Basic Statistics
Basics Of Measurement
Sampling Distribution of the Mean: The set of all possible means of samples of a given size taken from a population.
Calculating The Sampling Distribution Of The Mean
1. Collect a sample of a given size (e.g., n=16).
2. Calculate the mean.
3. Plot the mean on a graph.
4. Do this an infinite number of times.
Hypothesis Testing
Null Hypothesis: The assumption that any observed differences in two or more groups is due to chance.
Alpha: The probability of making a Type 1 error.
Type 1 Error: Rejecting the null hypothesis when in fact it is true.
Type 2 Error: Failing to reject the null hypothesis when it is in fact false.
Hypothesis Testing
p-Value: The likelihood of an observed statistic occurring on the basis of the sampling distribution.
Statistically Significant: An outcome is statistically significant if the p-value is less than alpha.
Statistically Nonsignificant: An outcome is statistically nonsignificant if the p-value is greater than alpha.
Hypothesis Testing
Effect Size-The magnitude of the relationship between two or more variables.
Effect Size Of A Correlation-Is obtained by squaring the correlation. For instance, the effect size of two variables is .36 if the correlation is -6.
According to Cohen (1977) a small effect size is .1 or less, a medium effect size is .3, and a large effect size is .5 or greater.
Hypothesis Testing
Statistical Significance = Effect Size x Sample Size
This equation indicates that the larger the effect size the less likely you are to make a Type 2 error.
This equation indicates that the larger the sample size the less likely you are to obtain statistical significance.
Correlation Basics
Scatterplot-A graph in which the predictor variable is the horizontal axis and the outcome variable is the vertical axis.
Regression Line-The line of “best fit” that minimizes the distance of data points from the line.
Linear Relationship-The association between the predictor and outcome variables approximates a straight line.
Correlation Basics
A Few Scatterplots And The Correlations They Produce
Correlation Basics
Regression Lines And Their Relationships