Business analytics final exam review

Consider the following time series. Calculate an Exponential forecast for October. The forecast for September was 120 and the smoothing coefficient is 0.2. Write your answer in the box to the nearest integer. Month Actual Jan 140 Feb 139 Mar 140 Apr 138 May 100 Jun 102 Jul 130 Aug 160 Sep 140

124

Consider the following time series. Calculate a three-period moving average forecast for October. Write your answer in the box to the nearest integer. Month Actual Jan 140 Feb 139 Mar 140 Apr 138 May 100 Jun 102 Jul 130 Aug 160 Sep 140

143

For a particular maximization problem, the payoff for the best decision alternative is $15.7 million while the payoff for one of the other alternatives is $12.9 million. The regret associated with the alternate decision would be _____. $15.7 million $2.8 million $0.129 million $28.6 million

2.8 millions

Brett wants to sell throw blankets for the holiday season at a local flea market. Brett purchases the throws for $15 and sells them to his customers for $35. The rental space is fixed fee of $1,500 for the season. Assume there is no leftover value for unsold units. If he orders 200 and demand is 150, what is the payoff? $50 $2,800 $750 $800

750

As we increase the cutoff value, _____ error will decrease and _____ error will rise. Class 1, Class 0 None of these are correct. false, true Class 0, Class 1

Class 0, Class 1

Classifying a record as belonging to one class when it belongs to another class is referred to as a(n) _____. error class overall error rate accuracy

Error

_____ refers to the scenario in which the analyst builds a model that does a great job of explaining the sample of data on which it is based but fails to accurately predict outside the sample data. Underfitting Oversampling Undersampling Overfitting

Overfitting

Estimation methods are also referred to as _____. association methods supervised methods clustering methods prediction methods

Prediction methods

Which algorithm, developed by George Dantzig and utilized by Excel Solver, is effective at investigating extreme points in an intelligent way to find the optimal solution to even very large linear programs? Trial-and-error algorithm Ellipsoidal algorithm Simplex algorithm Complex algorithm

Simplex algorithm

A time series plot of a period of time (in years) versus sales (in thousands of dollars) is shown below. Which of the following data patterns best describes the scenario shown? a. Linear trend pattern b. Nonlinear trend pattern c. Seasonal pattern d. Cyclical pattern

a. linear trend pattern

A(n) _____ is often displayed as a row of values in a spreadsheet or database in which the columns correspond to the variables. a. record b. classification c. data point d. location

a. record

Separate error rates with respect to the false negative and false positive cases are computed to take into account the _____. symmetric weights of these two cases effect of sampling error distortions due to outliers asymmetric costs in misclassification

asymmetric costs in misclassification

Which of the following is not present in a time series? a. Seasonality b. Operational variations c. Trend d. Cycles

b. operational variations

A characteristic or quantity of interest that can take on different values is a(n) _____. a. quality b. variable c. record d. observation

b. variable

A _____ refers to a constraint that can be expressed as an equality at the optimal solution. nonnegativity constraint slack variable binding constraint first class constraint

binding contraint

With reference to exponential forecasting models, a parameter that provides the weight given to the most recent time series value in the calculation of the forecast value is known as the _____. a. moving average b. regression coefficient c. smoothing constant d. mean forecast error

c. smoothing constant

An uncertain future event affecting the consequence associated with a decision is known as a _____. payoff chance event decision node decision alternative

chance event

The states of nature are defined so that they are _____. This means that at least one state of nature must occur at a given time for a chance event. mutually exclusive optimistic outcomes collectively exhaustive certain events

collectively exhaustive

A(n) _____ matrix displays a model's correct and incorrect classification. confusion ROC curve decile-wise lift chart cumulative lift

confusion

Choosing a decision alternative that maximizes the minimum profit is a feature of the _____ approach. conservative maximin regret optimistic expected value

conservative

Rob is a financial manager with Sharez, an investment advisory company. He must select specific investments—for example, stocks and bonds—from a variety of investment alternatives. Restrictions on the type of permissible investments would be a _____ in this case. slack variable constraint feasible solution surplus variable

constraint

_____ compares the number of actual Class 1 observations identified if considered in decreasing order of their estimated probability if randomly classified. Confusion Decile-wise lift chart Cumulative lift ROC curve

cumulative lift

Suppose for a particular week, the forecasted sales were $4,000. The actual sales were $3,000. What is the value of the mean absolute percentage error? a. -33.3% b. -25% c. 25% d. 33.3%

d. 33.3%

The exponential smoothing forecast for period t + 1 is a weighted average of the _____. a. forecast value in period t with weight α and the actual value for period t with weight 1 - α b. actual value in period t + 1 with weight α and the forecast for period t with weight 1 - α c.forecast value in period t - 1 with weight α and the forecast for period t with weight 1 - α d. actual value in period t with weight α and the forecast for period t with weight 1 - α

d. actual value in period t with weight α and the forecast for period t with weight 1 - α

The set of recorded values of variables associated with a single entity is a(n) _____. a. classification b. data point c. location d. observation

d. observation

A time series that shows a recurring pattern over one year or less is said to follow a _____. a. horizontal pattern b. stationary pattern c. cyclical pattern d. seasonal pattern

d. seasonal pattern

Which of the following states the objective of time series analysis? a. To predict the values of a time series based on one or more other variables b. To analyze the cause-and-effect relationship of a dependent variable with a time series and one or more other variables c. To use present variable values to study what should have been the ideal past values d. To uncover a pattern in a time series and then extrapolate the pattern into the future

d. to uncover a pattern in a time series and then extrapolate the pattern into the future.

_____ is the manipulation of the data with the goal of putting it in a form suitable for formal modeling. Data sampling Data partitioning Data preparation Model assessment

data preparation

_____ are graphical representations of the decision problems that show the sequential nature of the decision-making process. Utility functions Decision trees Influence diagrams Payoff tables

decisions trees

The weighted average of the payoffs for a chance node is known as the _____. variance of the node expected value risk measure median value

expected value

The points where constraints intersect on the boundary of the feasible region are termed as the _____. extreme points objective function contour feasible edges feasible points

extreme points

An observation classified as part of a group with a characteristic when it actually does not have the characteristic is termed as a(n) _____. false negative false positive residual outlier

false positive

A(n) _____ solution satisfies all the constraint expressions simultaneously. infeasible feasible extreme objective

feasible

_____ is a measure of the heterogeneity of observations in a classification tree. Accuracy Specificity Impurity Sensitivity

impurity

_____ is the situation in which no solution to the linear programming problem satisfies all the constraints. Unboundedness Infeasibility Divisibility Optimality

infeasibility

_____ is a generalization of linear regression for predicting a categorical outcome variable. Multiple linear regression Logistic regression Cluster analysis Discriminant analysis

logistic regression

For a maximization problem, the optimistic approach often is referred to as the _____ approach. maximax maximin minimin minimax

maximax

Rob is a financial manager with Sharez, an investment advisory company. He must select specific investments—for example, stocks and bonds—from a variety of investment alternatives. Which of the following statements is most likely to be the objective function in this scenario? Minimization of tax dues Minimization of the number of stocks held Maximization of investment risk Maximization of expected return

maximization of expected return

For a minimization problem, the optimistic approach often is referred to as the _____ approach. minimin minimax maximin maximax

minimim

A canned food manufacturer has its manufacturing plants in three locations across a state. Their product has to be transported to 3 central distribution centers, which in turn disperse the goods to 72 stores across the state. Which of the following is most likely to be the objective function in this scenario? Minimizing the quantity of goods distributed across the stores Increasing the number of goods manufactured at the plant Minimizing the cost of shipping goods from the plant to the store Decreasing the cost of their raw material sourcing

minimizing the cost of shipping goods from the plant to the store

The term _____ refers to the expression that defines the quantity to be maximized or minimized in a linear programming model. decision variable association rule objective function problem formulation

objective function

In problem formulation, the _____. constraints are expressed in terms of the obtained objective function coefficients. objective is expressed in terms of the decision variables. nonnegativity constraints are always ignored. optimal solution is decided upon.

objective is expressed in terms of the decision variables

The amount of loss (lower profit or higher cost) from not making the best decision for each state of nature is known as _____. opportunity loss best payoff risk profile utility

opportunity loss

The _____ approach evaluates each decision alternative in terms of the best payoff that can occur. maximin regret conservative optimistic expected value

optimistic

The percent of misclassified records out of the total records in the validation data is known as the _____. class accuracy overall error rate error

overall error rate

_____, or modeling, is the process of translating a verbal statement of a problem into a mathematical statement. Data preparation Data structuring Problem formulation Problem-solving approach

problem formulation

The _____ assumption necessary for a linear programming model to be appropriate means that the contribution to the objective function and the amount of resources used in each constraint are in accordance to the value of each decision variable. divisibility additivity negativity proportionality

proportionality

_____ is the study of the possible payoffs and probabilities associated with a decision alternative or a decision strategy in the face of uncertainty. Cost analysis Certainty analysis Risk analysis Optimization

risk analysis

The study of how changes in the probability assessments for the states of nature or changes in the payoffs affect the recommended decision alternative is known as _____. probability analysis sensitivity analysis cost analysis uncertainty analysis

sensitivity analysis

The change in the optimal objective function value per unit increase in the right-hand side of a constraint is given by the _____. objective function coefficient allowable increase shadow price restrictive cost

shadow price

The _____ value for each less-than-or-equal-to constraint indicates the difference between the left-hand and right-hand values for a constraint. objective function coefficient surplus unbounded slack

slack

Data mining methods for classifying or estimating an outcome based on a set of input variables is referred to as _____. data sampling dimension reduction supervised learning unsupervised learning

supervised learning

_____ is a category of data mining techniques in which an algorithm learns how to classify or estimate an outcome variable of interest. Dimension reduction Supervised learning Unsupervised learning Data sampling

supervised learning

Data used to build a data mining model is called _____. exploration data test data validation data training data

test data

Nonnegativity constraints ensure that _____. the objective function of the problem always returns maximum quantities the problem modeling includes only nonnegative values in the constraints the solution to the problem will contain only nonnegative values for the decision variables there are no inequalities in the constraints

the solution to the problem will contain only nonnegative values for the decision variables

A set of observations on a variable measured at successive points in time or over successive periods of time constitute a _____. geometric series time invariant set time series logarithmic series

time series

The situation in which the value of the solution may be made infinitely large in a maximization linear programming problem or infinitely small in a minimization problem without violating any of the constraints is known as _____. infiniteness semi-optimality unbounded infeasibility

unbounded