Foundations
Correlational Analyses
Intro to Inferential Statistics & Chi-Square
100

This is the generally accepted p-value for statistical significance. 

What is .05?

100

This is the analysis you would use when interested in the relationship between two or more interval/ratio variables.

What is Pearson's r?

100

When evaluating the differences in expected and observed counts for one nominal variable, you would use this analysis. 

What is one-way chi-square?

200

This statistic calculates the mathematical middle of the data set

What is the mean?

200

This is one of the assumptions of parametric correlational statistics.

What is normality or linearity?

200

This category of statistics has assumptions for the data, and if a data set does not meet those assumptions, the statistic is not appropriate to use.

What are parametric statistics?

300

This category of statistics can only summarize data for individual variables. 

What are descriptive statistics?

300

This is the effect size for correlational statistics.

What is r2?

300

In contrast to descriptive statistics, this category of statistics are used to analyze data in order to answer research questions. 

What are inferential statistics?

400

This is the measure of central tendency that is most sensitive to change.

What is the mean?

400

Regression analyses add this additional information to correlational analyses

What is line of best fit or prediction?

400

This hypothesis states that there is no relationship between the observed variables. 

What is the null hypothesis?

500

This is why it is important for our sample data to match the distribution of the population data.

What is external validity/generalization?

500

These are the values you need to predict someone's score on Y.

What is Y-intercept (a), slope (b), and score on X?

500

Statistical significance tells us if the findings are likely due to chance or not, while _____tells us about the meaningfulness or magnitude of the relationship/difference. 

What is effect size?