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HBX Core Business Analytics Starting with 100- correct answers
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HBX Core Business Analytics Starting with 100- correct answers
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HBX CoreBusiness
Analytics
Starting with
100% correct
answers
A/B test - answer An experiment that
compares the value of a specified dependent
variable (such as the likelihood that a web
site visitor purchases an item) across two
different groups (usually a control group and
a treatment group). The members of each
group must be randomly selected to ensure
that the only difference between the groups
is the "manipulated" independent variable
(for example, the size of the font on two
otherwise-identical web sites). An A/B test is
,a hypothesis test that tests whether the
means of the dependent variable are the
same across the two groups. (An A/B test can
also be used to test whether another
parameter, such a standard deviation, is the
same across two groups.)
adjusted R-squared - answer A measure of
the explanatory power of a regression
analysis. Adjusted R-squared is equal to R-
squared multiplied by an adjustment factor
that decreases slightly as each independent
variable is added to a regression model.
Unlike R-squared, which can never decrease
when a new independent variable is added to
a regression model, Adjusted R-squared
drops when an independent variable is added
that does not improve the model's true
explanatory power. Adjusted R2 should
always be used when comparing the
explanatory power of regression models that
have different numbers of independent
variables.
alternative hypothesis - answer An
alternative hypothesis is the theory or claim
we are trying to substantiate, and is stated
,as the opposite of a null hypothesis. When
our data allow us to nullify the null
hypothesis, we substantiate the alternative
hypothesis.
asymmetric distribution - answer A
probability distribution that is not symmetric
around the mean.
average - answer The most common statistic
used to describe the center of the values in a
data set. The mean is also known as the
average. For a distribution that has discrete
values, the mean is equal to sum of the
values of all the data points in the set,
divided by the number of data points.
base case - answer The category of a
categorical variable for which a dummy
variable is NOT included in a regression
model. A regression model with a categorical
variable that has n categories should have n-
1 dummy variables. The coefficients of the
dummy variables included in the regression
model are interpreted in relation to the base
case. The analyst can select any category to
, be excluded from the regression model;
however, different base cases lead to
different interpretations of the dummy
variables' coefficients. For example, suppose
we are trying to determine the average
difference in height between men and women
in a sample, and suppose that on average
men are 5 inches taller than women in the
sample. If we use Female as the base case
then the coefficient for the dummy variable
for Male would be +5. If we use Male as the
base case, the coefficient for the dummy
variable for Female would be -5.
bias - answer The tendency of a
measurement process to over- or under-
estimate the value of a population
parameter. Although a sample statistic will
almost always differ from the population
parameter, for an unbiased sample, the
difference will be random. In contrast, for a
biased sample, the statistic will differ in a
systematic way (e.g., tend to be too high).
Some common reasons for bias include non-
random sampling methods and non-neutral
question phrasing.
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