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102 Cards in this Set

  • Front
  • Back
What are the 2 types of statistics?
Descriptive
Inferential
Define Descriptive statistics.
Allows us to 'describe.' Involves:
measure of central tendencies
measure of variability
crosstabs/Chi Square
Correlations
What are the measures of central tendencies? Define each.
Mean - average

median - the 'middle' element when the data is lined up in order of magnitude

mode - the data element that occurs most frequently
What is the best measure of central tendency?
mean
What are the Levels of Data? Define them.
nominal - has no order; only gives names or labels to categories; e.g. sex being male or female
ordinal - has order but the interval b/w measurements has no meaning; e.g. Likert scale
interval - meaningful intervals b/w measurements but no true zero
ratio - highest level of measurement; has a starting point (zero) with meaningful intervals b/w measurements
What is probability?
the chance that a particular event or outcome will occur

values range from 0 to 1
percentages range from 0 to 100%
What is standard deviation (SD)?
a descriptive statistic measuring the degree of variability in a set of scores

square root of the variance
Define Standard Error of the Mean (SEM)?
SEM = SD/square root of N

where N=sample size

when SEM is large there is more variability in the sample means
What is a Z-score?
the number of SDs a score of interest lies from the mean

Z = (x-xbar)/SD
x=score
xbar=mean
What does p<.05 mean?
5 times out of 100 the difference is due to chance

it is a significance level
What is a type I error?
known as alpha (usually .05)

reject the null hypothesis when it is true

it is a false positive
What is a type II error?
beta (usually .2)
accept the null hypothesis when it is false

it is a false negative
What are inferential statistics & give types of tests used.
explores the relationship b/w variables & the generalizability from sample to population

tests:
t-tests
ANOVA & ANCOVA
Linear & logistic regression
characteristics of a positively skewed distribution
mean>median>mode
characteristics of a negatively skewed distribution
mode>median>mean
define parametric tests
DV is I/R
IV is nominal or I/R
uses T-test, ANOVA, ANCOVA or regression
define non-parametric tests
Measurement level of variables are nominal or ordinal

uses Chi-Square Test or crosstabs
True or False

In a normal distribution, the mean, median, and mode are equal.
True
What is variability?
measures how dispursed the scores are in a distribution

not a reliable measurement as extreme scores can distort the range
What is variance?
average of the squared differences of the mean
what is standard deviation?
the square root of the variance (where variance is the average of the squared differences from the mean)

SD is a descriptive statistic that measures the degree of variability in a set of scores
What is 1SD from the mean?
34%

if you want the range + or - 1, then it's 68%
What is 2SD from the mean?
47.5%

if you want the range + or - 1, then it's 95%
What is 3SD from the mean?
98%

if you want the range + or - 1, then it's 49%
What level of data are these:

weight
sex: male/female
Likert scale
weight - ratio
sex: male/female - nominal
Likert scale - ordinal
When do we use the Chi Square test? What kind of data does it use?
We use Chi Squared when we want to know if the expected number differs significantly from the observed number.

uses nominal or ordinal data
Characteristics of Chi squared
non-parametric test that measures if the expected number differs significantly from the observed
char. by one parameter called degrees of freedom
measures are independent of each other
always positive
Define simple correlation
Pearson's R

relationship between two variables

ranges between -1 and +1

the absolute value of the coefficient reflects the strength of the correlation
What does r=.8 mean?
strong positive correlation
What does r=.1 mean?
nothing or very weak correlation
What is shared variance?
the square of the correlation coefficient

it is a measure of the amount of variance shared by two variables

eg r=.20, so the shared variance is r squared, which = .04 or 4%

another way to say it is the IV accounts for 4% of the variance of the DV
assumptions of correlations
can be calculated with all levels of data
sample must represent the population
relationship of X & Y must be linear
assume homoscedasticity
What is homoscedasticity?
variance homogeneity

for every value of X, the distribution of Y scores must have approximately equal variability
What are the Rules of Thumb for strength of correlations?

e.g. 0.4-0.6 means what?
0.8 to 1.0 (very strong relationship)
0.6 to 0.8 (strong relationship)
0.4 to 0.6 (moderate relationship)
0.2 to 0.4 (weak relationship)
0.0 to 0.2 No to weak relationship)
Which group of people are we talking about when we use the following terms?

statistic
parameter
statistic ---> sample
parameter ---> population
Define non-parametric.
categorical or non-normal data
Measurement level of variables are nominal or ordinal
Chi-Square Test
Crosstabs
Define parametric.
based on normality of data

DV is I/R
IV is nominal or I/R
T-test, ANOVA and ANCOVA
Regression
If your correlation statistic is -.702, what is the strength of the correlation?
strong negative correlation
How much variance is shared between 2 variables with an r= .702?
r2 = .702 *.702 = .493 or 49.3%

so the IV accounts for 49.3% of the variance of the DV, OR the variance shared between the 2 variables is 49.3%
Z=2. What does this mean?
This is a Z-score, the number of SDs the score lies away from the mean.

Z=2 means the score of interest is 2SD away from the mean
another name for significance.
P-value
What type of error is this or is it the correct decision?

The null hypothesis is true but the test rejects it
Type I error

you are rejecting the null hypothesis when it's true (false negative)
What type of error is this or is it the correct decision?

The null hypothesis is false but the test accepts it
Type II error

you are accepting the null hypothesis when it's false (false negative)
Why use a T-test? What are some characteristics of it?
to find the difference between 2 means in 2 groups

IV is nominal
DV (or outcome) is continuous (ordinal, I/R)
assume 2 mutually exclusive groups
equal variances are assumed
What is the purpose of ANOVA?
to find if a difference between the means of 2 or more groups exists
What is the purpose of a Post-Hoc test?
to define the difference between groups
How many degrees of freedom in a T-test with 24 people in each group?
46

df = (24 people x 2 groups) - 2
For a T-test, what is the scale of measurement for the dependent variable?
ordinal or I/R --> treated as continuous
in a T-test, are the distributions of the 2 groups homogeneous?
yes, homogeneity of variance
what are the 2 types of T-tests?
independent - 2 independent groups that are mutually exclusive

paired - one group with 2 measures over time
A Levene's test has the following results:
F=1.153
Sig.=.286

What does this mean?
the results are not significant, there is no difference between the groups therefore we assume equal variances.
A Levene's test has the following results:
F=6.228
Sig.=.002

What does this mean?
significant results, there are differences between the groups therefore equal variances can not be assumed
In an ANOVA test, what type of data is used for the IV?
nominal (categorical)
In an ANOVA test, what type of data is used for the DV?
ordinal, I/R (continuous)
What is the difference between a One-way and a Two-way ANOVA?
A one-way ANOVA has one IV and one DV.

A two way has two IV and one DV
What is the purpose of a T-test?
It assesses the difference between the means of 2 groups.
In a T-test, what kind of variable is the IV? the DV?
IV is nominal

DV is ordinal, interval or ratio (continuous)
Name and define the 2 types of T-tests.
independent T-test - looking at the difference in means of 2 mutually exclusive groups

paired T-test - looking at the difference of the means of one group with 2 measures over time. (e.g. pre & post test)
What are the assumptions of a T-test?
IV is categorical (nominal)
2 mutually exclusive groups
normal distribution of the DV
homogeneity of variance (equal variances are assumed, i.e. Levene's test)
Define degrees of freedom.
the number of categories or classes being tested minus 1
What is the purpose of ANOVA?
tests the difference of means among more than 2 groups
What level of data is the IV in an ANOVA study? DV?
IV is nominal

DV is continuous (I/R)
What are the 'assumptions' of an ANOVA?
same as the T-test

groups are mutually exclusive
normal distribution of DV
homogeneity of variance.
Define mean square.
the average amount of variance per degree of freedom
The F-statistic correlates with what test? The t-statistic correlates with what test?
F-statistic is the result of ANOVA

t-statistic is the result of a T-test
What does the F-statistic mean in an ANOVA?
in order to reject the null hypothesis, the F-statistic must meet or exceed the critical value (that is looked up on a chart in the back of Munro)
True or False

The F-statistic in an ANOVA can either be positive or negative.
FALSE

The F-statistic is always positive b/c we are only testing to see if there is a difference b/w groups, not the direction of the difference.
True or False

the ANOVA produces only one critical F-value and it is always positive.
TRUE
True or False

An ANOVA tells you there are differences b/w groups and where they are.
FALSE

ANOVA only tells you there are differences. A post-hoc test tells you where those differences are.
How is F derived in an ANOVA?
F = MS(between)/MS(within)

where MS=mean square
What is an ANCOVA test?
it is an ANOVA but control for extraneous variable.
What are the assumptions of an ANCOVA?
the same as an ANOVA:
groups should be mutually exclusive
homogeneity of variances
DV should be normally distributed
the covariate should be continuous (age)
2 additional assumptions are:
the covariate & DV must show a linear relationship
directrion & strength of the relationship b/w DV and covariate must be similar in each group-->homogeneity of regression
What are the types of regression?
simple - one IV used to predict a DV

multiple - multiple IVs used to predict a DV

Logistic - used when DV is categorical (nominal data) in nature
Define the components of this equation:
Y = B0 + B1X1 + E
Y = the predicted score or the DV (outcome)

B0 = constant (Y-intercept on a line graph)

B1 = regression coefficient, representing the amt Y changes when the IV (x) changes by one unit

E = error
When do we use regression?
It's used to make predictions:

when the relationship b/w 2 variable is perfectly linear, knowledge of value of one variable allows you to predict the value of another variable with accuracy
The regression line is also known as what?
The "line of best fit."
True or False

Regression is the line of best fit therefore it can curve through the scatterplot to create the best fit.
FALSE

It is the best linear representation of the data
Characteristics of the regression line.
It is the line of best fit.
The line passes through the exact center of the data on a scatterplot.
The distance b/w the point (value) & the line is the easurement error
The regression line is the best line with the least amount of error.
True or False

The regression line is the best line with the least amount of error.
TRUE
In a regression, define the following:
R squared
F-statistic
T-statistic
R squared is shared variance (it is the correlation coefficient squared)
F-statistic is the same as ANOVA, the overall significance of the model.
T-statistic is the significance of each IV
In a regression equation, what does the y-intercept represent? the Y?
Y-intercept is the constant

Y is what you are solving for, the DV or the outcome
What is the purpose of Logit regression?
It uses MLE (maximum likelihood estimation) to transform the probability of an event occurring into it's odds
Define Odds Ratio.
ratio of 2 probabilities; the probability of the event occurring versus the probability that it will not occur
What is a cohort study?
What is a case control study?
both are epidemiological studies.
The cohort studies look at relative risk, and work from treatment to outcome.

The case control studies look at the odds ratio and work from outcome to treatment.
Which study does not obtain relative risk directly, cohort or case control studies?
case control studies

case control studies obtain the odds ratio which is then used to estimate the relative risk. It tends to overestimate it.
True or False

Logistic regression is only used case control studies to produce an odds ratio.
FALSE

It is used in both cohort and case control studies. It produces an odds ratio which is often interpreted as relative risk.
Define odds.
another way of presenting probability

the probability of occurrence over the probability of non-occurrence
Define odds ratio
comparing the odds of 2 groups

e.g. the odds of rolling a six if female

group 1 - odds of rolling a 6
group 2 - odds of being female
Define probability, odds, and odds ratio.
probability - measure of likelihood of an event happening

odds - the probability of occurrence over the probability of non-occurrence

odds ratio - comparing the odds of 2 groups
Which study uses odds ratio, cohort or case control?
case control
why use odds ratio?
provides an estimate for the relationship b/w a binary variable (1 & O or nominal data)
What is relative risk?
the risk given one condition versus the risk given the other condition.

A more direct method of calculating 'odds' (for lack of a better word)
True or False

the odds ratio is an accurate estimate of relative risk.
FALSE

it is at least equivalent to but often overestimates relative risk.
Interpret this.
OR= 2.53, 95% CI: 1.66 - 3.55
positive (95% CI: 1.66 - 3.55)

two and a half times more likely to have the outcome (significant b/c CI doesn't include 1.00, therefore equal odds).
Interpret this.
OR= 0.60, 95% CI: 0.26 - 0.92
negative (95% CI: 0.26 - 0.92)

40% less likely to have the outcome (1 - 0.60).

significant b/c CI doesn't include 1.00, therefore equal odds.
In logit, what does the Hosmer and Lemeshow Test tell us?
That is the 'goodness of fit' test. If the test is not significant (p>.05), then the data fits the model.
True or False

A raw score tends to overestimate an adjusted score.
TRUE
What is ethnography?
study of culture

Describes & analyzes aspects of ways of life of a particular culture, subculture, or subculture groups
4 types of qualitative research designs.
phenomenology
grounded theory
ethnography
historical research
What is phenomenology?
to describe the 'lived experience' of study participants
What is grounded theory?
how people deal with a phenomenon over time

explores social processes with the goal of developing a theory
What is historical research?
examines event of the past