SIRBL Flashcards
Statistics used to analyze nominal and ordinal data are referred to as
nonparametric tests.
do not involve the use of any population parameters. In other words, mean and standard deviation are not needed, and the underlying distribution does not have to be normal.
Nonparametric tests
is a nonparametric statistical test used for comparing categorical information against that we would expect based on previous knowledge. As such, it tests the observed frequency against the expected frequency
compares how well an observed frequency distribution of one nominal variable fits some expected pattern of frequencies
the data are in frequencies
The Chi-Square (X2) Goodness-of-fit Test
*related in chi square
simply count how many individuals from the sample are in each category
Observed Frequency
Is a statistical technique for finding the best-fitting straight line for a set of data. The resulting line is called the regression line.
Regression
is used when you want to predict variables. (e.g., how much will be the jeepney fare if the distance is 5 kilometers?)
Regression
is a model building.
Regression
The is used to determine whether a sample comes from a population with a specific mean.
one-sample t-test
The ________________ is a parametric statistical test that compares the means of two different samples of participants. It indicates whether the two samples perform so similarly that we conclude they are likely from the same population or whether they perform so differently that we conclude they represent two different populations.
control vs treatment group design
independent-groups t-test
The ____ compares the means between two related groups on the same continuous, dependent variable.
dependent t-test (called the paired-samples t-test in SPSS Statistics)
-assumes that the source population is normally distributed
Parametric Tests
-does not make assumptions on the source population
Non-parametric tests
is a type of inferential statistic used to determine if there is a significnt difference between the means of two groups, which may be related in certain features.
T-test
is a statistical test that is used to compare the means of two groups.
it is often used in hypothesis testing to determine whether a process or treatment actually has an effect on the population of interest, or whether two groups are different from one another.
T-test
Is there a difference between a group and the population
One Sample t-test
Is there a difference between two groups
Independent T-test
Same group measured twice
pre and post test
indicates whether there is a difference in teh sample means and wheteher this difference is great than would be expected based on chance
includes two scores for each person
Paired T-test
is there a difference in a group between two points in time
Paired samples t-test
Correlation is a statistical technique that is used to measure and describe the relationship between two variables.
neither variable is manipulated.
Correlation
*Related with correlation
in which higher scores on one variable tend to be associated with higher scores on the other.
positive relationship,
*related with correlation
is one in which higher scores on one variable tend to be associated with lower scores on the other.
A negative relationship
Is a hypothesis testing procedure that is used to compare the differences in the means of two or more groups.
can compare two or more treatments.
ANOVA
- the variable that distingiushes the groups in ANOVA is called
Factor (independent variable)
The invidual conditions or values that define the factor in ANOVA are called the
Levels of the factor
Is used in conjunction with ANOVA to identify exaclty the comparisons that have a significant difference.
Post hoc test
