diference beien the experimental With respect to how the variables are dealt wit

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diference beien the experimental With respect to how the variables are dealt with, know vs. correlational methods v the three main characteristics of a correlation (e.g direction, form * Based upon the resuts (writen in words, not notation) of a correlational Be able to identify the most plausible correlation based on a graph. to identify how to correctly interpret that result in words est, be able atching Q': know the four types of correlations we discussed and which scaks measurement are used to measure each of the variables Know where and why correlations are used (prediction, validity, etc.) Know the general diflerence between the two terms: reliability and vakdlity * Know the cautions that should be taken when interpreting correlations (no causation . Identifty (in notation fomal) a set of hypotheses for a comelation (e-g whatis the parae . Know the general formula for a correlation (what information is in the numerator Know the difference between SP and Ss in terms of what they stand for range, etc.) are hypothesizing abour?) denominator of the test statistic (r)-you should know this in words, not notation) Be able to identify the degrees of freedom for a Pearson correlation Know the definition of the coeficient of determination () in words Chapter 16:Introduction to Regression (about 10 Questions . Know the main characteristics of a regression line (e.g central tendency for a relationship, used to predict vakues, etc.) . Know the difference between regression and correlations (regressions used for prediting values) General form la for any near equation (know which variables are the slope and Y.ntercep.) · .What is the diffèerence between Y and Y (hat)? . What is the least-squared-error solution and why is it used? the standard eror of the estimate is conceptually similar to standard error terms for t- lationship between the value of the standard error of the estinate and the accuracy Know that tests . What is the rel of your predictiomst should be taken when using a regression line for prediction (eg restricted range, accuracy of prediction (related to r), ec.) Analys s atio n wordshvariance is being tor and denominator (know what information is contained in the numera n (What variance is being analyaed here and how is it broken down?) Analysis of

Explanation / Answer

Chapter 15:

1. Correlation analysis is performed to understand the linear association between 2 quantitative (continuous preferably) variables.

2. Positive correlation indicates the directly proportional and negative one indicates the inversely proportional relationship. The value varies between -1 to +1 (inclusive). The correlation value closer to -1 or +1 indicates highly significant association.

3. We can test the significance of correlation value using t-test as follows:

t= r*sqrt((n-1)/(1-r^2)); where r= correlation coefficient

4. Correlation are used to model regression equations. For simple linear regression model:

Y=b0+b1*X, degree of determination R-sq= r^2

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