N580 Final Exam Questions With Correct Marking
Scheme
/statistics vs. parameters - Answer-analysis on a sample vs. analysis on the entire
population
/.overview to data analysis - 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 - 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 - 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... - 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 - 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 - 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 - 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 - 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) - 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 - Answer-RANOVA (parametric) or Friedman (non-
parametric)
/.how can you choose? - 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 - 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 - Answer-the raw material of research
/.variable - Answer-something that varies or takes on different values
we are always interested in variability and explaining variation
/.variables are also classified as... - 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
- 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 - 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 - Answer-influences what statistical tests can be chosen
4 basic levels:
nominal
ordinal
Scheme
/statistics vs. parameters - Answer-analysis on a sample vs. analysis on the entire
population
/.overview to data analysis - 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 - 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 - 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... - 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 - 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 - 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 - 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 - 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) - 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 - Answer-RANOVA (parametric) or Friedman (non-
parametric)
/.how can you choose? - 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 - 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 - Answer-the raw material of research
/.variable - Answer-something that varies or takes on different values
we are always interested in variability and explaining variation
/.variables are also classified as... - 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
- 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 - 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 - Answer-influences what statistical tests can be chosen
4 basic levels:
nominal
ordinal
