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.

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Presentation transcript:

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