# Project #95725 - 12 multiple choice questions about predictive analytics

1. The ____ is a measure of dispersion.

 a. mean b. proportion c. range d. mode

2.     Which of the following techniques is used in predictive analytics?

a.   Data dashboards

b.   Linear regression

c.   Data visualization

d.   Optimization models

3._____ provide facts and figures that can be used for analysis and interpretation of a population of interest.

a.    Data

b.    Variables

c.    Range

d.    Query

4.The data on grades (A, B, C, and D) scored by all students in a test is an example of

a.   quantitative data.

b.   sample data.

c.   categorical data.

d.   analytical data.

5.When the data are large and when it is difficult to analyze all at once, which of the following feature in Excel is used to make the data more manageable and to develop insights?

a.   Frequency table

b.   Sorting and filtering

c.   Fill color

d.   Charts

6.  A crosstabulation in Microsoft Excel is known as a

a.    scatter plot.

b.    bar chart.

c.    histogram.

d.    PivotTable.

7.   Which of the following graphs provide information on outliers and IQR of a data set?

a.   Histogram

b.   Line chart

c.   Scatter chart

d.   Box plot

8.The graph of the simple linear regression equation is a(n) _____.

a.     ellipse

b.     hyperbola

c.     parabola

d.     straight line

9.   A researcher is reviewing average household income data and sees that one household reported an annual income of over \$1 million. This value lies outside the normal range of the data and is called a(n) ____.

 a. abnormality b. marginality c. outlier d. quartile

10._____ is the data set used to build the data mining  models.

a.     Range

b.     Codomain

c.     Validation data

d.     Training data

11.One minus the overall error rate is often referred to as the _____ of the model.

a.     sensitivity

b.     accuracy

c.     specificity

d.     cutoff value

12.In the k-nearest neighbors method, when the value of k is set to 1,:

a.     the classification or prediction of a new observation is based solely on the single most similar observation from the training set.

b.     the new observation’s class is naïvely assigned to the most common class in the training set.

c.     the new observation’s prediction is used to estimate the anticipated error rate on future data over the entire training set.

d.     the classification or prediction of a new observation is subject to the smallest possible classification error.

 Subject Computer Due By (Pacific Time) 11/24/2015 11:00 pm
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