quiz 3 review Flashcards
step 1 of hypothesis testing
ID statement of the problem
step 2 of hypothesis testing
ID statistical analysis
step 3 of hypothesis testing
ID statistical or null hypothesis
(no significant differences)
step 4 of hypothesis testing
ID alternative hypotheses
step 5 of hypothesis testing
determine your alpha level
step 6 of hypothesis testing
collect data
step 7 of hypothesis testing
draw a normal curve
step 8 of hypothesis testing
determine table critical values
step 9 of hypothesis testing
run statistical analysis
step 10 of hypothesis testing
plot results on the normal curve and determine results
p = 0.05
95% confident
5% chance type 1 error
p = 0.01
99% confident
1% chance of type 1 error
p = 0.10
90% confident
10% chance of type 1 error
normal distribution: mean median and mode are
all the same
normal distribution: the greatest number of scores will be
in the middle and represent the highest point of the bell curve
standard deviation
variability of scores in relation to the mean
median
middle score
mode
most occuring score
inferential statistics
statistics that allow the researcher to draw conclusions about the target population based on the sample data collected
inferential stats: parametric stats
are calculated for research variables that are interval or ratio level data and the sample collected assumes there is a normal distribution for purposes of generalizing to the population.
inferential stats: non-parametric stats
are calculated for research variables that are ordinal level data or the sample collected does not assume a normal distribution.
type 1 error
incorrect rejection of the null hypothesis when in fact the null hypothesis is true within the population
type 2 error
incorrect acceptance of the null hypothesis when in fact the null hypothesis is false within the population.
correlation research design
focus on determining the relationship among two continuous variables or how much the predictor variable influences the criterion variable.
correlation coefficients range from
-1 to 1
.2 - .5 correlation =
weak
1 correlation coefficient =
perfect relationship
independent groups
include subjects who were each measured once, and the groups are mutually exclusive.
repeated measures groups
: include subjects who were tested at all levels
- pre and post test
- acts as own control
- baseline measures
independent group t test
independent variable has 2 levels
one way analysis of variance (ANOVA)
just like a t test but IV has 3+ levels
ANOVA: F ratio
true variance/error variance
ANOVA: analyze the variation in scores ____ and ____ groups to determine differences
between; within
F = 1
a good thing
probably have significance
F > 1
significance
paired samples t test
repeated measures w/ IV = 2 levels
repeated measures ANOVA
multiple IV levels over multiple time points
- changes over time
factorial ANOVA
interaction between more than one IV, each with their own number of levels
- ex: 3x2
step 1 in managing qual data
organizing data
step 2 in managing qual data
immersion in data
step 3 in managing qual data
generating categories and themes
step 4 in managing qual data
coding
step 5 in managing qual data
offering interpretations through memos
step 6 in managing qual data
searching for alternative understanding
