ISSCM final Exam Questions and Answers Solved 100%
statistics - Answers The science of collecting, organizing, analyzing, interpreting and presenting data to
assist in making more effective decisions.
Descriptive statistics - Answers used to organize and summarize data in an informative way that it is easy
to understand.
Inferential statistics - Answers involve estimating properties of a population based on a sample of data
from the population.
population - Answers the entire set of individuals or objects of interest, or the measurements obtained.
It contains all cases of a specified group with which researchers are interested.
sample - Answers a portion or part of the population of interest. It contains a subset of cases from a
population dataset.
Parameters - Answers numbers that summarize data for an entire population.
Statistics - Answers numbers that summarize data from a sample.
numerical variable/quantitative variable - Answers When a variable has measured numerical values with
units and the variable tells us about the quantity of what is measured
categorical/qualitative variable - Answers When a variable names categories and answers questions
about how cases fall into those categories
continuous variable - Answers a numerical variable with an infinite number of possible values, generally
the result of a measurement.
discrete variable - Answers a numerical variable that can only take on whole numbers, generally the
result of counting.
Ordinal variables - Answers - qualitative variables ranked or ordered according to some relationship with
one another.
- The order of the values is what's important and significant, but the differences between each one is not
really known.
- Ordinal scales are typically the measures of non-numeric concepts like satisfaction, happiness,
discomfort, etc.
(examples : rank in class)
Interval variables - Answers - quantitative variables with a meaningful order and fixed distance between
values based on a known unit of measurement.
, - The difference between values is meaningful, but the zero point is arbitrary and does not mean
nothingness.
(examples : temperature, dress size)
Ratio variables - Answers - quantitative variables with the characteristics of interval variables, but the
zero point is meaningful and represents an absence of the characteristic.
- As such, the ratio between two values is meaningful.
(examples : profit, fuel efficiency, distance to class)
frequency table - Answers a grouping of qualitative data into mutually exclusive and collectively
exhaustive classes showing the number of observations in each class.
- consists of a table with each category (class) along with the count for each class and provides a
summary of the distribution for one qualitative variable.
Mutually exclusive - Answers each observation is only in one class
Collectively exhaustive - Answers there is a class for each value
relative frequency table - Answers includes the addition of a percent column whereby each of the class
frequencies is divided by the total number of observations to show class proportion relative to the
whole.
bar chart - Answers the most common graphic topresent a qualitative variable and is a graph that shows
the classes (categories) on the horizontalaxis and the class frequencies on the verticalaxis.
pie chart - Answers a chart that shows the proportion or percentage that each class represents of the
total number of frequencies.
- Useful in conceptualizing percentage distributions. Sum adds up to 100%.
Contingency tables - Answers used to examine the relationship between two categorical variables
frequency distribution - Answers a table grouping quantitative data into mutually exclusive and
collectively exhaustive classes showing the number of observations in each class.
relative frequency distribution - Answers includes the addition of a percent column whereby each of the
class frequencies is divided by the total number of observations to show class proportion relative to the
whole.
how to decide on the number of classes - Answers Use the 2^ 𝑘 > 𝑛 rule, where
- 𝑘 is the number of classes and
- 𝑛 is the number of observations in the dataset
statistics - Answers The science of collecting, organizing, analyzing, interpreting and presenting data to
assist in making more effective decisions.
Descriptive statistics - Answers used to organize and summarize data in an informative way that it is easy
to understand.
Inferential statistics - Answers involve estimating properties of a population based on a sample of data
from the population.
population - Answers the entire set of individuals or objects of interest, or the measurements obtained.
It contains all cases of a specified group with which researchers are interested.
sample - Answers a portion or part of the population of interest. It contains a subset of cases from a
population dataset.
Parameters - Answers numbers that summarize data for an entire population.
Statistics - Answers numbers that summarize data from a sample.
numerical variable/quantitative variable - Answers When a variable has measured numerical values with
units and the variable tells us about the quantity of what is measured
categorical/qualitative variable - Answers When a variable names categories and answers questions
about how cases fall into those categories
continuous variable - Answers a numerical variable with an infinite number of possible values, generally
the result of a measurement.
discrete variable - Answers a numerical variable that can only take on whole numbers, generally the
result of counting.
Ordinal variables - Answers - qualitative variables ranked or ordered according to some relationship with
one another.
- The order of the values is what's important and significant, but the differences between each one is not
really known.
- Ordinal scales are typically the measures of non-numeric concepts like satisfaction, happiness,
discomfort, etc.
(examples : rank in class)
Interval variables - Answers - quantitative variables with a meaningful order and fixed distance between
values based on a known unit of measurement.
, - The difference between values is meaningful, but the zero point is arbitrary and does not mean
nothingness.
(examples : temperature, dress size)
Ratio variables - Answers - quantitative variables with the characteristics of interval variables, but the
zero point is meaningful and represents an absence of the characteristic.
- As such, the ratio between two values is meaningful.
(examples : profit, fuel efficiency, distance to class)
frequency table - Answers a grouping of qualitative data into mutually exclusive and collectively
exhaustive classes showing the number of observations in each class.
- consists of a table with each category (class) along with the count for each class and provides a
summary of the distribution for one qualitative variable.
Mutually exclusive - Answers each observation is only in one class
Collectively exhaustive - Answers there is a class for each value
relative frequency table - Answers includes the addition of a percent column whereby each of the class
frequencies is divided by the total number of observations to show class proportion relative to the
whole.
bar chart - Answers the most common graphic topresent a qualitative variable and is a graph that shows
the classes (categories) on the horizontalaxis and the class frequencies on the verticalaxis.
pie chart - Answers a chart that shows the proportion or percentage that each class represents of the
total number of frequencies.
- Useful in conceptualizing percentage distributions. Sum adds up to 100%.
Contingency tables - Answers used to examine the relationship between two categorical variables
frequency distribution - Answers a table grouping quantitative data into mutually exclusive and
collectively exhaustive classes showing the number of observations in each class.
relative frequency distribution - Answers includes the addition of a percent column whereby each of the
class frequencies is divided by the total number of observations to show class proportion relative to the
whole.
how to decide on the number of classes - Answers Use the 2^ 𝑘 > 𝑛 rule, where
- 𝑘 is the number of classes and
- 𝑛 is the number of observations in the dataset
