill in the blank below.

1. Fill in the blank below.

1. Fill in the blank below.

1. Why does R put an 'X' in front of numerical column names?
Select all that apply

1. Fill in the blank below.

1. Why did NAs appear when we initially read in the data?

Based on this comparison cloud, order the customer comments according to those that are most consistently complimentary (at the top) and those most negative and pervasive(at the bottom).

1. What can we conclude about the statistic that there are 88 guns for every 100 Americans?

1. Which of the following sources would need to be datafied or converted into numbers, so that you can run analyses and gain greater insight?
Select all that apply

1. Which function should I use if I want to make sure my results are reproducible?

1. Fill in the blanks below.

1. What does the ".SD" notation stand for?

1. Fill in the blank below.

2. Drag the term to the box next to the correct description.

3. Which function generates a vector of numbers with a specified range that can count by another number?

2. Which package can we use to scrape websites for information?

3. What are some conclusions we see when we graph points per game by minutes per game with three clusters?
Select all that apply

3. When summarizing a long document via text analysis, the most "important" words will be determined by:

2. Which aspect of Big Data is highlighted in these examples?

-Location data from mobile phones can infer how many people were in Macy’s on Black Friday, estimating sales before Macy's aggregates the numbers.
-Amazon's product catalogue receives more than 50 million updates a week, and deliveries and inventories are tracked in real time.

3. Naïve Bayes is probabilistic classification method commonly used for text classification. Most spam filters are based on a variant of Naïve Bayes.

Order the steps that a spam filter takes when deciding whether or not a new email should be placed in the spam folder. Place the first step at the top.

2. Order the steps needed to build a multivariate regression model.

3. Use the edge.attr.comb argument to

3. Match the output elements shown in the console below to what information they are providing.

2. What does the Akaike Information Criterion (AIC) do?
Select all that apply

3. Put the steps of the data science control cycle in the correct order.

3. What is TRUE about an identity matrix?
Select all that apply

2. Fill in the blank below.

3. Please fill in the blanks below:

3. Match the function to its purpose.

4. Fill in the blank below.

4. Visualization is an iterative process. Put the steps in order starting with "Analyze"

4. What is the output of this R code?

 "matrix"[,c(1:4)] 

4. In order for us to determine how much variation our clusters account for, we need to:
Select all that apply

3. Which of the following are epistemological challenges?

5. Networks can contain a wealth of information. Which of the following questions are best be answered by measuring an aspect of the network (assuming the necessary data are available).

4. Data analysis can provide:
Select all that apply

5. Fill in the missing words.

4. Which assumption does Naïve Bayes make about its attributes?

5. If most of the data points cluster around a regression line, it may be the case that:

3. Which function would you use to pull the longitude and latitude figures from Google?

5. Match the questions with the correct step in the Data Science Control Cycle.

5. How do we know we still need to refine our model further?

4. Put the steps of time series data methodology in correct order.

4. What is TRUE about top observers or collectors of information in a network?
Select all that apply

4. Put the steps of the Data Science Control Cycle in order.

4. Which method allows us to build a recommendation engine?

3. Why is it important to understand different data types?
Select all that apply

5. Why do we build visualizations?
Select all that apply

5. When Hewlett Packard started tracking a range of employee factors, what were the results?

5. You are creating a feedback survey to send your customers. You already know their zip code, education level, and age. Which additional survey item captures a different type of information and may add explanatory power to your model?

5. What is R Squared?

5. What is important to keep in mind when calculating eigenvector centrality in R?
Select all that apply

5. What is a limitation of calculating edge betweenness in large networks?

5. Why do we build visualizations?

Fill in the blank below.

Table: Company_Employees

Which SQL code will result in a frequency distribution of the Company field?

How do you measure the explanatory power of your predictive model?

Put the four steps of building a classification tree in order.

Put the following SQL clauses in the correct standard query template order:

Put the six Data Science control cycle steps in order, starting with “Ask”

Identify the three things necessary to make a graph in ggplot2.
Select all that apply