BADM 210 Final Exam Questions and
Answers
Association Rules - ANSWER-An if-then statement describing the relationship
between item sets.
support count = frequency in a data set
Confidence = support(antecedent and consequent)/support(antecedent)
which means the conditional probability of the consequent item set occurring given
that the antecedent item set occurs.
Lift Ratio = confidence/(support of consequent/total # of transactions)
which means how effective an association rule is at identifying transactions in which
the consequent item set occurs versus a randomly selected transaction.
A lift ratio >1 suggests that there is some usefulness to the association rule and that
it is better at identifying cases when the consequent occurs than having no rule at all.
Census vs. Sampling - ANSWER-Obtaining a census is unviable because it's costly
and takes too long. Sampling cuts costs and takes less time by representing the
population.
Statistical Inference - ANSWER-Drawing conclusions about the population based on
estimates from a sample.
Creating Random Samples in Excel - ANSWER--In cell D1, enter the text Random
Numbers.
-In cells D2:D2501, enter the formula =rand()
-Select the cell range D2:D2501
-In the Home tab in the Ribbon:
-Click Copy in the Clipboard group
-Click the arrow below Paste in the Clipboard group.
-When the Paste window appears, click Values in the Paste Values area
-Press the Esc key
-Select cells A1:D2501 (data plus random numbers)
-In the Data tab on the Ribbon, click Sort in the Sort & Filter group
-When the Sort dialog box appears:
-Select the check box for My data has headers
-In the first Sort by dropdown menu, select Random Numbers
-Click OK
, Sample Estimates of the Parameters of the Population - ANSWER-We use sample
estimates to infer information about population parameters (which are usually
unknown).
The sample point estimates can be xbar (mean), s (stdev), pbar (proportion)
Normal Distribution - ANSWER-Smaller stdev creates a narrower and taller
distribution.
Larger stdev creates a wider and shorter distribution.
The area under the curve reflects a proabability.
Standard Deviation of the Sampling Distribution (Standard Error)*** - ANSWER-sx =
s/sqrt(n)
stderror = stdev/sqrt(sample size)
Should be able to use stderror for population porportion (p) or 𝜎𝑝̅= sqrt(𝑝0(1 −
𝑝0)/n).
Sampling Distribution - ANSWER-It is the distribution of sample means if we took
multiple samples.
The sample means of a sampling distribution will vary in a tighter range than the
sample.
This means the sampling distribution is more accurate than just a single sample.
Central Limit Theorem - ANSWER-As sample sizes get large, the sampling
distribution will approach a normal distribution, regardless of the shape of the original
population.
t-Distribution - ANSWER-If the sampling distribution of xbar (mean) follows a normal
distribution, we address this additional source of uncertainty by using a probability
distribution known as the t distribution.
These t distributions are similar in shape to the standard normal distribution but are
wider; this reflects the additional uncertainty that results from using an estimate
stdev.
The greater the degrees of freedom, the narrower and taller the t-distribution
becomes as it gets closer to looking like a standard normal distribution.
t-Distribution and Sampling Distributions - ANSWER-We can calculate the mean and
standard deviation for repeated samples. For a confidence level of 90%, we expect
that our confidence interval contains the population mean for 90% of the samples.
Confidence Level - ANSWER-A confidence level of 90% means that we are 90%
confident that confidence interval contains the population mean.
Answers
Association Rules - ANSWER-An if-then statement describing the relationship
between item sets.
support count = frequency in a data set
Confidence = support(antecedent and consequent)/support(antecedent)
which means the conditional probability of the consequent item set occurring given
that the antecedent item set occurs.
Lift Ratio = confidence/(support of consequent/total # of transactions)
which means how effective an association rule is at identifying transactions in which
the consequent item set occurs versus a randomly selected transaction.
A lift ratio >1 suggests that there is some usefulness to the association rule and that
it is better at identifying cases when the consequent occurs than having no rule at all.
Census vs. Sampling - ANSWER-Obtaining a census is unviable because it's costly
and takes too long. Sampling cuts costs and takes less time by representing the
population.
Statistical Inference - ANSWER-Drawing conclusions about the population based on
estimates from a sample.
Creating Random Samples in Excel - ANSWER--In cell D1, enter the text Random
Numbers.
-In cells D2:D2501, enter the formula =rand()
-Select the cell range D2:D2501
-In the Home tab in the Ribbon:
-Click Copy in the Clipboard group
-Click the arrow below Paste in the Clipboard group.
-When the Paste window appears, click Values in the Paste Values area
-Press the Esc key
-Select cells A1:D2501 (data plus random numbers)
-In the Data tab on the Ribbon, click Sort in the Sort & Filter group
-When the Sort dialog box appears:
-Select the check box for My data has headers
-In the first Sort by dropdown menu, select Random Numbers
-Click OK
, Sample Estimates of the Parameters of the Population - ANSWER-We use sample
estimates to infer information about population parameters (which are usually
unknown).
The sample point estimates can be xbar (mean), s (stdev), pbar (proportion)
Normal Distribution - ANSWER-Smaller stdev creates a narrower and taller
distribution.
Larger stdev creates a wider and shorter distribution.
The area under the curve reflects a proabability.
Standard Deviation of the Sampling Distribution (Standard Error)*** - ANSWER-sx =
s/sqrt(n)
stderror = stdev/sqrt(sample size)
Should be able to use stderror for population porportion (p) or 𝜎𝑝̅= sqrt(𝑝0(1 −
𝑝0)/n).
Sampling Distribution - ANSWER-It is the distribution of sample means if we took
multiple samples.
The sample means of a sampling distribution will vary in a tighter range than the
sample.
This means the sampling distribution is more accurate than just a single sample.
Central Limit Theorem - ANSWER-As sample sizes get large, the sampling
distribution will approach a normal distribution, regardless of the shape of the original
population.
t-Distribution - ANSWER-If the sampling distribution of xbar (mean) follows a normal
distribution, we address this additional source of uncertainty by using a probability
distribution known as the t distribution.
These t distributions are similar in shape to the standard normal distribution but are
wider; this reflects the additional uncertainty that results from using an estimate
stdev.
The greater the degrees of freedom, the narrower and taller the t-distribution
becomes as it gets closer to looking like a standard normal distribution.
t-Distribution and Sampling Distributions - ANSWER-We can calculate the mean and
standard deviation for repeated samples. For a confidence level of 90%, we expect
that our confidence interval contains the population mean for 90% of the samples.
Confidence Level - ANSWER-A confidence level of 90% means that we are 90%
confident that confidence interval contains the population mean.
