1. How would the Pearson product-moment correlation look? 2. What is the be
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.
1. How would the Pearson product-moment
2. What is the best path to complete a scatter point with this data, I am not sure I am coming up with the correct response?
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1. Use these data to answer Questions 1a and 1b. These data are saved as Chapter 5 Data Set 2.
a. Compute the Pearson product-moment correlation coefficient by hand and show all your
work.
b. Construct a scatterplot for these 10 pairs of values by hand. Based on the scatterplot, would
you predict the correlation to be direct or indirect? Why?
Number Correct (out of a
Attitude (out of a
possible 20)
possible 100)
17
94
13
73
12
59
Attitude (out of a
Number Correct (out of a
possible 20)
possible 100)
15
80
16
93
14
85
16
66
16
79
18
77
19
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