N580 FINAL EXAM QUESTIONS AND ANSWERS | N580 FINAL STUDY
GUIDE & PRACTICE TEST 2026/2027
statistics vs. parameters - correct answer ✔✔analysis on a sample vs. analysis on the entire population
overview to data analysis - correct answer ✔✔quantitative: descriptive and inferential
descriptive: simply describe a characteristic of a population/sample or a phenomenon
inferential: hope to generalize from a sample to a population (based on probability)--we use parametric
and non-parametric statistics
parametric tests and non-parametric tests - correct answer ✔✔every statistical test has assumptions
that must be met
parametric tests have more stringent assumptions--two of the most critical assumptions: normal
distribution of the data and level of measurement (must be interval-like in nature)
non-parametric tests don't have such limitations
we like parametric tests b/c they are more powerful and more likely to find a difference if there is one
one chosen will depend on your data
analysis - correct answer ✔✔clearly the problem is the driving force--the sophistication of analysis will
never compensate for an insignificant problem
always remember the research question or hypothesis always drives the analysis
look at the hypothesis or question--should be able to begin to think about the type of analysis that
would be appropriate
when you are beginning to think about statistical tests... - correct answer ✔✔you must look at what
drives the tests-->the research question and the hypothesis--what are the variables and how are they
measured? what is the level of measurement?
if the question focuses on describing some phenomena - correct answer ✔✔N & % (if data are nominal
or categorical) or descriptive statistics (if measures are interval-like in nature--mean, standard deviation,
range)
if the research question or hypothesis is interested in a relationship between two variables - correct
answer ✔✔correlation
Pearson's r (parametric test) or Spearman Rho/Kendall's Tau (non-parametric test)
if the research question or hypothesis is interested in a difference between two independent groups -
correct answer ✔✔the independent t test (parametric) or the Mann Whitney U (if data weren't normally
distributed)
if the research question or hypothesis is interested in a difference between two or more independent
groups - correct answer ✔✔ANOVA (parametric) or the Kruskal Wallis (if data aren't normally distributed
or if measure is ordinal)
,if the research question or hypothesis is interested in differences in two groups that are dependent
(repeated measures) - correct answer ✔✔the paired t test (parametric) or Wilcoxon (non-parametric)
if the research question or hypothesis is interested in the difference in two or more groups that are
dependent - correct answer ✔✔RANOVA (parametric) or Friedman (non-parametric)
how can you choose? - correct answer ✔✔what is the research question or hypothesis asking?
are groups independent or dependent?
what is the level of measurement of the variables?
are the assumptions of the statistical test met, particularly that of normal distribution?
knowledge of statistics is necessary to all who read or conduct research - correct answer ✔✔research:
making observations or measurements on people, things, or events to answer a research question
statistics: a set of procedures for describing those measurements--how do we quantify and report these
measurements?
data - correct answer ✔✔the raw material of research
variable - correct answer ✔✔something that varies or takes on different values
we are always interested in variability and explaining variation
variables are also classified as... - correct answer ✔✔discrete: finite number of value (almost like you can
count)--obtained by counting
continuous: infinite number of value between any two points--obtained by measuring
statistical methods are sometimes described by the number of variables in the analysis - correct answer
✔✔univariate: average cholesterol
bivariate: average cholesterol (exercise group and sedentary group)
multivariate: average cholesterol (exercise: yes/no, diet: good/bad, gender: M/F)
measurement - correct answer ✔✔key to capturing variables
assigning numbers to objects, events, etc. according to the rules
some things are more difficult to measure than others--consider temperature vs. self-efficacy
level of measurement - correct answer ✔✔influences what statistical tests can be chosen
4 basic levels:
nominal
ordinal
interval
ratio
want to know about it when collecting data, when analyzing data (level of measurement will influence
statistical test you can select)
always measure at the highest level realistically possible: more powerful test, greater flexibility, more
info
nominal - correct answer ✔✔category: categorical variable (M/F/transgender, race, etc.--can go in one
but not the other)
can't treat mathematically
, if these are the dependent variable: they are reported by n and %, mode
also used in: grouping (study has 3 independent interventions [groups] looking at an independent
variable), logistic regression (results in odds ratios--dependent variable is categorical--given a certain
treatment, what are the odds the patient is dead or alive)
ex: preferred mode of transportation, blood type, gender
non-parametric
how are numbers assigned to nominal level data for statistical analysis? - correct answer ✔✔blood type
1=O+
2=A+
3=B+
4=AB+
and so forth
think about gender, race, marital status--how would you assign numbers to levels of these variables?
we assign numbers to enter them in a computer
recommend to always collect data at the highest level
ordinal - correct answer ✔✔uses numbers to designate ordering of an attribute--relative standing
describes an amount of some attribute but there is not an equivalent distance between each number (so
really is ranking)
think about track finishes--not an equivalent amount between 1st place and 2nd place, 2nd place and
3rd place, and so on
examples of ordinal data - correct answer ✔✔socioeconomic status
academic rank
psychological inventories (mini-mental status exam, QOL scales, etc.)
treatment of ordinal data varies - correct answer ✔✔parametric or non-parametric
general rule is non-parametric tests should be used
if there are 11 or so measures and if the scores are well-distributed, then parametric tests can be used
interval - correct answer ✔✔amount of an attribute, equal distance between each number in terms of
amount (no absolute 0 value)
ex: Fahrenheit scale
can be used in parametric tests so dependent variable is interval-like in nature and there is a normal
distribution
ratio - correct answer ✔✔same as interval but has an absolute 0
morphine in mgs, length in inches, Kelvin temp
can make comparative statements (twenty pounds is twice as heavy as ten pounds)
don't have to distinguish between ratio and interval data because statistically they are treated the same
identifying the characteristics of data - correct answer ✔✔can the data be put in order? no=nominal
do the data have units, including numbers of things? no=ordinal
yes=metric
do the data come from measuring or counting things? if measuring then continuous data, if counting
then discrete data
GUIDE & PRACTICE TEST 2026/2027
statistics vs. parameters - correct answer ✔✔analysis on a sample vs. analysis on the entire population
overview to data analysis - correct answer ✔✔quantitative: descriptive and inferential
descriptive: simply describe a characteristic of a population/sample or a phenomenon
inferential: hope to generalize from a sample to a population (based on probability)--we use parametric
and non-parametric statistics
parametric tests and non-parametric tests - correct answer ✔✔every statistical test has assumptions
that must be met
parametric tests have more stringent assumptions--two of the most critical assumptions: normal
distribution of the data and level of measurement (must be interval-like in nature)
non-parametric tests don't have such limitations
we like parametric tests b/c they are more powerful and more likely to find a difference if there is one
one chosen will depend on your data
analysis - correct answer ✔✔clearly the problem is the driving force--the sophistication of analysis will
never compensate for an insignificant problem
always remember the research question or hypothesis always drives the analysis
look at the hypothesis or question--should be able to begin to think about the type of analysis that
would be appropriate
when you are beginning to think about statistical tests... - correct answer ✔✔you must look at what
drives the tests-->the research question and the hypothesis--what are the variables and how are they
measured? what is the level of measurement?
if the question focuses on describing some phenomena - correct answer ✔✔N & % (if data are nominal
or categorical) or descriptive statistics (if measures are interval-like in nature--mean, standard deviation,
range)
if the research question or hypothesis is interested in a relationship between two variables - correct
answer ✔✔correlation
Pearson's r (parametric test) or Spearman Rho/Kendall's Tau (non-parametric test)
if the research question or hypothesis is interested in a difference between two independent groups -
correct answer ✔✔the independent t test (parametric) or the Mann Whitney U (if data weren't normally
distributed)
if the research question or hypothesis is interested in a difference between two or more independent
groups - correct answer ✔✔ANOVA (parametric) or the Kruskal Wallis (if data aren't normally distributed
or if measure is ordinal)
,if the research question or hypothesis is interested in differences in two groups that are dependent
(repeated measures) - correct answer ✔✔the paired t test (parametric) or Wilcoxon (non-parametric)
if the research question or hypothesis is interested in the difference in two or more groups that are
dependent - correct answer ✔✔RANOVA (parametric) or Friedman (non-parametric)
how can you choose? - correct answer ✔✔what is the research question or hypothesis asking?
are groups independent or dependent?
what is the level of measurement of the variables?
are the assumptions of the statistical test met, particularly that of normal distribution?
knowledge of statistics is necessary to all who read or conduct research - correct answer ✔✔research:
making observations or measurements on people, things, or events to answer a research question
statistics: a set of procedures for describing those measurements--how do we quantify and report these
measurements?
data - correct answer ✔✔the raw material of research
variable - correct answer ✔✔something that varies or takes on different values
we are always interested in variability and explaining variation
variables are also classified as... - correct answer ✔✔discrete: finite number of value (almost like you can
count)--obtained by counting
continuous: infinite number of value between any two points--obtained by measuring
statistical methods are sometimes described by the number of variables in the analysis - correct answer
✔✔univariate: average cholesterol
bivariate: average cholesterol (exercise group and sedentary group)
multivariate: average cholesterol (exercise: yes/no, diet: good/bad, gender: M/F)
measurement - correct answer ✔✔key to capturing variables
assigning numbers to objects, events, etc. according to the rules
some things are more difficult to measure than others--consider temperature vs. self-efficacy
level of measurement - correct answer ✔✔influences what statistical tests can be chosen
4 basic levels:
nominal
ordinal
interval
ratio
want to know about it when collecting data, when analyzing data (level of measurement will influence
statistical test you can select)
always measure at the highest level realistically possible: more powerful test, greater flexibility, more
info
nominal - correct answer ✔✔category: categorical variable (M/F/transgender, race, etc.--can go in one
but not the other)
can't treat mathematically
, if these are the dependent variable: they are reported by n and %, mode
also used in: grouping (study has 3 independent interventions [groups] looking at an independent
variable), logistic regression (results in odds ratios--dependent variable is categorical--given a certain
treatment, what are the odds the patient is dead or alive)
ex: preferred mode of transportation, blood type, gender
non-parametric
how are numbers assigned to nominal level data for statistical analysis? - correct answer ✔✔blood type
1=O+
2=A+
3=B+
4=AB+
and so forth
think about gender, race, marital status--how would you assign numbers to levels of these variables?
we assign numbers to enter them in a computer
recommend to always collect data at the highest level
ordinal - correct answer ✔✔uses numbers to designate ordering of an attribute--relative standing
describes an amount of some attribute but there is not an equivalent distance between each number (so
really is ranking)
think about track finishes--not an equivalent amount between 1st place and 2nd place, 2nd place and
3rd place, and so on
examples of ordinal data - correct answer ✔✔socioeconomic status
academic rank
psychological inventories (mini-mental status exam, QOL scales, etc.)
treatment of ordinal data varies - correct answer ✔✔parametric or non-parametric
general rule is non-parametric tests should be used
if there are 11 or so measures and if the scores are well-distributed, then parametric tests can be used
interval - correct answer ✔✔amount of an attribute, equal distance between each number in terms of
amount (no absolute 0 value)
ex: Fahrenheit scale
can be used in parametric tests so dependent variable is interval-like in nature and there is a normal
distribution
ratio - correct answer ✔✔same as interval but has an absolute 0
morphine in mgs, length in inches, Kelvin temp
can make comparative statements (twenty pounds is twice as heavy as ten pounds)
don't have to distinguish between ratio and interval data because statistically they are treated the same
identifying the characteristics of data - correct answer ✔✔can the data be put in order? no=nominal
do the data have units, including numbers of things? no=ordinal
yes=metric
do the data come from measuring or counting things? if measuring then continuous data, if counting
then discrete data
