N580 FINAL EXAM STUDY GUIDE
1. statistics vs. parameters ANSWER analysis on a sample vs. analysis on
the entire population
2. 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
3.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
4.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
, N580 FINAL EXAM STUDY GUIDE
5.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?
6.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)
7.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)
8.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)
9.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)
10. 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)
, N580 FINAL EXAM STUDY GUIDE
11. 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)
12. 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?
13. knowledge of statistics is necessary to all who read or conduct research ANSWER
re-
search: 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?
14. data ANSWER the raw material of research
15. variable ANSWER something that varies or takes on different values we are always
interested in variability and explaining variation
, N580 FINAL EXAM STUDY GUIDE
16. 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
17. statistical methods are sometimes described by the number of variables in the
analysis: univariate
ANSWER average cholesterol
bivariate: average cholesterol (exercise group and sedentary group)
multivariate: average cholesterol (exercise: yes/no, diet: good/bad, gender: M/F)
18. 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
19. level of measurement 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)
1. statistics vs. parameters ANSWER analysis on a sample vs. analysis on
the entire population
2. 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
3.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
4.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
, N580 FINAL EXAM STUDY GUIDE
5.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?
6.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)
7.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)
8.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)
9.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)
10. 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)
, N580 FINAL EXAM STUDY GUIDE
11. 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)
12. 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?
13. knowledge of statistics is necessary to all who read or conduct research ANSWER
re-
search: 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?
14. data ANSWER the raw material of research
15. variable ANSWER something that varies or takes on different values we are always
interested in variability and explaining variation
, N580 FINAL EXAM STUDY GUIDE
16. 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
17. statistical methods are sometimes described by the number of variables in the
analysis: univariate
ANSWER average cholesterol
bivariate: average cholesterol (exercise group and sedentary group)
multivariate: average cholesterol (exercise: yes/no, diet: good/bad, gender: M/F)
18. 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
19. level of measurement 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)
