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Your responses should be substantive, which means they should encourage further dialogue and discussion and persuade your classmates to think about other aspects relevant to the topic. You should share practical examples of key concepts from professional or personal experiences. Additionally, you should compare your response with your classmates’ responses or ask a relevant, meaningful question that will help you understand the concepts better.

Make sure your writing is clear, concise, and organized; demonstrates ethical scholarship in accurate representation and attribution of sources; and displays accurate spelling, grammar, and punctuation.

#1 JJ

In research and statistics, correlation coefficients are used to measure the strength of the relationship between two variables.  Whiston (2013) explains, Pearson correlation coefficient measures to determines the linear relationship between two sets of data using a line graph to represent the data presented.  The Pearson correlation is represented using (p) for the population and ‘r’ for the sample.  The range in the correlation can range from -1 to 1, however true research wouldn't yield an exact number of -1 or 1.  -1 indicates a negative relationship between variables while a 1 indicates a positive.  0 represents that there is no linear relationship.  Ideally, the linear relationship should suggest that the data can be represented using a linear graph.  In addition, Pearson correlation coefficient does not have the ability to determine the difference in dependent and independent variables.  The correlation between the two may yield the same results when assigning a variable as dependent or independent and can only determine if there is a relationship between the two.

A research question example:  Do athletes that consume a high-calorie diet have more body muscle?  The variables to be discussed in this sample research questions would be high-calorie diet and body muscle.  This example is appropriate for this type of correlation test whereas we would identify the positive or negative relationship between the consumption of a higher calorie diet and muscle.  We could determine if athletes who consume higher calories (based on suggested standards) have more body muscle in comparison to body fat.  Also, it could also be determined if there is no relationship between the two.

Reference

Whiston, S. C. (2013). Principles and applications of assessment in counseling (4th ed.). Belmont, CA: Brooks/Cole, Cengage Learning.

#2 LP

Calculating a correlation coefficient is a way to determine the strength of the relationship between two variables. Pearson correlation coefficient is used to examine the linear relationship between two variables and then determine an equation that best fits a line for prediction (Pace, 2008). Suppose a psychologist would like to know the correlation between an athlete’s self-confidence level and the number of games played. Do athletes with higher self-confidence play in more games?

From the research question above, the two variables are athlete’s self-confidence and number of games played. The two scores, self-confidence and games played, must be attained from each athlete. These scores cannot be separated when analyzing data. In other words, athlete A’s self-confidence level must be compared with their own number of games played. Athlete A self-confidence cannot compare to athletes’ B number of games played, and vise versa.

The Pearson correlation coefficient is a definitional formula used on small sets of data (Christensen et. al., 2013). The formula begins by converting the independent variable (self-confidence) and the dependent variable (number of games) data values to z scores. Next, multiply the z scores, add them together, and then divide by the number of cases. Once the number of cases is divided, the average of the multiplied z scores is obtained. This will provide a pattern either positive or negative value for the numerator, which tells if the relationship is positive or negative.