Everything in general and Nothing in particular
This type of statistics is used to describe your data without applying hypotheses or methods.
What is descriptive?
This analysis compares a sample mean to a known population mean.
What is one-sample t-test?
This is what you conclude in your statistical test when the probability (p-value) of getting the test statistic is greater than 0.05.
What is fail to reject (accept) the null?
This is the type of data you need for linear regression
What is continuous?
This type of error rejects a true null hypothesis
This type of statistics helps to make inferences about your data using criteria from your data analysis methods.
You'll need two categorical variables to analyze data with this non-parametric analysis.
What is Chi-square test?
When your p-value is less than 0.05, you can reasonably conclude, as long as all other assumptions have been met, the result is this.
What is statistically significant?
This type of regression requires two or more predictor variables.
What is multiple regression?
When you make an error in assessing the correct statistical test, you may need to complete additional testing of this type
These types of analyses involve other assumptions and especially consider non-normally distributed data.
What is non-parametric analyses?
This analysis uses the F-statistic to determine the p-value.
What is ANOVA?
When we make conclusions about multivariate regression, we know that we have determined this when we get a statistically significant result.
What is best-fit model?
This regression is described by the following equation:
z = b2y + b1x + b0
What is multiple regression?
This is an alternative to describing standard deviation
What is standard error of the mean
What is correlation is not causation?
This analysis considers how an intervention may have affected a group of individuals.
What is Paired Samples t-test?
This is what we interpret from the output of a logistic regression
What is odds ratio?
This value in any regression tells us the strength of the relationship between the dependent and independent variables and can sometimes be adjusted.
What is R squared
If a hypothesis test uses 95% confidence, what is the probability of type 1 error?
What is 5% (0.05) ?
A strong correlation typically relies on having this coefficient value or higher.
What is 0.5?
One important piece of interpreting an ANOVA p-value is recognizing that it only tells you there is a difference between the three groups. This is what is does not tell you.
What is where the differences lie?
Linear regressions tells, with statistical significance, that the independent variable explains x% of this in the dependent variable
What is variability? (Variance ok too)
This regression uses categorical data and sometimes dummy variables.
What is logistic regression?
This is an application of type 2 error where there are no false negatives