DATA DRIVEN DECISION MAKING FINAL
PRACTICE SOLUTION 2026 VIEW AHEAD
TESTED SET
◉ Conditional Probability. Answer: The probability of an event
occurring given that another event has occurred.
◉ Population variance. Answer: where:
σ2 = the population variance
μ = the population mean
∑(x - μ)2 = the sum of the squared differences between each data
point and the mean. That is, you square each data point's difference
from the mean, then add these squared numbers together
N= the size of the population
◉ Population Standard Deviation. Answer: where:
σ2 = the population variance
μ = the population mean
∑(x - μ)2 = the sum of the squared differences between each data
point and the mean. That is, you square each data point's difference
from the mean, then add these squared numbers together
N= the size of the population
,Remember, population standard deviation (σ) is the square root of
population variance.
◉ Sample Variance. Answer: where:
s2 = the sample variance
x = the sample mean
∑(x - x)2 = the sum of the squared differences between each data
point and the mean. That is, you square each data point's difference
from the mean, then add these squared numbers together
n= the sample size
◉ Sample Standard Deviation. Answer: where:
s2 = the sample variance
x = the sample mean
∑(x - x)2 = the sum of the squared differences between each data
point and the mean. That is, you square each data point's difference
from the mean, then add these squared numbers together
n= the sample size
Remember, sample standard deviation (s) is the square root of
sample variance.
◉ Bassel's correction. Answer: The replacement of N with n - 1
yields a more accurate number for a sample — especially a small
sample. When the size of the sample (n) is very large, the difference
,between the population and sample variances and standard
deviations becomes very small.
◉ Quartile. Answer: Four equal groups into which a population can
be divided.
◉ Interquartile. Answer: The difference between the third quartile
and the first quartile. To determine the first and third quartiles,
order the data from lowest value to highest value. Then separate the
data into four equal groups.
◉ Histograms. Answer: Measures how continuous data is
distributed over various ranges. A graph that displays continues
data.
◉ Bar Graph. Answer: Measures data that is distributed over groups
or categories.
◉ Proportion. Answer: A type of ratio where the number of
observations that are part of a specific group is compared to the
total relevant population.
◉ Probability Distribution. Answer: A list of all of the different
probabilities of each outcome that can occur. This is often displayed
as a graph, table, or formula
, ◉ Probability functions. Answer: Functions that assign probabilities
to values of a random variable, determine the information in a
probability distribution. Needs to have the sum of the probability
values equal to one and also needs each probability value to be
greater than zero and less than one.
◉ P(X) = { P(2-9) = 0.615
P(10-K) = 0.308
P(A) = 0.077 }. Answer: A probability distribution is displayed as a
function it shows the probability of each outcome. (This example is
drawing a card from a suit
◉ Probability density functions are used for..... Answer: Continuous
random variables. A probability distribution is continuous if there is
any number of outcomes in a range. Like temperature.
◉ Probability mass functions are used for..... Answer: Discrete
random variables. A probability distribution is discrete if there are a
defined number of outcomes. Like working computers or being
pregnant; you are or you are not.
PRACTICE SOLUTION 2026 VIEW AHEAD
TESTED SET
◉ Conditional Probability. Answer: The probability of an event
occurring given that another event has occurred.
◉ Population variance. Answer: where:
σ2 = the population variance
μ = the population mean
∑(x - μ)2 = the sum of the squared differences between each data
point and the mean. That is, you square each data point's difference
from the mean, then add these squared numbers together
N= the size of the population
◉ Population Standard Deviation. Answer: where:
σ2 = the population variance
μ = the population mean
∑(x - μ)2 = the sum of the squared differences between each data
point and the mean. That is, you square each data point's difference
from the mean, then add these squared numbers together
N= the size of the population
,Remember, population standard deviation (σ) is the square root of
population variance.
◉ Sample Variance. Answer: where:
s2 = the sample variance
x = the sample mean
∑(x - x)2 = the sum of the squared differences between each data
point and the mean. That is, you square each data point's difference
from the mean, then add these squared numbers together
n= the sample size
◉ Sample Standard Deviation. Answer: where:
s2 = the sample variance
x = the sample mean
∑(x - x)2 = the sum of the squared differences between each data
point and the mean. That is, you square each data point's difference
from the mean, then add these squared numbers together
n= the sample size
Remember, sample standard deviation (s) is the square root of
sample variance.
◉ Bassel's correction. Answer: The replacement of N with n - 1
yields a more accurate number for a sample — especially a small
sample. When the size of the sample (n) is very large, the difference
,between the population and sample variances and standard
deviations becomes very small.
◉ Quartile. Answer: Four equal groups into which a population can
be divided.
◉ Interquartile. Answer: The difference between the third quartile
and the first quartile. To determine the first and third quartiles,
order the data from lowest value to highest value. Then separate the
data into four equal groups.
◉ Histograms. Answer: Measures how continuous data is
distributed over various ranges. A graph that displays continues
data.
◉ Bar Graph. Answer: Measures data that is distributed over groups
or categories.
◉ Proportion. Answer: A type of ratio where the number of
observations that are part of a specific group is compared to the
total relevant population.
◉ Probability Distribution. Answer: A list of all of the different
probabilities of each outcome that can occur. This is often displayed
as a graph, table, or formula
, ◉ Probability functions. Answer: Functions that assign probabilities
to values of a random variable, determine the information in a
probability distribution. Needs to have the sum of the probability
values equal to one and also needs each probability value to be
greater than zero and less than one.
◉ P(X) = { P(2-9) = 0.615
P(10-K) = 0.308
P(A) = 0.077 }. Answer: A probability distribution is displayed as a
function it shows the probability of each outcome. (This example is
drawing a card from a suit
◉ Probability density functions are used for..... Answer: Continuous
random variables. A probability distribution is continuous if there is
any number of outcomes in a range. Like temperature.
◉ Probability mass functions are used for..... Answer: Discrete
random variables. A probability distribution is discrete if there are a
defined number of outcomes. Like working computers or being
pregnant; you are or you are not.
