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Business Analytics Final
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Terms in this set (89)
. ______ encompasses reports, data dashboards, and descriptive statistics to describe the past data.
a. Predictive analytics
b. Descriptive analytics
c. Prescriptive analytics
d. Decision analysis
b descriptive
_____ helps in constructing a mathematical model to predict the future sales, based on past data.
a. Predictive analytics
b. Decision analysis
c. Prescriptive analytics
d. Descriptive analytics
a. Predictive analytics
Which of the following techniques is used in predictive analytics?
a. Data dashboards
b. Linear regression
c. Data visualization
d. Optimization models
b. Linear regression
A children's apparel manufacturer used descriptive analytics:
a. to present supply chain to managers visually.
b. to achieve efficiency in delivery of goods.
c. to schedule staff and vehicle for delivery.
d. to plan capacity utilization by incorporating the inherent uncertainty in commodities pricing.
a. to present supply chain to managers visually.
A variable is defined as a
a. quantity of interest that can take on same values.
b. set of values.
c. quantity of interest that can take on different values.
2
d. characteristic that takes on same values from a set of values.
c. quantity of interest that can take on different values.
A variable whose values are not known with certainty is called a _____.
a. certain variable
b. random variable
c. constant variable
d. decision variable
b. random variable
. _____ act(s) as a representative of the population.
a. The analytics
b. The variance
c. A sample
d. The random variables
c. A sample
The act of collecting data that are representative of the population data is called
a. random sampling.
b. sample data.
c. population sampling.
d. applications of business analytics.
a. random sampling.
. 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.
c. categorical data.
The data on the time taken by 10 students in a class to answer a test is an example of
a. population data.
b. categorical data.
c. time series data.
d. quantitative data.
d. quantitative data.
. _____ are collected from several entities at the same point in time.
a. Time series data
b. Categorical and quantitative data
c. Cross-sectional data
d. Random data
c. Cross-sectional data
Data collected from several entities over several time periods is
a. categorical and quantitative data.
b. time series data.
c. source data.
d. cross-sectional data.
b. time series data.
. A summary of data that shows the number of observations in each of several nonoverlapping bins is
called
a. a frequency distribution.
b. a sample summary.
c. a bin distribution.
d. an observed distribution.
a. a frequency distribution.
Compute the relative frequencies for the data given in the table below:
Grades
Number of
students
A 16
B 28
C 33
D 13
Total 90
a. 0.31, 0.14, 0.37, 0.18
b. 0.37, 0.14, 0.31, 0.18
c. 0.14, 0.31, 0.37, 0.18
d. 0.18, 0.31, 0.37, 0.14
d. 0.18, 0.31, 0.37, 0.14
Which of the following are necessary to be determined to define the classes for a frequency distribution
with quantitative data?
a. Number of nonoverlapping bins, width of each bin, and bin limits
b. Width of each bin and bin lower limits
c. Number of overlapping bins, width of each bin, and bin upper limits
d. Width of each bin and number of bins
a. Number of nonoverlapping bins, width of each bin, and bin limits
The _____ shows the number of data items with values less than or equal to the upper class limit of each
class.
a. cumulative frequency distribution
b. frequency distribution
c. percent frequency distribution
d. relative frequency distribution
a. cumulative frequency distribution
The simplest measure of variability is the
a. variance.
b. standard deviation.
c. coefficient of variation.
d. range.
d. range.
The variance is based on the
a. deviation about the median.
b. number of variables.
c. deviation about the mean.
d. correlation in the data.
c. deviation about the mean.
A _____ determines how far a particular value is from the mean relative to the data set's standard
deviation.
a. coefficient of variation
b. z-score
c. variance
d. percentile
b. z-score
Any data value with a z-score less than -3 or greater than +3 is treated as a(n)
a. outlier.
b. usual value.
c. whisker.
d. z-score value.
a. outlier.
. The correlation coefficient will always take values
a. greater than 0.
b. between -1 and 0.
c. between -1 and +1.
d. less than -1.
c. between -1 and +1.
Data-ink is the ink used in a table or chart that
a. does not help in conveying the data to the audience.
b. helps in presenting data when the audience need not know exact values.
c. is necessary to convey the meaning of the data to the audience.
d. increases the Non-data-ink ratio.
c. is necessary to convey the meaning of the data to the audience.
Tables should be used when
a. the reader need not refer to specific numerical values.
b. the reader need not make precise comparisons between different values and not just relative
comparisons.
c. the values being displayed have different units or very different magnitudes.
d. the reader need not differentiate the columns and rows.
c. the values being displayed have different units or very different magnitudes.
A useful type of table for describing data of two variables is a
a. data table.
b. bubble chart.
c. crosstabulation.
d. scatter chart.
c. crosstabulation.
A _____ is a graphical presentation of the relationship between two quantitative variables.
a. histogram
b. bar chart
c. pie chart
d. scatter chart
d. scatter chart
A _____ is a line that provides an approximation of the relationship between the variables.
a. line chart
b. sparkline
c. trendline
d. gridline
c. trendline
If the scatter chart indicates a positive linear relationship between two variables, then their correlation
coefficient is
a. equal to -1.
b. greater than 1.
c. between 0 and +1.
d. between -1 and 0.
c. between 0 and +1.
A line chart displaying the data values collected over a period of time is termed as a
a. boxplot.
b. frequency graph.
c. dot plot
d. time series plot.
d. time series plot.
In order to visualize three variables in two-dimensional graph, we use a
a. 2-D chart.
b. 3-D chart.
c. bubble chart.
d. column chart.
c. bubble chart.
A two-dimensional graph representing the data using different shades of color to indicate magnitude is
called a ______.
a. heat map
b. bubble chart
c. column chart
d. pie chart
a. heat map
. Consider the clustered bar chart of the dashboard developed to monitor the performance of a call center:
This chart allows the IT manager to
a. identify a particular type of problem by the call volume.
b. identify a particular type of problem by location.
c. identify different types of problems (Email, Internet, or Software) in the call center.
d. identify the frequency of each problem in the call center.
b. identify a particular type of problem by location.
Which of the following propositions describes an existing theory or belief?
a. standard deviation
b. null hypothesis
c. proportion
d. alternative hypothesis
b. null hypothesis
Which of the following is a valid one-sample hypothesis test?
a. H0: population parameter ≠ constant vs. H1: population parameter = constant
b. H0: population parameter > constant vs. H1: population parameter ≤ constant
c. H0: population parameter < constant vs. H1: population parameter ≥ constant
d. H0: population parameter = constant vs. H1: population parameter ≠ constant
d. H0: population parameter = constant vs. H1: population parameter ≠ constant
A manufacturer wishes to determine if the average profit from the sale of his product exceeds $6,710.
Which of the following is the appropriate hypothesis test?
a. H0: population mean profit from sale > $6,710 vs. H1: population mean profit from sale ≤
$6,710
b. H0: population mean profit from sale ≤ $6,710 vs. H1: population mean profit from sale >
$6,710
c. H0: population mean profit from sale < $6,710 vs. H1: population mean profit from sale ≥
$6,710
d. H0: population mean profit from sale ≥ $6,710 vs. H1: population mean profit from sale <
$6,710
b. H0: population mean profit from sale ≤ $6,710 vs. H1: population mean profit from sale >
Which of the following is true about determining the proper form of the hypotheses?
a. H0 is statistically proved true while testing
b. failure to reject H0 proves H1 wrong
c. H0 is always assumed to be true in testing
d. H1 is always assumed to be true in testing
c. H0 is always assumed to be true in testing
Which of the following is a Type I error?
a. the null hypothesis is actually true, and the hypothesis test correctly fails to reject it
b. the null hypothesis is actually false, but the test incorrectly fails to reject it
c. the null hypothesis is actually false, and the test correctly rejects it
d. the null hypothesis is actually true, but the hypothesis test incorrectly rejects it
d. the null hypothesis is actually true, but the hypothesis test incorrectly rejects it
Robin Inc. feared that the average company loss is running beyond $34,000. It initially conducted a
hypothesis test on a sample extracted from its database. The hypothesis was formulated as H0: average
company loss $34,000 vs. H1: average company loss > $34,000. The test resulted in favor of Robin Inc.'s
loss not exceeding $34,000. Detailed study of company accounts later revealed that the average company
loss had run up to $37,896. Which of the following errors were made during the hypothesis test?
a. Type III error
b. Type II error
c. Type I error
d. Type IV error
b. Type II error
Type II error occurs when the test:
a. correctly fails to reject an actually true null hypothesis.
b. incorrectly fails to reject an actually false null hypothesis.
c. correctly rejects an actually false null hypothesis.
d. incorrectly rejects an actually true null hypothesis.
b. incorrectly fails to reject an actually false null hypothesis.
What is the confidence coefficient when the level of significance is 0.03?
a. 0.9700
b. 0.0376
c. 0.7924
d. 0.7776
a. 0.9700
. For a one-tailed test, the critical value:
a. divides the sampling distribution into three parts.
b. is the number of standard errors away from the sample mean.
c. helps determine if the test statistic falls in the rejection region or not.
d. fails to reject the null hypothesis if the test statistic exceeds the critical value.
c. helps determine if the test statistic falls in the rejection region or not.
For a two-sample hypothesis test for differences in population parameters (1) and (2), which of the
following is the correct form of an upper-tailed test?
a. H0: population parameter (1) - population parameter (2) ≥ 0 vs. H1: population parameter (1)
- population parameter (2) < 0
b. H0: population parameter (1) - population parameter (2) > 0 vs. H1: population parameter (1)
- population parameter (2) ≤ 0
c. H0: population parameter (1) - population parameter (2) < 0 vs. H1: population parameter (1)
- population parameter (2) > 0
d. H0: population parameter (1) - population parameter (2) ≤ 0 vs. H1: population parameter (1)
- population parameter (2) > 0
d. H0: population parameter (1) - population parameter (2) ≤ 0 vs. H1: population parameter (1)
- population parameter (2) > 0
A regression analysis involving one independent variable and one dependent variable is referred to as a
_____.
a. factor analysis
b. time series analysis
c. simple regression
d. data mining
c. simple regression
A linear regression analysis for which any one unit change in the independent variable is assumed to:
a. have the same change in the dependent variable.
b. have no change in the dependent variable.
c. have an inverse effect on the dependent variable
d. have a nullifying effect on the dependent variable.
a. have the same change in the dependent variable.
In the graph of the simple linear regression equation, the parameter β1 is the _____ of the regression line.
a. slope
b. x-intercept
c. y-intercept
d. end-point
a. slope
When the mean value of the dependent variable is independent of variation in the independent variable,
the slope of the regression line is _____.
a. positive
b. zero
c. negative
d. infinite
b. zero
The procedure of using sample data to find the estimated regression equation is better known as _____.
a. point estimation
b. interval estimation
c. the least squares method
d. extrapolation
c. the least squares method
Prediction of the value of the dependent variable outside the experimental region is called _____.
a. interpolation
b. forecasting
c. averaging
d. extrapolation
d. extrapolation
What would be the value of the sum of squares due to regression (SSR) if the total sum of squares (SST)
is 25.32 and the sum of squares due to error (SSE) is 6.89?
a. 31.89
b. 19.32
c. 18.43
d. 15.32
c. 18.43
The coefficient of determination:
a. takes values between -1 to +1.
b. is equal to zero for a perfect fit.
c. is equal to one for the poorest fit.
d. is used to evaluate the goodness of fit.
d. is used to evaluate the goodness of fit.
What would be the coefficient of determination if the total sum of squares (SST) is 23.29 and the sum of
squares due to regression (SSR) is 10.03?
a. 2.32
b. 0.43
c. 13.26
d. 0.89
b. 0.43
Which of the following inferences can be drawn from the scatter chart given below?
a. The residuals have a varying variance.
b. The model captures the relationship between the variables accurately.
c. The regression model follows the F probability distribution.
d. The residual distribution is consistently scattered about zero.
a. The residuals have a varying variance.
The following scatter chart would help conclude that:
12
a. the residuals have a constant variance.
b. the model fails to capture the relationship between the variables accurately.
c. the model underpredicts the value of the dependent variable for intermediate values of the
independent variable.
d. the residual is normally distributed.
b. the model fails to capture the relationship between the variables accurately.
. Which of the following inferences can be drawn from the scatter chart given below?
a. The residuals have a constant variance.
b. The model captures the relationship between the variables accurately.
c. The model underpredicts the value of the dependent variable for intermediate values of the
independent variable.
d. The residual distribution is not normally distributed.
d. The residual distribution is not normally distributed.
_____ is used to test the hypothesis that the values of the regression parameters β1, β2, . . . , βq are all zero.
a. An F test
b. A t test
13
c. The least squares method
d. Extrapolation
a. An F test
forecast is defined as a(n):
a. prediction of future values of a time series.
b. quantitative method used when historical data on the variable of interest are either unavailable or not
applicable.
c. set of observations on a variable measured at successive points in time.
d. outcome of a random experiment.
a. prediction of future values of a time series.
A set of observations on a variable measured at successive points in time or over successive periods of
a. geometric series
b. time invariant set
c. time series
d. logarithmic series
c. time series
A _____ pattern exists when the data fluctuate randomly around a constant mean over time.
a. vertical
b. seasonal
c. cyclical
d. horizontal
d. horizontal
. Trend refers to:
a. the long-run shift or movement in the time series observable over several periods of time.
b. the outcome of a random experiment.
c. the recurring patterns observed over successive periods of time.
d. the short-run shift or movement in the time series observable at some specific period of time.
a. the long-run shift or movement in the time series observable over several periods of time.
Which of the following data patterns best describes the scenario shown in the below plot?
14
a. Time series with a linear trend pattern
b. Time series with a nonlinear trend pattern
c. Time series with no pattern
d. Time series with a horizontal pattern
d. Time series with a horizontal pattern
Which of the following data patterns best describes the scenario shown in the given time series plot?
a. Linear trend pattern
b. Nonlinear trend pattern
c. Seasonal pattern
d. Cyclical pattern
a. Linear trend pattern
Which of the following data patterns best describes the scenario shown in the given time series plot?
15
a. Linear trend pattern
b. Logarithmic trend
c. Exponential trend
d. Seasonal pattern
d. Seasonal pattern
Which of the following data patterns best describes the scenario shown in the given time series plot?
a. Linear trend and cyclical pattern
b. Linear trend and horizontal pattern
c. Seasonal and cyclical patterns
d. Seasonal pattern and linear trend
d. Seasonal pattern and linear trend
_____ is the amount by which the predicted value differs from the observed value of the time series
variable.
a. Mean forecast error
b. Mean absolute error
c. Smoothing constant
d. Forecast error
d. Forecast error
If the forecasted value of the time series variable for period 2 is 22.5 and the actual value observed for
period 2 is 25, what is the forecast error in period 2?
a. 3
b. 2
c. 2.5
d. -2.5
c. 2.5
The moving averages and exponential smoothing methods are appropriate for a time series exhibiting
_____.
a. horizontal pattern
b. cyclical pattern
c. trends
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d. seasonal effects
a. horizontal pattern
_____ uses a weighted average of past time series values as the forecast.
a. The qualitative method
b. Exponential smoothing
c. Correlation analysis
d. The causal model
b. Exponential smoothing
Autoregressive models:
a. use the average of the most recent data values in the time series as the forecast for the next period.
b. are used to smooth out random fluctuations in time series.
c. relate a time series to other variables that are believed to explain or cause its behavior.
d. occur whenever all the independent variables are previous values of the same time series.
d. occur whenever all the independent variables are previous values of the same time series.
The term _____ refers to the expression that defines the quantity to be maximized or minimized in a
linear programming model.
a. objective function
b. problem formulation
c. decision variable
a. objective function
Constraints are:
a. quantities to be maximized in a linear programming model.
b. quantities to be minimized in a linear programming model.
c. restrictions that limit the settings of the decision variables.
d. input variables that can be controlled during optimization.
c. restrictions that limit the settings of the decision variables.
A controllable input for a linear programming model is known as a _____.
a. parameter
b. decision variable
c. dummy variable
d. constraint
b. decision variable
Nonnegativity constraints ensure that
a. the problem modeling includes only nonnegative values in the constraints.
b. the solution to the problem will contain only nonnegative values for the decision variables.
c. the objective function of the problem always returns maximum quantities.
d. there are no inequalities in the constraints.
b. the solution to the problem will contain only nonnegative values for the decision variables.
A(n) _____ solution satisfies all the constraint expressions simultaneously.
a. feasible
b. objective
c. infeasible
d. extreme
a. feasible
Which algorithm, developed by George Dantzig, is effective at investigating extreme points in an
intelligent way to find the optimal solution to even very large linear programs?
a. The ellipsoidal algorithm
b. The complex algorithm
c. The trial-and-error algorithm
d. The simplex algorithm
d. The simplex algorithm
. _____ is the situation in which no solution to the linear programming problem satisfies all the constraints.
a. Unboundedness
b. Divisibility
c. Infeasibility
d. Optimality
c. Infeasibility
Problems with infeasible solutions arise in practice because:
a. management doesn't specify enough restrictions.
b. too many restrictions have been placed on the problem.
c. of errors in objective function formulation.
d. there are too few decision variables.
b. too many restrictions have been placed on the problem.
. 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 _____.
a. infeasibility
b. unbounded
c. infiniteness
d. semi-optimality
b. unbounded
The study of how changes in the input parameters of a linear programming problem affect the optimal
solution is known as_____.
a. regression analysis
b. cluster analysis
c. optimality analysis
d. sensitivity analysis
d. 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 _____.
a. objective function coefficient
b. shadow price
c. restrictive cost
d. right-hand side allowable increase
b. shadow price
Which of the following statements is most likely to be the objective function in this scenario?
a. Minimization of the number of stocks held
b. Maximization of expected return
c. Minimization of tax dues
d. Maximization of investment risk
b. Maximization of expected return
Restrictions on the type of permissible investments would be a _____ in this case.
a. feasible solution
b. surplus variable
19
c. slack variable
d. constraint
d. constraint
. Which of the following is most likely to be the objective function in this scenario?
a. Increasing the number of goods manufactured at the plant
b. Decreasing the cost of their raw material sourcing
c. Minimizing the cost of shipping goods from the plant to the store
d. Minimizing the quantity of goods distributed across the stores
c. Minimizing the cost of shipping goods from the plant to the store
Which of the following visualization tools could help understand this problem better?
a. A time-series plot
b. A scatter chart
c. A network graph
d. A contour plot
c. A network graph
The objective function for a linear optimization problem is: Max 3x + 5y, with one of the constraints
being x, y ≥ 0 and integer. x and y are the only decisions variables. This is an example of a(n) _____.
a. all-integer linear program
b. mixed-integer linear program
c. nonlinear program
d. binary integer linear program
a. all-integer linear program
. The linear program that results from dropping the integer requirements for the variables in an integer
linear program is known as _____.
a. convex hull
b. a mixed-integer linear program
c. LP relaxation
d. a binary integer linear program
c. LP relaxation
The objective function for an optimization problem is: Max 5x - 3y, with one of the constraints being x, y
≥ 0 and y integer. x and y are the only decisions variables. This is an example of a(n) _____.
a. all-integer linear program
b. mixed-integer linear program
c. LP relaxation of the integer linear program
d. binary integer linear program
b. mixed-integer linear program
In binary integer linear program, the integer variables take only the values:
a. 0 or 1.
b. 0 or ∞.
c. 1 or ∞.
d. 1 or -1.
a. 0 or 1.
The objective function for a linear optimization problem is: Max 3x + 2y, with one of the constraints
being x, y = 0, 1. x and y are the only decision variables. This is an example of a _____.
a. nonlinear program
b. mixed-integer linear program
c. LP relaxation of the integer linear program
d. binary integer linear program
d. binary integer linear program
The sum of two or more binary variables must be less than or equal to one in _____ constraint.
a. corequisite
b. conditional
c. multiple-choice
d. mutually exclusive
d. mutually exclusive
A constraint involving binary variables that does not allow certain variables to equal one unless certain
other variables are equal to one is known as a _____.
a. conditional constraint
b. corequisite constraint
c. k out of n alternatives constraint
d. mutually exclusive constraint
a. conditional constraint
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