Question 1

The income of a company that produces disaster equipment has been expressed as a linear regression model based upon the input variable which is the number of hurricanes projected for the upcoming hurricane season. The model is express as Y = mX + b where Y is the estimated sales in millions of dollars, m = .76 and b = 5. Assuming that the weather service is predicting 6 hurricanes during the season what are the sales in millions of dollars expected to be?

______ million dollars The correct answer is: 9.56

Question 2

True or False: The following data plot represents data that is linearly separable

Select one: * True * False

The correct answer is 'False'.

Question 3

Which of the following functions is used to generate a linear regression model within R?

Select one:

• a. lredict()
• b. lm()
• c. lstat()
• d. glm()

The correct answer is: lm()

Question 4

You have a dataset which produces the following plot and you need to create a predictive model. Which of the following techniques are you most likely to use?

Select one:

• a. Linear Regression
• b. Curvilinear Regression
• c. K-Nearest Neighbors
• d. Logistic Regression

The correct answer is: Linear Regression

Question 5

True or False: Residual plots are a useful tool for identifying non-linearity.

Select one:

• True
• False

The correct answer is 'True'.

Question 6

The names() function within R:

Select one: * a. Lists all of the column names in the data frame provided as an argument to the function. * b. Attaches the names to make the variables in the data frame available by name. * c. Displays the names of the classes identified by the K means clustering algorithm. * d. None of these answers

The correct answer is: Lists all of the column names in the data frame provided as an argument to the function.

Question 7

When data observations are placed into specific groups according to their observed characteristics this is known as: __

Select one:

• a. Classification
• b. Decision Tree Analysis
• c. Clustering
• d. Regression

The correct answer is: Classification

Question 8

True/False: A linear regression model can be used to predict categorical data values.

Select one:

• True
• False

The correct answer is 'False'.

Question 9

When using a relational database engine as the backend for analytics processing, the acronym ______ is used to describe it.

Select one:

• a. MOLAP
• b. ROLAP
• c. OLAP
• d. RDBMS

The correct answer is: ROLAP

Question 10

Which of the following statements will generate a multiple linear regression model within R where the output or predicted variables is Sales and the prediction variables include temperature and unemploymentrate?

Select one:

• a. lm(sales~temperature+unemploymentrate)
• b. lm(temperature+unemploymentrate=sales)
• c. lm(sales+temperature~unemploymentrate)
• d. None of these commands are valid

The correct answer is: lm(sales~temperature+unemploymentrate)

Question 11

The following diagram represents which technique?

Select one:

• a. Linear Regression
• b. Curvilinear Regression
• c. Spline Regression
• d. Polynomial curve fitting

The correct answer is: Curvilinear Regression

Question 12

A linear regression model is expressed as y ≈ β0+ β1x where β0 is the intercept and β1 is the slope of the line). The following equations can be used to compute the value of the coefficients β 0 and β1.

Using the following set of data, find the coefficients β 0 and β1 rounded to the nearest thousandths place and the predicted value of y when x is 10. {(-1 , 0),(0 , 2),(1 , 4),(2 , 5)} What is the value of y.

The correct answer is: 18.9

Question 13

A linear regression model is expressed as y ≈ β0+ β1x where β0 is the intercept and β1 is the slope of the line). The following equations can be used to compute the value of the coefficients β 0 and β1.

Using the following set of data, find the coefficients β 0 and β1 rounded to the nearest thousandths place and the predicted value of y when x is 10. {(-1 , 0),(0 , 2),(1 , 4),(2 , 5)} What is the value of β1.

The correct answer is: 1.7

Question 14

Assume that you had a variety of data including medical history, diet, heredity factors on individuals who developed cancer and you wanted to use this data to determine whether a person is likely to develop cancer. Which technique would be the most promising to start with?

Select one:

• a. Classification
• b. Regression
• c. Clustering
• d. Estimation

The correct answer is: Classification

Question 15

A linear regression model is expressed as y ≈ β0+ β1x where β0 is the intercept and β1 is the slope of the line). The following equations can be used to compute the value of the coefficients β 0 and β1.

Using the following set of data, find the coefficients β 0 and β1rounded to the nearest thousandths place and the predicted value of y when x is 10. {(-1 , 0),(0 , 2),(1 , 4),(2 , 5)} What is the value of β0.

The correct answer is: 1.9