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Data Driven Decision Making WGU C207 Exam Latest 2024 | Data Driven Decision Making WGU C207 Exam Update Questions and Correct Answers Rated A+ $23.60   Add to cart

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Data Driven Decision Making WGU C207 Exam Latest 2024 | Data Driven Decision Making WGU C207 Exam Update Questions and Correct Answers Rated A+

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Data Driven Decision Making WGU C207 Exam Latest 2024 | Data Driven Decision Making WGU C207 Exam Update Questions and Correct Answers Rated A+

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  • July 25, 2024
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Data Driven Decision Making WGU C207
Exam Latest 2024 | Data Driven Decision
Making WGU C207 Exam Update 2024-2025
Questions and Correct Answers Rated A+
How would a greater number of samples and a fewer number of
populations affect an ANOVA analysis? -ANSWER-The results would be
more accurate.

Mary is determining the likelihood that she will lose money on an
investment. There is an expected 10 percent gain in a normally distributed
dataset, with a standard deviation of 10 percent. The likelihood she'll lose
money is _______ percent. -ANSWER-16

Select the choice that is true. Regression analysis: -ANSWER-takes
information from one data set and can predict information for another data
set.

Jane works for a public health company. She is working on an anti-tobacco
campaign and is interested in how smoking cigarettes affects a smoker's
cholesterol. She could use the number of cigarettes smoked per day as her
_____ variable and place it on the __-axis. -ANSWER-independent, x

We perform a regression analysis on a pair of variables and determine that
there is a linear relationship. The regression line is determined to be
y=12x−5y=12x-5. What type of linear relationship exists between the
independent variable, x, and the dependent variable, y? -ANSWER-positive

describe R-squared? -ANSWER-a) R-squared measures the goodness of
fit.
b) R-squared can be misleading if there are false independent variables.
c) R-squared is 1.0 when correlation is -1 or 1.

,Which of the following are technique a manager uses when forecasting? -
ANSWER-A)Time Series
c) Associative
d) Judgmental

Which of the following are advantages of cluster analysis? -ANSWER-b) It
sorts individual data points into different groups.
c) It will not help in determining target markets.
d) It does not identify successful and unsuccessful habits and systems.

A trend is... -ANSWER-a general slope upward or downward over a long
period of time.

If there is a relationship between variables, but the relationship is not linear,
what possible challenge with regression could it be? -ANSWER-Polynomial
Regression

Catherine is trying to sell a ticket to the Super Bowl. She is determining
whether or not she should sell a ticket now or wait until just before the
game and try and sell it then. Currently, someone is offering $350 for the
ticket. From research of past prices, she knows that the tickets immediately
before the Super Bowl are sold for about $500. She determines that there
is a 75 percent chance she will be able to sell the ticket immediately before
the Super Bowl. Based on expected payoffs from risk decision making,
what should she do? How much is the difference if she chooses to sell now
-ANSWER-Catherine should wait to sell ticket; the difference will be $25.

Heteroscedasticity -ANSWER-A regression in which the variances in y for
the values of x are not equal

Cumulative Average-Time Learning Model -ANSWER-A learning curve
model in which the cumulative average time per unit declines by a constant
percentage each time the cumulative quantity of units produced is doubled

,Dependent Variable -ANSWER-The variable whose value depends on one
or more variables in the equation; typically the cost or activity to be
predicted

Independent Variable -ANSWER-The variable presumed to influence
another variable (dependent variable); typically it is the level of activity or
cost driver

Analysis of Variance (ANOVA) -ANSWER-A statistical method that helps
identify the sources of variability by comparing their means or averages; it
compares the variation within a sample to the variation between samples to
see if any differences are the result of some contributing factor or if the
differences occur by chance alon

Experience Curve -ANSWER-A curve that shows the decline in cost per
unit in various business functions of the value chain as the amount of these
activities increases

Crossover Analysis -ANSWER-Allows a decision maker to identify the
crossover point, which represents the point at which we are indifferent
between the plans

Cyclicality -ANSWER-Repetition of up (peaks) or down movements
(troughs) that follow or counteract a business cycle that can last several
years

Linear Programming -ANSWER-A mathematical tool used to optimize a
function (the objective function) subject to various constraints, all of which
are linear. Often used to find the combination of products that will maximize
profits or minimize costs

Simple Linear Regression -ANSWER-A form of regression analysis with
only one independent variable

, Regression Line -ANSWER-the "line of best fit" where the margin of error
at every point is minimized

Data Management -ANSWER-The management, including cleaning and
storage, of collected data

Random Variation -ANSWER-The variability of a process which might be
caused by irregular fluctuations due to chance that cannot be anticipated,
detected, or eliminated

Seasonality -ANSWER-Regular pattern of volatility, usually within a single
year

Homoscedasticity -ANSWER-A regression in which the variances in y for
the values of x are equal or close to equal

Irregularity -ANSWER-One-time deviations from expectations caused by
unforeseen circumstances such as war, natural disasters, poor weather,
labor strikes, single-occurrence company-specific surprises or
macroeconomic shocks

Chi-squared Test -ANSWER-A hypothesis test that is used to examine the
distribution of categorical data

Expected Value -ANSWER-The Expected Value for an alternative is the
sum of all possible payoffs for that alternative, each weighted by the
probability of that payoff occurring

Multiple Linear Regression -ANSWER-A statistical method used to model
the relationship between one dependent (or response) variable and two or
more independent (or explanatory) variables by fitting a linear equation to
observed data

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