4. For the following scores, Y 1 9. a. Sketch a scatter plot and estimate the Pearson con relation. b. Compute the Pearson correlation. 466 O21
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
![Change the sub-questions as follows:
• Compute SS, SP, and r. To do so, create a
worksheet as shown in the Lecture Slide
13 (within Chapter 14 Part 1 file).
• Conduct a hypothesis test (two tails;
alpha=.05). Show the following
intermediate steps:
1. State the hypotheses.
2. Sketch the sampling distribution.
Shade the part of the distribution
you are interested in.
3. Identify critical values using the
Pearson Correlation table (Appendix
В-6).
4. Decide whether you reject or fail to
reject the null hypothesis and
whether X and Y are related in the
population.
• For a regression equation [y = b*x + a],
identify b and a. Hint: you will use SSx
and SP from (1).](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F9b73e317-a1b7-4b0e-beda-10be4573c1de%2F4cc7fe1f-c1b2-4d52-9a63-426381319fb4%2F87mq1h_processed.jpeg&w=3840&q=75)
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