1/30
Looks like no tags are added yet.
Name | Mastery | Learn | Test | Matching | Spaced |
---|
No study sessions yet.
P-value
The probability of obtaining the data given the null hypothesis is true
Standard Error
the standard deviation of estimates sampling distribution
Sample (frequency) Distribution
the number of times each value occurs for a variable in a sample
Sampling Distribution
The probability distribution of all values for an estimate that we might obtain when we sample a population
Sampling Error
the difference between the estimate and population parameter do to chance
Chi-Square Assumptions
1.no values below 1
2.no more than 20% of expected values should be less than 5
accept null hypothesis
p-value less than .05
reject null hypothesis
p-value greater than 0.05
When to use Chi-squared test
test whether there are differences in proportions between two treatments
Assumptions for ANVOA
1.Normality of Scores
2.Homogeneity
3.Independence of scores
Parametric vs. Non parametric tests
parametric: strictly interval and ratio data- assume normal distribution
non-parametric: nominal and ordinal data- assume not normal distribution
ANOVA Null hypothesis
the means of all the groups are equal
How ANOVA works
assesses whether individuals from other groups are, on average, more different than individuals chosen from the same group
When to use Shapiro-Wilkes
Used to test if the data is normally distributed. Used for linear regression to see if the residuals are normally distributed
Mann-Whitney U test
non-parametric alternative test to test the independent sample t-test
Student’s t-test
statistical test used to compare the means of data values of two populations
Welches t-test
Two-sample t-test with unequal variances adjusts for very unequal variances assumes: normal populations, random, independent, equal sample sizes
Kruskal-Wallis test
The non-parametric equivalent to the one-way ANOVA
Simple Linear Regression
regression analysis involving one independent variable and one dependent variable in which the relationship between the variables is approximated by a straight line
Multiple Linear Regression
A statistical method used to model the relationship between one dependent (or response) variable and two or more independent (or explanatory) variables by fitting a linear equation to observed data
test statistics
A number calculated from the data that is used to evaluate how compatible the data are with the result expected under the null hypothesis.
Probability distribution
A list of mathematical functions describing all the probabilities of mutually exclusive outcomes of a random trail or experiment.
Null Distribution
A sampling distribution of the outcomes for a test statistic given that the null hypothesis is true.
Standard normal distribution
A normal distribution with a mean of 0 and a standard deviation of 1.
Post hoc test
statistical procedure conducted after an ANOVA (Analysis of Variance) to determine which specific group means are significantly different from each other.
Null Hypothesis
a specific statement about a population parameter made for the purpose of argument.
Alternative Hypothesis
includes all other feasible values for the population parameter besides the value stated in the null.
Probability of an event
the proportion of times an event would happen if we repeated the same process continuously
Probability Distribution
A list of mathematical functions describing all the probabilities of mutually exclusive outcomes of a random trail or experiment.
Null Distribution
A sampling distribution of the outcomes for a test statistic given that the null hypothesis is true.
Sampling Bias
systematic discrepancy between the estimate and the actual value caused by human error